Containers Docker Kind Kubernetes Istio

@arafkarsh arafkarsh
ARAF KARSH HAMID
Co-Founder / CTO
MetaMagic Global Inc., NJ, USA
@arafkarsh
arafkarsh
Microservices
Architecture Series
Building Cloud Native Apps
Docker
Kubernetes, KinD
Service Mesh: Istio
Part 7 of 11

Docker / Kubernetes / Istio
Containers Container Orchestration Service Mesh
2
MicroservicesArchitectureStyles © 2017 byAraf Karsh Hamid is licensed under CC BY 4.0

Slides are color coded based on the topic colors.
Linux Containers
Docker
1
Kubernetes
2
Kubernetes
Networking &
Packet Path
3
Service Mesh: Istio
Best Practices 4
3

• 12 Factor App Methodology
• Docker Concepts
• Images and Containers
• Anatomy of a Dockerfile
• Networking / Volume
Docker
1
• Kubernetes Concepts
• Namespace
• Pods
• RelicaSet
• Deployment
• Service / Endpoints
• Ingress
• Rollout and Undo
• Auto Scale
Kubernetes
2
• API Gateway
• Load Balancer
• Service Discovery
• Config Server
• Circuit Breaker
• Service Aggregator
Infrastructure Design Patterns
4
• Environment
• Config Map
• Pod Presets
• Secrets
3 Kubernetes – Container App Setup
4

• Docker / Kubernetes Networking
• Pod to Pod Networking
• Pod to Service Networking
• Ingress and Egress – Internet
Kubernetes Networking – Packet Path
7
• Kubernetes IP Network
• OSI | L2/3/7 | IP Tables | IP VS |
BGP | VXLAN
• Kube DNS | Proxy
• LB, Cluster IP, Node Port
• Ingress Controller
Kubernetes Networking Advanced
8
• In-Tree & Out-of-Tree Volume Plugins
• Container Storage Interface
• CSI – Volume Life Cycle
• Persistent Volume
• Persistent Volume Claims
• Storage Class
Kubernetes Volumes
5
• Jobs / Cron Jobs
• Quotas / Limits / QoS
• Pod / Node Affinity
• Pod Disruption Budget
• Kubernetes Commands
Kubernetes Advanced Concepts
6
5

• Docker Best Practices
• Kubernetes Best Practices
• Security Best Practices
13 Best Practices
• Istio Concepts / Sidecar Pattern
• Envoy Proxy / Cilium Integration
10 Service Mesh – Istio
• Security
• RBAC
• Mesh Policy | Policy
• Cluster RBAC Config
• Service Role / Role Binding
Istio – Security and RBAC
12
• Gateway / Virtual Service
• Destination Rule / Service Entry
• AB Testing using Canary
• Beta Testing using Canary
Istio Traffic Management
11
• Network Policy L3 / L4
• Security Policy for Microservices
• Weave / Calico / Cilium / Flannel
Kubernetes Network Security Policies
9
6

Agile
Scrum (4-6 Weeks)
Developer Journey
Monolithic
Domain Driven Design
Event Sourcing and CQRS
Waterfall
Optional
Design
Patterns
Continuous Integration (CI)
6/12 Months
Enterprise Service Bus
Relational Database [SQL] / NoSQL
Development QA / QC Ops
7
Microservices
Scrum / Kanban (1-5 Days)
Mandatory
Design
Patterns
CI
DevOps
Event Streaming / Replicated Logs
SQL NoSQL
CD
Container Orchestrator Service Mesh

12 Factor App Methodology
4 Backing Services Treat Backing services like DB, Cache as attached resources
5 Build, Release, Run Separate Build and Run Stages
6 Process Execute App as One or more Stateless Process
7 Port Binding Export Services with Specific Port Binding
8 Concurrency Scale out via the process Model
9 Disposability Maximize robustness with fast startup and graceful exit
10 Dev / Prod Parity Keep Development, Staging and Production as similar as possible
11 Logs Treat logs as Event Streams
12 Admin Process Run Admin Tasks as one of Process
Source:
https://12factor.net/
Factors Description
1 Codebase One Code base tracked in revision control
2 Dependencies Explicitly declare dependencies
3 Configuration Configuration driven Apps
8

Cloud Native
9
Cloud Native computing uses an
opensource software stack
to deploy applications as microservices,
packaging each part into its own container,
and dynamically orchestrating those
containers to optimize resource utilization.
As defined by CNCF
https://www.cncf.io/about/who-we-are/

Docker Containers
• 12 Factor App Methodology
• Docker Concepts
• Images and Containers
• Anatomy of a Dockerfile
• Networking / Volume
Source: https://github.com/MetaArivu/k8s-workshop
10
1

What’s a Container?
Virtual
Machine
Looks like a
Walks like a
Runs like a
Containers are a Sandbox inside Linux Kernel sharing the kernel with
separate Network Stack, Process Stack, IPC Stack etc.
They are NOT Virtual Machines or Light weight Virtual Machines.
11

Servers / Virtual Machines / Containers
Hardware
Host OS
HYPERVISOR
App 1 App 1 App 1
Guest
OS
BINS
/ LIB
Guest
OS
BINS
/ LIB
Guest
OS
BINS
/ LIB
Type 2 Hypervisor
App 2
App 3
App 2
OS
Hardware
Desktop / Laptop
BINS
/ LIB
App
BINS
/ LIB
App
Container 1 Container 2
Type 1 Hypervisor
Hardware
HYPERVISOR
App 1 App 1 App 1
Guest
OS
BINS
/ LIB
Guest
OS
BINS
/ LIB
Guest
OS
BINS
/ LIB
App 2
App 3
App 2
Guest OS
Hardware
Type 1 Hypervisor
BINS
/ LIB
App
BINS
/ LIB
App
BINS
/ LIB
App
Container 1 Container 2 Container 3
HYPERVISOR
Virtualizes the OS
Create Secure Sandboxes in OS
Virtualizes the Hardware
Creates Virtual Machines
Hardware
OS
BINS / LIB
App
1
App
2
App
3
Server
Data Center
No Virtualization
Cloud Elastic Computing
12

Docker containers are Linux Containers
CGROUPS
NAME
SPACES
Copy on
Write
DOCKER
CONTAINER
• Kernel Feature
• Groups Processes
• Control Resource
Allocation
• CPU, CPU Sets
• Memory
• Disk
• Block I/O
• Images
• Not a File System
• Not a VHD
• Basically a tar file
• Has a Hierarchy
• Arbitrary Depth
• Fits into Docker
Registry
• The real magic behind
containers
• It creates barriers
between processes
• Different Namespaces
• PID Namespace
• Net Namespace
• IPC Namespace
• MNT Namespace
• Linux Kernel Namespace
introduced between
kernel 2.6.15 – 2.6.26
docker run
lxc-start
https://access.redhat.com/documentation/en-us/red_hat_enterprise_linux/6/html/resource_management_guide/ch01
13

Docker Container – Linux and Windows
Control Groups
cgroups
Namespaces
Pid, net, ipc, mnt, uts
Layer Capabilities
Union File Systems:
AUFS, btrfs, vfs
Control Groups
Job Objects
Namespaces
Object Namespace, Process
Table. Networking
Layer Capabilities
Registry, UFS like
extensions
Namespaces: Building blocks of the Containers
14

Linux Kernel
HOST OS (Ubuntu)
Client
Docker Daemon
Cent OS
Alpine
Debian
Linux
Kernel
Host Kernel
Host Kernel
Host Kernel
All the containers
will have the same
Host OS Kernel
If you require a
specific Kernel
version, then Host
Kernel needs to be
updated
HOST OS (Windows 10)
Client
Docker Daemon
Nano Server
Server Core
Nano Server
Windows
Kernel
Host Kernel
Host Kernel
Host Kernel
Windows Kernel
15

Docker Key Concepts
1. Docker images
1. A Docker image is a read-only template.
2. For example, an image could contain an Ubuntu operating system with Apache and
your web application installed.
3. Images are used to create Docker containers.
4. Docker provides a simple way to build new images or update existing images, or you
can download Docker images that other people have already created.
5. Docker images are the build component of Docker.
2. Docker containers
1. Docker containers are similar to a directory.
2. A Docker container holds everything that is needed for an application to run.
3. Each container is created from a Docker image.
4. Docker containers can be run, started, stopped, moved, and deleted.
5. Each container is an isolated and secure application platform.
6. Docker containers are the run component of Docker.
3. Docker Registries
1. Docker registries hold images.
2. These are public or private stores from which you upload or download images.
3. The public Docker registry is called Docker Hub.
4. It provides a huge collection of existing images for your use.
5. These can be images you create yourself or you can use images that others have
previously created.
6. Docker registries are the distribution component of Docker.
Images
Containers
16

Docker Daemon
Docker Client
How Docker works….
$ docker search ….
$ docker build ….
$ docker container create ..
Docker Hub
Images
Containers
$ docker container run ..
$ docker container start ..
$ docker container stop ..
$ docker container ls ..
$ docker push ….
$ docker swarm ..
2
1
3
4
1. Search for the Container
2. Docker Daemon Sends the request to Hub
3. Downloads the image
4. Run the Container from the image
17

Docker Image structure
• Images are read-only.
• Multiple layers of image
gives the final Container.
• Layers can be sharable.
• Layers are portable.
• Debian Base image
• Emacs
• Apache
• Writable Container
18

Running a Docker Container
$ ID=$(docker container run -d ubuntu /bin/bash -c “while true; do date; sleep 1; done”)
Creates a Docker Container of Ubuntu OS and runs the container and execute bash shell with a script.
$ docker container logs $ID Shows output from the( bash script) container
$ docker container ls List the running Containers
$ docker pull ubuntu Docker pulls the image from the Docker Registry
When you copy the commands for testing change ”
quotes to proper quotes. Microsoft PowerPoint
messes with the quotes.
19

Anatomy of a Dockerfile
Command Description Example
FROM
The FROM instruction sets the Base Image for subsequent instructions. As such, a
valid Dockerfile must have FROM as its first instruction. The image can be any valid
image – it is especially easy to start by pulling an image from the Public repositories
FROM ubuntu
FROM alpine
MAINTAINER
The MAINTAINER instruction allows you to set the Author field of the generated
images. (Deprecated)
MAINTAINER John Doe
LABEL
The LABEL instruction adds metadata to an image. A LABEL is a key-value pair. To
include spaces within a LABEL value, use quotes and backslashes as you would in
command-line parsing.
LABEL version="1.0”
LABEL vendor=“M2”
RUN
The RUN instruction will execute any commands in a new layer on top of the current
image and commit the results. The resulting committed image will be used for the
next step in the Dockerfile.
RUN apt-get install -y
curl
ADD
The ADD instruction copies new files, directories or remote file URLs from <src> and
adds them to the filesystem of the container at the path <dest>.
ADD hom* /mydir/
ADD hom?.txt /mydir/
COPY
The COPY instruction copies new files or directories from <src> and adds them to the
filesystem of the container at the path <dest>.
COPY hom* /mydir/
COPY hom?.txt /mydir/
ENV
The ENV instruction sets the environment variable <key> to the value <value>. This
value will be in the environment of all "descendent" Dockerfile commands and can be
replaced inline in many as well.
ENV JAVA_HOME /JDK8
ENV JRE_HOME /JRE8
20

Anatomy of a Dockerfile
Command Description Example
VOLUME
The VOLUME instruction creates a mount point with the specified name and marks it as
holding externally mounted volumes from native host or other containers. The value can be a
JSON array, VOLUME ["/var/log/"], or a plain string with multiple arguments, such as VOLUME
/var/log or VOLUME /var/log
VOLUME /data/webapps
USER
The USER instruction sets the user name or UID to use when running the image and for any
RUN, CMD and ENTRYPOINT instructions that follow it in the Dockerfile.
USER johndoe
WORKDIR
The WORKDIR instruction sets the working directory for any RUN, CMD, ENTRYPOINT, COPY
and ADD instructions that follow it in the Dockerfile.
WORKDIR /home/user
CMD
There can only be one CMD instruction in a Dockerfile. If you list more than one CMD then only
the last CMD will take effect.
The main purpose of a CMD is to provide defaults for an executing container. These defaults
can include an executable, or they can omit the executable, in which case you must specify an
ENTRYPOINT instruction as well.
CMD echo "This is a test." |
wc -
EXPOSE
The EXPOSE instructions informs Docker that the container will listen on the
specified network ports at runtime. Docker uses this information to interconnect
containers using links and to determine which ports to expose to the host when
using the –P flag with docker client.
EXPOSE 8080
ENTRYPOINT
An ENTRYPOINT allows you to configure a container that will run as an executable. Command
line arguments to docker run <image> will be appended after all elements in an exec form
ENTRYPOINT, and will override all elements specified using CMD. This allows arguments to be
passed to the entry point, i.e., docker run <image> -d will pass the -d argument to the entry
point. You can override the ENTRYPOINT instruction using the docker run --entrypoint flag.
ENTRYPOINT ["top", "-b"]
21

Docker Image
• Dockerfile
• Docker Container Management
• Docker Images
22

Build Docker Containers as easy as 1-2-3
Create
Dockerfile
1
Build
Image
2
Run
Container
3
23

Build a Docker Java image
1. Create your Dockerfile
• FROM
• RUN
• ADD
• WORKDIR
• USER
• ENTRYPOINT
2. Build the Docker image
3. Run the Container
$ docker build -t org/java:8 .
$ docker container run –it org/java:8
24

Docker Container Management
$ ID=$(docker container run –d ubuntu /bin/bash)
$ docker container stop $ID Start the Container and Store ID in ID field
Stop the container using Container ID
$ docker container stop $(docker container ls –aq)
Stops all the containers
$ docker container rm $ID
Remove the Container
$ docker container rm $(docker container ls –aq)
Remove ALL the Container (in Exit status)
$ docker container prune
Remove ALL stopped Containers)
$ docker container run –restart=Policy –d –it ubuntu /sh Policies = NO / ON-FAILURE / ALWAYS
$ docker container run –restart=on-failure:3
–d –it ubuntu /sh
Will re-start container ONLY 3 times if a
failure happens
$ docker container start $ID
Start the container
25

Docker Container Management
$ ID=$(docker container run –d -i ubuntu)
$ docker container exec -it $ID /bin/bash
Start the Container and Store ID in ID field
Inject a Process into Running Container
$ ID=$(docker container run –d –i ubuntu)
$ docker container exec inspect $ID
Start the Container and Store ID in ID field
Read Containers MetaData
$ docker container run –it ubuntu /bin/bash
# apt-get update
# apt-get install—y apache2
# exit
$ docker container ls –a
$ docker container commit –author=“name” –
message=“Ubuntu / Apache2” containerId apache2
Docker Commit
• Start the Ubuntu Container
• Install Apache
• Exit Container
• Get the Container ID (Ubuntu)
• Commit the Container with new
name
$ docker container run –cap-drop=chown –it ubuntu /sh To prevent Chown inside the Container
Source: https://github.com/meta-magic/kubernetes_workshop
26

Docker Image Commands
$ docker login …. Log into the Docker Hub to Push images
$ docker push image-name Push the image to Docker Hub
$ docker image history image-name Get the History of the Docker Image
$ docker image inspect image-name Get the Docker Image details
$ docker image save –output=file.tar image-name Save the Docker image as a tar ball.
$ docker container export –output=file.tar c79aa23dd2 Export Container to file.
$ docker image rm image-name Remove the Docker Image
$ docker rmi $(docker images | grep '^<none>' | tr -s " " | cut -d " " -f 3)
27

Build Docker Apache image
• FROM alpine
• RUN
• COPY
• EXPOSE
• ENTRYPOINT
$ docker build -t org/apache2 .
$ docker container run –d –p 80:80 org/apache2
$ curl localhost
28

Build Docker Tomcat image
• FROM alpine
• RUN
• COPY
• EXPOSE
• ENTRYPOINT
$ docker build -t org/tomcat .
$ docker container run –d –p 8080:8080 org/tomcat
$ curl localhost:8080
29

Docker Images in the Github Workshop
Ubuntu
JRE 8 JRE 11
Tomcat 8 Tomcat 9
My App 1
Tomcat 9
My App 3
Spring Boot
My App 4
From Ubuntu
Build My Ubuntu
From My Ubuntu
Build My JRE8
From My Ubuntu
Build My JRE11
From My JRE 11
Build My Boot
From My Boot
Build My App 4
From My JRE8
Build My TC8
From My TC8
Build My App 1
My App 2
30

Docker Images in the Github Workshop
Alpine Linux
JRE 8 JRE 11
Tomcat 9 Tomcat 10
My App 1
Tomcat 10
My App 3
Spring Boot
My App 4
From Alpine
Build My Alpine
From My Alpine
Build My JRE8
From My Alpine
Build My JRE11
From My JRE 11
Build My Boot
From My Boot
Build My App 4
From My JRE8
Build My TC9
From My TC8
Build My App 1
My App 2
31

Docker Networking
• Docker Networking – Bridge / Host / None
• Docker Container sharing IP Address
• Docker Communication – Node to Node
• Docker Volumes
32

Docker Networking – Bridge / Host / None
$ docker network ls
$ docker container run --rm --network=host alpine brctl show
$ docker network create tenSubnet –subnet 10.1.0.0/16
33

Docker Networking – Bridge / Host / None
$ docker container run --rm -–net=host alpine ip address
$ docker container run --rm alpine ip address
$ docker container run –rm –net=none alpine ip address
No Network Stack
https://docs.docker.com/network/#network-drivers
34

Docker Containers
Sharing IP Address
$ docker container run --name ipctr –itd alpine
$ docker container run --rm --net container:ipctr alpine ip address
IP
(Container)
Service 1
(Container)
Service 3
(Container)
Service 2
(Container)
$ docker container exec ipctr ip address
35

Docker Networking: Node to Node
Same IP Addresses
for the Containers
across different
Nodes.
This requires NAT.
Container 1
172.17.3.2
Web Server 8080
Veth: eth0
Container 2
172.17.3.3
Microservice 9002
Veth: eth0
Container 3
172.17.3.4
Microservice 9003
Veth: eth0
Container 4
172.17.3.5
Microservice 9004
Veth: eth0
IP tables rules
eth0
10.130.1.101/24
Node 1
Docker0 Bridge 172.17.3.1/16
Veth0 Veth1 Veth2 Veth3
Container 1
172.17.3.2
Web Server 8080
Veth: eth0
Container 2
172.17.3.3
Microservice 9002
Veth: eth0
Container 3
172.17.3.4
Microservice 9003
Veth: eth0
Container 4
172.17.3.5
Microservice 9004
Veth: eth0
IP tables rules
eth0
10.130.1.102/24
Node 2
Veth: eth0
Veth0
Veth Pairs connected to the
container and the Bridge
36

Docker Volumes
$ docker volume create hostvolume
Data Volumes are special directory in the Docker Host.
$ docker volume ls
$ docker container run –it –rm –v hostvolume:/data alpine
# echo “This is a test from the Container” > /data/data.txt
Source:
https://github.com/meta-magic/kubernetes_workshop
37

Docker Volumes
$ docker container run - - rm –v $HOME/data:/data alpine Mount Specific File Path
Source:
38

Kubernetes
39
2

Deployment – Updates and rollbacks, Canary Release
D
ReplicaSet – Self Healing, Scalability, Desired State
R
Worker Node 1
Master Node (Control Plane)
Kubernetes
Architecture
POD
POD itself is a Linux
Container, Docker
container will run inside
the POD. PODs with single
or multiple containers
(Sidecar Pattern) will share
Cgroup, Volumes,
Namespaces of the POD.
(Cgroup / Namespaces)
Scheduler
Controller
Manager
Using yaml or json
declare the desired
state of the app.
State is stored in
the Cluster store.
Self healing is done by Kubernetes using watch loops if the desired state is changed.
POD POD POD
BE
1.2
10.1.2.34
BE
1.2
10.1.2.35
BE
1.2
10.1.2.36
BE
15.1.2.100
DNS: a.b.com 1.2
Service Pod IP Address is dynamic, communication should
be based on Service which will have routable IP
and DNS Name. Labels (BE, 1.2) play a critical role
in ReplicaSet, Deployment, & Services etc.
Cluster
Store
etcd
Key Value
Store
Pod Pod Pod
Label Selector selects pods based on the Labels.
Label
Selector
Label Selector
Label Selector
Node
Controller
End Point
Controller
Deployment
Controller
Pod
Controller
….
Labels
Internet
Firewall K8s Virtual
Cluster
Cloud Controller
For the cloud providers to manage
nodes, services, routes, volumes etc.
Kubelet
Node
Manager
Container
Runtime
Interface
Port 10255
gRPC
ProtoBuf
Kube-Proxy
Network Proxy
TCP / UDP Forwarding
IPTABLES / IPVS
Allows multiple
implementation of
containers from v1.7
RESTful yaml / json
$ kubectl ….
Port 443
API Server
Pod IP ...34 ...35 ...36
EP
• Declarative Model
• Desired State
Key Aspects
N1
N2
N3
Namespace
1
N1
N2
N3
Namespace
2
• Pods
• ReplicaSet
• Deployment
• Service
• Endpoints
• StatefulSet
• Namespace
• Resource Quota
• Limit Range
• Persistent
Volume
Kind
Secrets
Kind
• apiVersion:
• kind:
• metadata:
• spec:
Declarative Model
• Pod
• ReplicaSet
• Service
• Deployment
• Virtual Service
• Gateway, SE, DR
• Policy, MeshPolicy
• RbaConfig
• Prometheus, Rule,
• ListChekcer …
@
@
Annotations
Names
Cluster IP
Node
Port
Load
Balancer
External
Name
@
Ingress
40

Focus on the Declarative Model
41

Ubuntu Installation
Kubernetes Setup – Minikube
$ sudo snap install kubectl --classic Install Kubectl using Snap Package Manager
$ kubectl version Shows the Current version of Kubectl
• Minikube provides a developer environment with master and a single node
installation within the Minikube with all necessary add-ons installed like DNS,
Ingress controller etc.
• In a real world production environment you will have master installed (with a
failover) and ‘n’ number of nodes in the cluster.
• If you go with a Cloud Provider like Amazon EKS then the node will be created
automatically based on the load.
• Minikube is available for Linux / Mac OS and Windows.
$ curl -Lo minikube https://storage.googleapis.com/minikube/releases/v0.30.0/minikube-linux-amd64
$ chmod +x minikube && sudo mv minikube /usr/local/bin/
https://kubernetes.io/docs/tasks/tools/install-kubectl/
Source: https://github.com/meta-magic/kubernetes_workshop 42

Windows Installation
Kubernetes Setup – Minikube
C:> choco install kubernetes-cli Install Kubectl using Choco Package Manager
C:> kubectl version Shows the Current version of Kubectl
Mac OS Installation
$ brew install kubernetes-cli Install Kubectl using brew Package Manager
$ kubectl version Shows the Current version of Kubectl
C:> cd c:usersyouraccount
C:> mkdir .kube
Create .kube directory
$ curl -Lo minikube https://storage.googleapis.com/minikube/releases/latest/minikube-darwin-amd64
$ chmod +x minikube && sudo mv minikube /usr/local/bin/
C:> minikube-installer.exe Install Minikube using Minikube Installer
https://kubernetes.io/docs/tasks/tools/install-kubectl/
Source:
$ brew update; brew cask install minikube Install Minikube using Homebrew or using curl
43

Kubernetes Minikube - Commands
Commands
$ minikube status Shows the status of minikube installation
$ minikube start Start minikube
All workshop examples Source Code: https://github.com/meta-magic/kubernetes_workshop
$ minikube stop Stop Minikube
$ minikube ip Shows minikube IP Address
$ minikube addons list Shows all the addons
$ minikube addons enable ingress Enable ingress in minikube
$ minikube start --memory=8192 --cpus=4 --kubernetes-version=1.14.2 8 GB RAM and 4 Cores
$ minikube dashboard Access Kubernetes Dashboard in minikube
$ minikube start --network-plugin=cni --extra-config=kubelet.network-plugin=cni --memory=5120 With Cilium
Network
Driver
$ kubectl create -n kube-system -f https://raw.githubusercontent.com/cilium/cilium/v1.3/examples/kubernetes/addons/etcd/standalone-etcd.yaml
$ kubectl create -f https://raw.githubusercontent.com/cilium/cilium/v1.3/examples/kubernetes/1.12/cilium.yaml
44

K8s Setup – Master / Nodes : On Premise
Cluster Machine Setup
1. Switch off Swap
2. Set Static IP to Network interface
3. Add IP to Host file
$ k8s-1-cluster-machine-setup.sh
4. Install Docker
5. Install Kubernetes
Run the cluster setup script to install
the Docker and Kubernetes in all the
machines (master and worker node)
1
Master Setup
Setup kubernetes master with pod
network
1. Kubeadm init
2. Install CNI Driver
$ k8s-2-master-setup.sh
$ k8s-3-cni-driver-install.sh
$ k8s-3-cni-driver-uninstall.sh
$ kubectl get po --all-namespaces
Check Driver Pods
Uninstall the driver
2
Node Setup
n1$ kubeadm join --token t IP:Port
Add the worker node to Kubernetes
Master
$ kubectl get nodes
Check Events from namespace
3
$ kubectl get events –n namespace
Check all the nodes
$ sudo ufw enable
$ sudo ufw allow 31100
Source Code: https://github.com/meta-magic/metallb-baremetal-example
Only if the Firewall is blocking your Pod
Al the above-mentioned shell scripts are
available in the Source Code Repository
$ sudo ufw allow 443
45

Kubernetes Setup – Master / Nodes
$ kubeadm init node1$ kubeadm join --token enter-token-from-kubeadm-cmd Node-IP:Port Adds a Node
$ kubectl get nodes $ kubectl cluster-info
List all Nodes
$ kubectl run hello-world --replicas=7 --labels="run=load-balancer-example" --image=metamagic/hello:1.0 --port=8080
Creates a Deployment Object and a ReplicaSet object with 7 replicas of Hello-World Pod running on port 8080
$ kubectl expose deployment hello-world --type=LoadBalancer --name=hello-world-service
List all the Hello-World Deployments
$ kubectl get deployments hello-world
Describe the Hello-World Deployments
$ kubectl describe deployments hello-world
List all the ReplicaSet
$ kubectl get replicasets
Describe the ReplicaSet
$ kubectl describe replicasets
List the Service Hello-World-Service with
Custer IP and External IP
$ kubectl get services hello-world-service
Describe the Service Hello-World-Service
$ kubectl describe services hello-world-service
Creates a Service Object that exposes the deployment (Hello-World) with an external IP Address.
List all the Pods with internal IP Address
$ kubectl get pods –o wide
$ kubectl delete services hello-world-service
Delete the Service Hello-World-Service
$ kubectl delete deployment hello-world
Delete the Hello-Word Deployment
Create a set of Pods for Hello World App with an External IP Address (Imperative Model)
Shows the cluster details
$ kubectl get namespace
Shows all the namespaces
$ kubectl config current-context
Shows Current Context
46

Setup KinD (Kubernetes in Docker)
$ curl -Lo ./kind https://kind.sigs.k8s.io/dl/v0.11.1/kind-linux-amd64
$ chmod +x ./kind
$ mv ./kind /some-dir-in-your-PATH/kind
Linux
Source: https://kind.sigs.k8s.io/docs/user/quick-start/
$ brew install kind
Mac OS via Homebrew
c:> curl.exe -Lo kind-windows-amd64.exe https://kind.sigs.k8s.io/dl/v0.11.1/kind-windows-amd64
c:> Move-Item .kind-windows-amd64.exe c:some-dir-in-your-PATHkind.exe
Windows
o Kind is a tool for running
local Kubernetes clusters
using Docker container
“nodes”.
o Kind was primarily
designed for testing
Kubernetes itself but may
be used for local
development or CI.
47

KinD Creates Cluster(s)
$ kind create cluster $ kind create cluster - -name my2ndcluster
Create a default cluster named kind Create a cluster with a specific name
$ kind create cluster - -config filename.yaml
Create a cluster from a file
$ kind get cluster
List all Clusters
$ kind delete cluster
Delete a Cluster
$ kubectl cluster-info --context kind-kind $ kind load docker-image image1 image2 image3
Load Image into a Cluster (No Repository Needed)
48

KinD Cluster Setup
Single Node Cluster Setup 2 Node Cluster Setup
49

KinD Cluster Setup
3 Node Cluster Setup 5 Node Cluster Setup
50

KinD Cluster Setup + Network Driver
Single Node Cluster Setup
$ kind create cluster --config 1-clusters/alpha-1.yaml
2 Node Cluster Setup
$ kind create cluster --config 1-clusters/beta-2.yaml
$ kind create cluster --config 1-clusters/gama-3.yaml
$ kind create cluster --config 1-clusters/epsilon-5.yaml
$ kubectl apply --filename https://raw.githubusercontent.com/kubernetes/ingress-
nginx/master/deploy/static/provider/kind/deploy.yaml
NGINX Ingress Controller (This is part of shell scripts (Ex. ch1-create-epsilon-cluster ) provided in the GitHub Repo)
Creates 5 Node cluster and Adds NGINX Controller
$ ch1-create-epsilon-cluster
Install 4 Microservices and creates 7 instances
$ ch3-sigma-install-apps
51

KinD Cluster Setup Status
Setting up a 5 Node Cluster
o 2 Master Control Plane
o 3 Worker Node
o External Load Balancer
Setup Network Driver
o Adds NGINX Ingress
Controller
52

KinD Cluster Setup Status
5 Node Cluster Setup Status (Core DNS, API Server, Kube Proxy… ) Control Planes & Worker Nodes
53

KinD – Sigma App Installation Status
Install 4 Microservices and creates 7 instances
$ ch3-sigma-install-apps
54

KinD – Sigma Web App
55

3 Fundamental Concepts
1. Desired State
2. Current State
3. Declarative Model
56

Kubernetes Workload Portability
Goals
1. Abstract away Infrastructure
Details
2. Decouple the App Deployment
from Infrastructure (On-Premise
or Cloud)
To help Developers
1. Write Once, Run Anywhere
(Workload Portability)
2. Avoid Vendor Lock-In
Cloud
On-Premise
57

Kubernetes
Getting Started
• Namespace
• Pods / ReplicaSet / Deployment
• Service / Endpoints
• Ingress
• Rollout / Undo
• Auto Scale
58

Kubernetes Commands – Namespace
(Declarative Model)
$ kubectl config set-context $(kubectl config current-context) --namespace=your-ns
This command will let you switch
the namespace to your namespace
(your-ns).
$ kubectl get namespace
$ kubectl describe ns ns-name
$ kubectl create –f app-ns.yml
List all the Namespaces
Describe the Namespace
Create the Namespace
$ kubectl apply –f app-ns.yml
Apply the changes to the
Namespace
$ kubectl get pods –namespace= ns-name List the Pods from your
namespace
• Namespaces are used to group your teams and software’s in
logical business group.
• A definition of Service will add a entry in DNS with respect to
Namespace.
• Not all objects are there in Namespace. Ex. Nodes, Persistent
Volumes etc.
$ kubectl api-resources --namespaced=your-ns
59

• Pod is a shared environment for one of more
Containers.
• Pod in a Kubernetes cluster has a unique IP
address, even Pods on the same Node.
• Pod is a pause Container
Kubernetes Pods
$ kubectl create –f tc10-nr-Pod.yaml
$ kubectl get pods –o wide –n omega
Atomic Unit
Container
Pod
Virtual Server
Small
Big
60

Kubernetes Commands – Pods
(Declarative Model)
$ kubectl exec pod-name ps aux $ kubectl exec –it pod-name sh
$ kubectl exec –it –container container-name pod-name sh
By default kubectl executes the commands in the first container in the pod. If you are running multiple containers (sidecar
pattern) then you need to pass –container flag and give the name of the container in the Pod to execute your command.
You can see the ordering of the containers and its name using describe command.
$ kubectl get pods
$ kubectl describe pods pod-name
$ kubectl get pods -o json pod-name
$ kubectl create –f app-pod.yml
List all the pods
Describe the Pod details
List the Pod details in JSON format
Create the Pod (Imperative)
Execute commands in the first Container in the Pod Log into the Container Shell
$ kubectl get pods -o wide List all the Pods with Pod IP Addresses
$ kubectl apply –f app-pod.yml
Apply the changes to the Pod
$ kubectl replace –f app-pod.yml
Replace the existing config of the Pod
$ kubectl describe pods –l app=name Describe the Pod based on the
label value
$ kubectl logs pod-name container-name Source: https://github.com/MetaArivu/k8s-workshop
61

• Pods wrap around containers with benefits
like shared location, secrets, networking etc.
• ReplicaSet wraps around Pods and brings in
Replication requirements of the Pod
• ReplicaSet Defines 2 Things
• Pod Template
• Desired No. of Replicas
Kubernetes ReplicaSet
(Declarative Model)
What we want is the Desired State.
Game On!
62

Kubernetes Commands – ReplicaSet
(Declarative Model)
$ kubectl delete rs/app-rs cascade=false
$ kubectl get rs
$ kubectl describe rs rs-name
$ kubectl get rs/rs-name
$ kubectl create –f app-rs.yml
List all the ReplicaSets
Describe the ReplicaSet details
Get the ReplicaSet status
Create the ReplicaSet which will automatically create all the
Pods
Deletes the ReplicaSet. If the cascade=true then deletes all
the Pods, Cascade=false will keep all the pods running and
ONLY the ReplicaSet will be deleted.
$ kubectl apply –f app-rs.yml
Applies new changes to the ReplicaSet. For example, Scaling
the replicas from x to x + new value.
63

Kubernetes Commands – Deployment
(Declarative Model)
• Deployments manages
ReplicaSets and
• ReplicaSets manages
Pods
• Deployment is all about
Rolling updates and
• Rollbacks
• Canary Deployments
64

Kubernetes Commands – Deployment
(Declarative Model)
List all the Deployments
Describe the Deployment details
Show the Rollout status of the Deployment
Creates Deployment
Deployments contains Pods and its Replica information. Based on
the Pod info Deployment will start downloading the containers
(Docker) and will install the containers based on replication factor.
Updates the existing deployment.
Show Rollout History of the Deployment
$ kubectl get deploy app-deploy
$ kubectl describe deploy app-deploy
$ kubectl rollout status deployment app-deploy
$ kubectl rollout history deployment app-deploy
$ kubectl create –f app-deploy.yml
$ kubectl apply –f app-deploy.yml --record
$ kubectl rollout undo deployment app-deploy - -to-revision=1
$ kubectl rollout undo deployment app-deploy - -to-revision=2
Rolls back or Forward to a specific version number
of your app.
$ kubectl scale deployment app-deploy - -replicas=6 Scale up the pods to 6 from the initial 2 Pods.
65

Kubernetes Services
Why do we need Services?
• Accessing Pods from Inside the Cluster
• Accessing Pods from Outside
• Autoscale brings Pods with new IP
Addresses or removes existing Pods.
• Pod IP Addresses are dynamic.
Service Types
1. Cluster IP (Default)
2. Node Port
3. Load Balancer
4. External Name
Service will have a
stable IP Address.
Service uses Labels to
associate with a set
of Pods
66

Kubernetes Commands – Service / Endpoints
(Declarative Model)
$ kubectl delete svc app-service
$ kubectl create –f app-service.yml
List all the Services
Describe the Service details
List the status of the Endpoints
Create a Service for the Pods.
Service will focus on creating a
routable IP Address and DNS for
the Pods Selected based on the
labels defined in the service.
Endpoints will be automatically
created based on the labels in
the Selector.
Deletes the Service.
$ kubectl get svc
$ kubectl describe svc app-service
$ kubectl get ep app-service
$ kubectl describe ep app-service Describe the Endpoint Details
 Cluster IP (default) - Exposes the Service
on an internal IP in the cluster. This type
makes the Service only reachable from
within the cluster.
 Node Port - Exposes the Service on the
same port of each selected Node in the
cluster using NAT. Makes a Service
accessible from outside the cluster
using <NodeIP>:<NodePort>. Superset
of ClusterIP.
 Load Balancer - Creates an external load
balancer in the current cloud (if
supported) and assigns a fixed, external
IP to the Service. Superset of NodePort.
 External Name - Exposes the Service
using an arbitrary name (specified
by external Name in the spec) by
returning a CNAME record with the
name. No proxy is used. This type
requires v1.7 or higher of kube-dns.
67

Kubernetes Ingress
(Declarative Model)
An Ingress is a collection of rules
that allow inbound connections to
reach the cluster services.
Ingress Controllers are Pluggable.
Ingress Controller in AWS is linked to
AWS Load Balancer.
Source: https://kubernetes.io/docs/concepts/services-
networking/ingress/#ingress-controllers
68

Kubernetes Ingress
(Declarative Model)
An Ingress is a collection of rules
that allow inbound connections to
reach the cluster services.
Ingress Controllers are Pluggable.
Ingress Controller in AWS is linked to
AWS Load Balancer.
Source: https://kubernetes.io/docs/concepts/services-networking/ingress/#ingress-controllers
69

Kubernetes Auto Scaling Pods
(Declarative Model)
• You can declare the Auto scaling
requirements for every Deployment
(Microservices).
• Kubernetes will add Pods based on the
CPU Utilization automatically.
• Kubernetes Cloud infrastructure will
automatically add Nodes if it ran out of
available Nodes.
CPU utilization kept at 2% to demonstrate the auto
scaling feature. Ideally it should be around 80% - 90%
70

Kubernetes Horizontal Pod Auto Scaler
$ kubectl autoscale deployment appname --cpu-percent=50 --min=1 --max=10
$ kubectl run -it podshell --image=metamagicglobal/podshell
Hit enter for command prompt
$ while true; do wget -q -O- http://yourapp.default.svc.cluster.local; done
Deploy your app with auto scaling parameters
Generate load to see auto scaling in action
$ kubectl get hpa
$ kubectl attach podshell-name -c podshell -it
To attach to the running container
71

Kubernetes
App Setup
• Environment
• Config Map
• Pod Preset
• Secrets
72

Detach the Configuration information
of the App from the Container Image.
Config Map lets you create multiple
profiles for your Dev, QA and Prod
environment.
Config Map
All the Database configurations like
passwords, certificates, OAuth tokens,
etc., can be stored in secrets.
Secret
Helps you create common
configuration which can be injected to
Pod based on a Criteria (selected using
Label). For Ex. SMTP config, SMS
config.
Pod Preset
Environment option let you pass any
info to the pod thru Environment
Variables.
Environment
Container App Setup
73

Kubernetes Pod Environment Variables

Kubernetes Adding Config to Pod
Config Maps allow you to
decouple configuration artifacts
from image content to keep
containerized applications
portable.
Source: https://kubernetes.io/docs/tasks/configure-pod-container/configure-pod-configmap/
75

Kubernetes Pod Presets
A Pod Preset is an API resource for injecting
additional runtime requirements into a Pod
at creation time. You use label selectors to
specify the Pods to which a given Pod
Preset applies.
Using a Pod Preset allows pod template
authors to not have to explicitly provide all
information for every pod. This way,
authors of pod templates consuming a
specific service do not need to know all the
details about that service.
Source: https://kubernetes.io/docs/concepts/workloads/pods/podpreset/

Kubernetes Pod Secrets
Objects of type secret are intended to hold
sensitive information,
such as passwords,
OAuth tokens, and ssh keys.
Putting this information in a secret is safer
and more flexible than putting it verbatim
in a pod definition or in a docker
Source: https://kubernetes.io/docs/concepts/configuration/secret/

Infrastructure
Design Patterns
• API Gateway
• Load balancer
• Service discovery
• Circuit breaker
• Service Aggregator
• Let-it crash pattern
78

API Gateway Design Pattern – Software Stack
UI
Layer
WS
BL
DL
Database
Shopping Cart
Order
Customer
Product
Firewall
Users
API Gateway
Load
Balancer
Circuit
Breaker
UI
Layer
Web
Services
Business
Logic
Database
Layer
Product
SE
MySQL
DB
Product
Microservice
With 4 node
cluster
Load
Balancer
Circuit
Breaker
UI
Layer
Web
Services
Business
Logic
Database
Layer
Customer
Redis
DB
Customer
Microservice
With 2 node
cluster
Users
Access the
Monolithic
App
Directly
API Gateway (Reverse Proxy Server) routes the traffic
to appropriate Microservices (Load Balancers)
79

API Gateway – Kubernetes Implementation
/customer
/product
/cart
/order
API Gateway
Ingress
Deployment / Replica / Pod Nodes
Kubernetes Objects
Firewall
Customer Pod
Customer Pod
Customer Pod
Customer
Service
N1
N2
N2
EndPoints
Product Pod
Product Pod
Product Pod
Product
Service
N4
N3
MySQL
DB
EndPoints
Review Pod
Review Pod
Review Pod
Review
Service
N4
N3
N1
Service Call
Kube DNS
EndPoints
Internal
Load Balancers
Users
Routing based on Layer 3,4 and 7
Redis
DB
Mongo
DB
Load Balancer
80

API Gateway – Kubernetes / Istio
/customer
/product
/auth
/order
API Gateway
Virtual Service
Istio Sidecar - Envoy
Load Balancer
Firewall
P M C
Istio Control Plane
MySQL
Pod
N4
N3
Destination
Rule
Product Pod
Product Pod
Product Pod
Product
Service
Service Call
Kube DNS
EndPoints
Internal
Load Balancers
81
Kubernetes
Objects
Istio Objects
Users
Review Pod
Review Pod
Review Pod
Review
Service
N1
N4
N3
EndPoints
Customer Pod
Customer Pod
Customer Pod
Customer
Service
N1
N2
N2
Destination
Rule
EndPoints
Redis
DB
Mongo
DB
81

Load Balancer Design Pattern
Firewall
Users
API Gateway
Load
Balancer
Circuit
Breaker
UI
Layer
Web
Services
Business
Logic
Database
Layer
Product
SE
MySQL
DB
Product
Microservice
With 4 node
cluster
Load
Balancer
CB
=
Hystrix
UI
Layer
Web
Services
Business
Logic
Database
Layer
Customer
Redis
DB
Customer
Microservice
With 2 node
cluster
API Gateway (Reverse Proxy Server) routes
the traffic to appropriate Microservices
(Load Balancers)
Load Balancer Rules
1. Round Robin
2. Based on
Availability
3. Based on
Response Time
82

Ingress
Load Balancer – Kubernetes Model
Kubernetes
Objects
Firewall
Users
Product 1
Product 2
Product 3
Product
Service
N4
N3
N1
EndPoints
Internal
Load Balancers
DB
Load Balancer
API Gateway
N1
N2
N2
Customer 1
Customer 2
Customer 3
Customer
Service
EndPoints
DB
Internal
Load Balancers
Pods Nodes
• Load Balancer receives the (request) packet from the User and it picks up
a Virtual Machine in the Cluster to do the internal Load Balancing.
• Kube Proxy using IP Tables redirect the Packet using internal load
Balancing rules.
• Packet enters Kubernetes Cluster and reaches Node (of that specific Pod)
and Node handover the packet to the Pod.
/customer
/product
/cart
83

Service Discovery – NetFlix Network Stack Model
Firewall
Users
API Gateway
Load
Balancer
Circuit
Breaker
Product
MySQL
DB
Product
Microservice
With 4 node
cluster
Load
Balancer
Circuit
Breaker
UI
Layer
Web
Services
Business
Logic
Database
Layer
Customer
Redis
DB
Customer
Microservice
With 2 node
cluster
• In this model Developers write the
code in every Microservice to register
with NetFlix Eureka Service Discovery
Server.
• Load Balancers and API Gateway also
registers with Service Discovery.
• Service Discovery will inform the Load
Balancers about the instance details
(IP Addresses).
Service Discovery
84

Ingress
Service Discovery – Kubernetes Model
Kubernetes
Objects
Firewall
Users
Product 1
Product 2
Product 3
Product
Service
N4
N3
N1
EndPoints
Internal
Load Balancers
DB
API Gateway
N1
N2
N2
Customer 1
Customer 2
Customer 3
Customer
Service
EndPoints
DB
Internal
Load Balancers
Pods Nodes
• API Gateway (Reverse Proxy Server) doesn't know the instances (IP
Addresses) of News Pod. It knows the IP address of the Services
defined for each Microservice (Customer / Product etc.)
• Services handles the dynamic IP Addresses of the pods. Services
Endpoints will automatically discover the new Pods based on Labels.
Service Definition
from Kubernetes
Perspective
/customer
/product
/cart
Service Call
Kube DNS
85

Circuit Breaker Pattern
/ui
/productms
If Product Review is not
available Product service
will return the product
details with a message
review not available.
Reverse Proxy Server
Ingress
Kubernetes Objects
Firewall
UI Pod
UI Pod
UI Pod
UI Service
N1
N2
N2
EndPoints
Product Pod
Product Pod
Product Pod
Product
Service
N4
N3
MySQL
Pod
EndPoints
Internal
Load Balancers
Users
Review Pod
Review Pod
Review Pod
Review
Service
N4
N3
N1
Service Call
Kube DNS
EndPoints
86

Service Aggregator Pattern
/newservice
Ingress
Kubernetes
Objects
Firewall
Service Call
Kube DNS
Users
Internal
Load Balancers
EndPoints News Pod
News Pod
News Pod
News
Service
N4
N3
N2
News Service Portal
• News Category wise
Microservices
• Aggregator Microservice to
aggregate all category of news.
Auto Scaling
• Sports Events (IPL / NBA) spikes
the traffic for Sports Microservice.
• Auto scaling happens for both
News and Sports Microservices.
N1
N2
N2
National
National
National
National
Service
EndPoints
Internal
Load Balancers
DB
N1
N2
N2
Politics
Politics
Politics
Politics
Service
EndPoints
DB
Sports
Sports
Sports
Sports
Service
N4
N3
N1
EndPoints
Internal
Load Balancers
DB
87

Music UI
Play Count
Discography
Albums
88

Service Aggregator Pattern
/artist
Ingress
Kubernetes
Objects
Firewall
Service Call
Kube DNS
Users
Internal
Load Balancers
EndPoints Artist Pod
Artist Pod
Artist Pod
Artist
Service
N4
N3
N2
Spotify Microservices
• Artist Microservice combines all
the details from Discography,
Play count and Playlists.
Auto Scaling
• Scaling of Artist and downstream
Microservices will automatically
scale depends on the load factor.
N1
N2
N2
Discography
Discography
Discography
Discography
Service
EndPoints
Internal
Load Balancers
DB
N1
N2
N2
Play Count
Play Count
Play Count
Play Count
Service
EndPoints
DB
Playlist
Playlist
Playlist
Playlist
Service
N4
N3
N1
EndPoints
Internal
Load Balancers
DB
89

Config Store – Spring Config Server
Firewall
Users
API Gateway
Load
Balancer
Circuit
Breaker
Product
MySQL
DB
Product
Microservice
With 4 node
cluster
Load
Balancer
Circuit
Breaker
UI
Layer
Web
Services
Business
Logic
Database
Layer
Customer
Redis
DB
Customer
Microservice
With 2 node
cluster
• In this model Developers write the
code in every Microservice to
download the required configuration
from a Central server (Ex. Spring
Config Server for the Java World).
• This creates an explicit dependency
order in which service to come up will
be critical.
Config Server
90

Software Network Stack Vs Network Stack
Pattern Software Stack Java Software Stack .NET Kubernetes
1 API Gateway Zuul Server SteelToe K8s Ingress / Istio Envoy
2 Service Discovery Eureka Server SteelToe Kube DNS
3 Load Balancer Ribbon Server SteelToe Istio Envoy
4 Circuit Breaker Hysterix SteelToe Istio
5 Config Server Spring Config SteelToe Secrets, Env - K8s Master
Web Site https://netflix.github.io/ https://steeltoe.io/ https://kubernetes.io/
The Developer needs to write code to integrate with the Software Stack
(Programming Language Specific. For Ex. Every microservice needs to subscribe to
Service Discovery when the Microservice boots up.
Service Discovery in Kubernetes is based on the Labels assigned to Pod and Services
and its Endpoints (IP Address) are dynamically mapped (DNS) based on the Label.
91

Let-it-Crash Design Pattern – Erlang Philosophy
• The Erlang view of the world is that everything is a process and that processes can
interact only by exchanging messages.
• A typical Erlang program might have hundreds, thousands, or even millions of processes.
• Letting processes crash is central to Erlang. It’s the equivalent of unplugging your router
and plugging it back in – as long as you can get back to a known state, this turns out to be
a very good strategy.
• To make that happen, you build supervision trees.
• A supervisor will decide how to deal with a crashed process. It will restart the process, or
possibly kill some other processes, or crash and let someone else deal with it.
• Two models of concurrency: Shared State Concurrency, & Message Passing Concurrency.
The programming world went one way (toward shared state). The Erlang community
went the other way.
• All languages such as C, Java, C++, and so on, have the notion that there is this stuff called
state and that we can change it. The moment you share something you need to bring
Mutex a Locking Mechanism.
• Erlang has no mutable data structures (that’s not quite true, but it’s true enough). No
mutable data structures = No locks. No mutable data structures = Easy to parallelize.
92

Let-it-Crash Design Pattern
1. The idea of Messages as the first class citizens of a system, has been
rediscovered by the Event Sourcing / CQRS community, along with a strong
focus on domain models.
2. Event Sourced Aggregates are a way to Model the Processes and NOT things.
3. Each component MUST tolerate a crash and restart at any point in time.
4. All interaction between the components must tolerate that peers can crash.
This mean ubiquitous use of timeouts and Circuit Breaker.
5. Each component must be strongly encapsulated so that failures are fully
contained and cannot spread.
6. All requests sent to a component MUST be self describing as is practical so
that processing can resume with a little recovery cost as possible after a
restart.
93

Let-it-Crash : Comparison Erlang Vs. Microservices Vs. Monolithic Apps
Erlang Philosophy Micro Services Architecture Monolithic Apps (Java, C++, C#, Node JS ...)
1 Perspective
Everything is a
Process
Event Sourced Aggregates are a way to
model the Process and NOT things.
Things (defined as Objects) and
Behaviors
2
Crash
Recovery
Supervisor will
decide how to
handle the
crashed process
Kubernetes Manager monitors all the
Pods (Microservices) and its Readiness
and Health. K8s terminates the Pod if
the health is bad and spawns a new
Pod. Circuit Breaker Pattern is used
handle the fallback mechanism.
Not available. Most of the monolithic
Apps are Stateful and Crash Recovery
needs to be handled manually and all
languages other than Erlang focuses
on defensive programming.
3 Concurrency
Message Passing
Concurrency
Domain Events for state changes within
a Bounded Context & Integration Events
for external Systems.
Mostly Shared State Concurrency
4 State
Stateless :
Mostly Immutable
Structures
Immutability is handled thru Event
Sourcing along with Domain Events and
Integration Events.
Predominantly Stateful with Mutable
structures and Mutex as a Locking
Mechanism
5 Citizen Messages
Messages are 1st class citizen by Event
Sourcing / CQRS pattern with a strong
focus on Domain Models
Mutable Objects and Strong focus on
Domain Models and synchronous
communication.
94

Summary
Setup
1. Setting up Kubernetes Cluster
• 1 Master and
• 2 Worker nodes
Getting Started
1. Create Pods
2. Create ReplicaSets
3. Create Deployments
4. Rollouts and Rollbacks
5. Create Service
6. Create Ingress
7. App Auto Scaling
App Setup
1. Secrets
2. Environments
3. ConfigMap
4. PodPresets
On Premise Setup
1. Setting up External Load
Balancer using Metal LB
2. Setting up nginx Ingress
Controller
1. API Gateway
2. Service Discovery
3. Load Balancer
4. Config Server
5. Circuit Breaker
6. Service Aggregator Pattern
7. Let It Crash Pattern
95

Kubernetes Pods
Advanced
• Jobs / Cron Jobs
• Quality of Service: Resource Quota and Limits
• Pod Disruption Range
• Pod / Node Affinity
• Daemon Set
• Container Level features
96

Kubernetes Pod Quality of Service
Source: https://kubernetes.io/docs/tasks/configure-pod-container/quality-service-pod/
QoS:
Guaranteed
Memory limit =
Memory Request
CPU Limit =
CPU Request
QoS:
Burstable
!= Guaranteed
and
Has either
Memory OR
CPU Request
QoS:
Best Effort
No
Memory OR
CPU Request /
limits
97

A probe is an indicator to a container's health. It judges the
health through periodically performing a diagnostic action
against a container via kubelet:
• Liveness probe: Indicates whether a container is alive or
not. If a container fails on this probe, kubelet kills it and
may restart it based on the restartPolicy of a pod.
• Readiness probe: Indicates whether a container is ready
for incoming traffic. If a pod behind a service is not
ready, its endpoint won't be created until the pod is
ready.
Kubernetes Pod in Depth
3 kinds of action handlers can be configured to perform
against a container:
exec: Executes a defined command inside the container.
Considered to be successful if the exit code is 0.
tcpSocket: Tests a given port via TCP, successful if the port
is opened.
httpGet: Performs an HTTP GET to the IP address of target
container. Headers in the request to be sent is
customizable. This check is considered to be healthy if the
status code satisfies: 400 > CODE >= 200.
Additionally, there are five parameters to define a probe's behavior:
initialDelaySeconds: How long kubelet should be waiting for before the first probing.
successThreshold: A container is considered to be healthy when getting consecutive times of probing successes
passed this threshold.
failureThreshold: Same as preceding but defines the negative side.
timeoutSeconds: The time limitation of a single probe action.
periodSeconds: Intervals between probe actions. Source: https://github.com/meta-magic/kubernetes_workshop
98

A job creates one or more pods and ensures that a
specified number of them successfully terminate.
As pods successfully complete, the job tracks the
successful completions. When a specified number
of successful completions is reached, the job itself
is complete. Deleting a Job will cleanup the pods it
created.
A simple case is to create one Job object in order to
reliably run one Pod to completion. The Job object
will start a new Pod if the first pod fails or is deleted
(for example due to a node hardware failure or a
node reboot).
A Job can also be used to run multiple pods in
parallel.
Kubernetes Jobs
Source: https://kubernetes.io/docs/concepts/workloads/controllers/jobs-run-to-completion/
Command is wrapped for display purpose.
99

Kubernetes Cron Jobs
Source: https://kubernetes.io/docs/tasks/job/automated-tasks-with-cron-jobs//
Command is wrapped for display purpose.
You can use CronJobs to run jobs on a time-
based schedule. These automated jobs run
like Cron tasks on a Linux or UNIX system.
Cron jobs are useful for creating periodic and
recurring tasks, like running backups or sending
emails. Cron jobs can also schedule individual
tasks for a specific time, such as if you want to
schedule a job for a low activity period
100

• A resource quota, defined by a Resource
Quota object, provides constraints that
limit aggregate resource consumption per
namespace.
• It can limit the quantity of objects that can
be created in a namespace by type, as well
as the total amount of compute resources
that may be consumed by resources in
that project.
Kubernetes Resource Quotas
Source: https://kubernetes.io/docs/concepts/policy/resource-quotas/
101

• Limits specifies the Max resource a Pod
can have.
• If there is NO limit is defined, Pod will
be able to consume more resources
than requests. However, the eviction
chances of Pod is very high if other Pods
with Requests and Resource Limits are
defined.
Kubernetes Limit Range

• Liveness probe: Indicates
whether a container is alive
or not. If a container fails on
this probe, kubelet kills it
and may restart it based on
the restartPolicy of a pod.
Kubernetes
Pod Liveness Probe
Source: https://kubernetes.io/docs/tasks/configure-pod-
container/configure-liveness-readiness-probes/

• A PDB limits the number pods
of a replicated application that
are down simultaneously from
voluntary disruptions.
• Cluster managers and hosting
providers should use tools
which respect Pod Disruption
Budgets by calling the Eviction
API instead of directly deleting
pods.
Kubernetes Pod Disruption Range
Source: https://kubernetes.io/docs/tasks/run-application/configure-pdb/
$ kubectl drain NODE [options]

• You can constrain a pod to only be
able to run on particular nodes or
to prefer to run on particular
nodes. There are several ways to
do this, and they all use label
selectors to make the selection.
• Assign the label to Node
• Assign Node Selector to a Pod
Kubernetes Pod/Node Affinity / Anti-Affinity
Source: https://kubernetes.io/docs/concepts/configuration/assign-pod-node/
$ kubectl label nodes k8s.node1 disktype=ssd

Kubernetes Pod Configuration
Source: https://kubernetes.io/docs/user-journeys/users/application-developer/advanced/
Pod configuration
You use labels and annotations to attach metadata to your resources. To inject data into your
resources, you’d likely create ConfigMaps (for non-confidential data) or Secrets (for confidential data).
Taints and Tolerations - These provide a way for nodes to “attract” or “repel” your Pods. They are often
used when an application needs to be deployed onto specific hardware, such as GPUs for scientific
computing. Read more.
Pod Presets - Normally, to mount runtime requirements (such as environmental variables, ConfigMaps,
and Secrets) into a resource, you specify them in the resource’s configuration file. PodPresets allow you
to dynamically inject these requirements instead, when the resource is created. For instance, this
allows team A to mount any number of new Secrets into the resources created by teams B and C,
without requiring action from B and C.

Kubernetes DaemonSet
A DaemonSet ensures that all (or some) Nodes run a copy of a
Pod. As nodes are added to the cluster, Pods are added to them.
As nodes are removed from the cluster, those Pods are garbage
collected. Deleting a DaemonSet will clean up the Pods it created.
Some typical uses of a DaemonSet are:
• running a cluster storage daemon, such as glusterd, ceph, on
each node.
• running a logs collection daemon on every node, such
as fluentd or logstash.
• running a node monitoring daemon on every node, such
as Prometheus Node Exporter, collectd, Dynatrace OneAgent,
Datadog agent, New Relic agent, Ganglia gmond or Instana
agent.
107

Container-level features
Sidecar container: Although your Pod should still have a single main
container, you can add a secondary container that acts as a helper
(see a logging example). Two containers within a single Pod can
communicate via a shared volume.
Init containers: Init containers run before any of a Pod’s app
containers (such as main and sidecar containers)
Kubernetes Container Level Features
Source: https://kubernetes.io/docs/user-journeys/users/application-developer/advanced/
108

Kubernetes Volumes
• In-Tree and Out-Tree Volume Plugins
• Container Storage Interface – Components
• CSI – Volume Life Cycle
• Persistent Volume
• Persistent Volume Claims
• Storage Class
• Volume Snapshot
109

Kubernetes Workload Portability
Goals
1. Abstract away Infrastructure
Details
2. Decouple the App Deployment
from Infrastructure (On-Premise
or Cloud)
To help Developers
1. Write Once, Run Anywhere
(Workload Portability)
2. Avoid Vendor Lock-In
Cloud
On-Premise
110

K8s Volume Plugin – History
In-Tree Volume Plugins
• First set of Volume plugins with K8s.
• They are linked and compiled and
shipped with K8s releases.
• They were part of Core K8s libraries.
• Volume Driver Development is
tightly coupled with K8s releases.
• Bugs in the Volume Driver crashes
critical K8s components.
• Deprecated since K8s v1.8
Out-of-Tree Volume Plugins
• Flex Volume Driver
• Executable Binaries
• Worker Node communicates
with binaries in CLI.
• Need to access the Root File
System of the Worker Node
• Dependency issues
• CSI – Container Storage Interface
• Address the pain points of Flex
Volume Driver
111

Container Storage Interface
Source:https://blogs.vmware.com/cloudnative/2019/04/18/supercharging-kubernetes-storage-with-csi/
o CSI Spec is Container Orchestrator (CO) neutral
o Uses gRPC for inter-process communication
o Runs Outside CO Processes.
o CSI is control plane only Specs.
o Identity: Identity and capability of the Driver
o Controller: Volume operations such as
provisioning and attachment.
o Node: Mount / unmount ops must be executed
on the node where the volume is needed.
o Identity and Node are mandatory requirement
for the driver implementation.
Container Orchestrator (CO)
Cloud Foundry, Docker, Kubernetes,
Mesos
CSI
Driver
gRPC
Volume
Access
Storage API
Storage
System
112

CSI – Components – 3 gRPC Services on UDS
Controller Service
• Create Volume
• Delete Volume
• List Volume
• Controller Publish Volume
• Controller Unpublish Volume
• Validate Volume Capabilities
• Get Capacity
• Create Snapshot
• Delete Snapshot
• List Snapshots
• Controller Get Capabilities
Node Service
• Node Stage Volume
• Node Unstage Volume
• Node Publish Volume
• Node Unpublish Volume
• Node Get Volume Stats
• Node Get Info
• Node Get Capabilities
Identity Service
• Get Plugin Info
• Get Plugin Properties
• Probe (Probe Request)
Unix Domain Socket
113

StatefulSet Pod
Provisioner CSI
Driver
Attacher
Storage
System
Kubernetes & CSI Drivers
DaemonSet Pod
Registrar CSI
Driver
Kubelet
Worker Node
Master
API Server
etcd
gRPC
gRPC
gRPC
gRPC
Node Service
Identity Service
Controller Service
114

CSI – Volume Life cycle
Controller Service Node Service
CreateVolume ControllerPublishVolume NodeStageVolume
NodeUnStageVolume
NodePublishVolume
NodeUnPublishVolume
DeleteVolume ControllerUnPublishVolume
CREATED NODE_READY VOL_READY PUBLISHED
Volume Created Volume available for use Volume initialized in the
Node. One-time activity.
Volume attached to the Pod
115

Container Storage Interface Adoption
Container
Orchestrator
CO Version CSI Version
Kubernetes
1.10 0.2
1.13 0.3, 1.0
OpenShift 3.11 0.2
Mesos 1.6 0.2
Cloud Foundry 2.5 0.3
PKS 1.4 1.0
116

CSI – Drivers
Name
CSI Production Name
Provisioner
Ver Persistence Access Mode
Dynamic
Provisioning
Raw Block
Support
Volume
Snapshot
1 AWS EBS ebs.csi.aws.com v0.3, v1.0 Yes RW Single Pod Yes Yes Yes
2 AWS EFS efs.csi.aws.com v0.3 Yes RW Multi Pod No No No
3 Azure Disk disk.csi.azure.com v0.3, v1.0 Yes RW Single Pod Yes No No
4 Azure File file.csi.azure.com v0.3, v1.0 Yes RW Multi Pod Yes No No
5 CephFS cephfs.csi.ceph.com v0.3, v1.0 Yes RW Multi Pod Yes No No
6 Ceph RBD rbd.csi.ceph.com v0.3, v1.0 Yes RW Single Pod Yes Yes Yes
7 GCE PD pd.csi.storage.gke.io v0.3, v1.0 Yes RW Single Pod Yes No Yes
8 Nutanix Vol com.nutanix.csi v0.3, v1.0 Yes RW Single Pod Yes No No
9 Nutanix Files com.nutanix.csi v0.3, v1.0 Yes RW Multi Pod Yes No No
10 Portworx pxd.openstorage.org v0.3, v1.1 Yes RW Multi Pod Yes No Yes
Source: https://kubernetes-csi.github.io/docs/drivers.html
117

Kubernetes Volume Types
Host Based
o EmptyDir
o HostPath
o Local
Block Storage
o Amazon EBS
o OpenStack Cinder
o GCE Persistent Disk
o Azure Disk
o vSphere Volume
Others
o iScsi
o Flocker
o Git Repo
o Quobyte
Distributed File System
o NFS
o Ceph
o Gluster
o FlexVolume
o PortworxVolume
o Amazon EFS
o Azure File System
Life cycle of a
Persistent Volume
o Provisioning
o Binding
o Using
o Releasing
o Reclaiming

Ephemeral Storage
Volume Plugin: EmptyDir
o Scratch Space (Temporary) from the
Host Machine.
o Data exits only for the Life Cycle of
the Pod.
o Containers in the Pod can R/W to
mounted path.
o Can ONLY be referenced in-line from
the Pod.
o Can’t be referenced via Persistent
Volume or Claim.
119

Remote Storage Block Storage
o Amazon EBS
o OpenStack Cinder
o GCE Persistent Disk
o Azure Disk
o vSphere Volume
Distributed File System
o NFS
o Ceph
o Gluster
o FlexVolume
o PortworxVolume
o Amazon EFS
o Azure File System
o Remote Storage attached to the
Pod based on the requirement.
o Data persists beyond the life
cycle of the Pod.
o Two Types of Remote Storage
o Block Storage
o File System
o Referenced in the Pod either in-
line or PV/PVC
120

Remote Storage
Kubernetes will do the
following Automatically.
o Kubernetes will attach the
Remote (Block or FS)
Volume to the Node.
o Kubernetes will mount the
volume to the Pod.
This is NOT recommended because it breaks the
Kubernetes principle of workload portability.
121

Deployment and StatefulSet
Source: https://cloud.google.com/kubernetes-engine/docs/concepts/persistent-volumes#deployments_vs_statefulsets
Deployment
Kind: Deployment
• All Replicas of the Deployment share
the same Persistent volume Claim.
• ReadWriteOnce Volumes are NOT
recommended even with ReplicaSet 1
as it can fail or get into a deadlock
(when the Pod goes down and Master
tries to bring another Pod).
• Volumes with ReadOnlyMany &
ReadWriteMany are the best modes.
• Deployments are used for Stateless
Apps
For
Stateful
Apps
StatefulSet
Kind: StatefulSet
• StatefulSet is recommended for App
that need a unique volume per
ReplicaSet.
• ReadWriteOnce should be used with a
StatefulSet. RWO will create a unique
volume per ReplicaSet.
122

Node 3
Node 2
Deployment and StatefulSet
Storage GCE PD
Node 1
D Service1 Pod1
D Service1 Pod2
D Service1 Pod3
Test Case 1
Kind Deployment
Replica 3
Provisioning Storage Class
Volume GCE PD
Volume Type File System
Access Mode ReadWriteOnce (RWO)
Storage NFS
Node 1
D Service1 Pod1
D Service1 Pod2
D Service1 Pod3
Test Case 2
Kind Deployment
Replica 3
Provisioning Persistent Volume
Volume NFS
Access Mode RWX, ReadOnlyMany
Node 3
Node 2
Storage GCE PD
Node 1
S Service2 Pod1
Test Case 3
Kind StatefulSet
Replica 3
Provisioning Storage Class
Volume GCE PD
Access Mode ReadWriteOnce (RWO)
S Service2 Pod2
S Service2 Pod3
Node 3
Node 2
Storage NFS
Node 1
S Service2 Pod1
Test Case 4
Kind StatefulSet
Replica 3
Provisioning Persistent Volume
Volume NFS
Access Mode ReadWriteMany (RWX)
S Service2 Pod2
S Service2 Pod3
Mounted Storage System Mounted Storage System (Shared Drive) Mounted Storage System Mounted Storage System (Shared Drive)
Error Creating Pod
GCE – PD – 10 GB Storage GCE – PD – 10 GB Storage
Source: https://github.com/meta-magic/kubernetes_workshop/tree/master/yaml/volume-nfs-gcppd-scenarios
S1 S3
S2
S3
S2
S1
123

Node 3
Node 2
Deployment/StatefulSet – NFS Shared Disk – 4 PV & 4 PVC
Storage NFS
Node 1
D Service2 Pod1
D Service2 Pod2
D Service2 Pod3
Test Case 6
Kind Deployment
Replica 3
PVC pvc-3gb-disk
Volume NFS
Volume Type File System (ext4)
Node 3
Node 2
Storage NFS
Node 1
S Service4 Pod1
Test Case 8
Kind StatefulSet
Replica 3
PVC pvc-1gb-disk
Volume NFS
S Service4 Pod2
S Service4 Pod3
Mounted Storage System (Shared Drive) Mounted Storage System (Shared Drive)
Node 3
Node 2
Storage NFS
Node 1
D Service1 Pod1
D Service1 Pod2
D Service1 Pod3
Test Case 5
Kind Deployment
Replica 3
PVC pvc-2gb-disk
Volume NFS
Mounted Storage System (Shared Drive)
Node 3
Node 2
Storage NFS
Node 1
D Service3 Pod1
D Service3 Pod2
D Service3 Pod3
Test Case 7
Kind Deployment
Replica 3
PVC pvc-4gb-disk
Volume NFS
Mounted Storage System (Shared Drive)
GCE – PD – 2 GB Storage GCE – PD – 3 GB Storage GCE – PD – 4 GB Storage GCE – PD – 1 GB Storage
Source: https://github.com/meta-magic/kubernetes_workshop/tree/master/yaml/volume-nfs-gcppd-scenarios
PV, PVC mapping is 1:1
124

Volume Plugin: ReadWriteOnce, ReadOnlyMany, ReadWriteMany
Volume Plugin Kind: Deployment Kind: StatefulSet ReadWriteOnce ReadOnlyMany ReadWriteMany
AWS EBS Yes ✓ - -
AzureFile Yes Yes ✓ ✓ ✓
AzureDisk Yes ✓ - -
CephFS Yes Yes ✓ ✓ ✓
Cinder Yes ✓ - -
CSI depends on the driver depends on the driver depends on the driver
FC Yes Yes ✓ ✓ -
Flexvolume Yes Yes ✓ ✓ depends on the driver
Flocker Yes ✓ - -
GCEPersistentDisk Yes Yes ✓ ✓ -
Glusterfs Yes Yes ✓ ✓ ✓
HostPath Yes ✓ - -
iSCSI Yes Yes ✓ ✓ -
Quobyte Yes Yes ✓ ✓ ✓
NFS Yes Yes ✓ ✓ ✓
RBD Yes Yes ✓ ✓ -
VsphereVolume Yes ✓ - - (works when pods are collocated)
PortworxVolume Yes Yes ✓ - ✓
ScaleIO Yes Yes ✓ ✓ -
StorageOS Yes ✓ - -
Source: https://kubernetes.io/docs/concepts/storage/persistent-volumes/
125

Kubernetes Volumes for Stateful Pods
Provision
Network
Storage
Static / Dynamic
1
Request
Storage
2
Use
Storage
3
Static: Persistent Volume
Dynamic: Storage Class
Persistent Volume Claim
Claims are mounted
as Volumes inside the
Pod
126

Storage Class, PV, PVC and Pods
Physical Storage
AWS: EBS, EFS
GCP: PD
Azure: Disk
NFS: Path, Server
Dynamic
Storage Class
Static
Persistent Volume
Persistent Volume Claims
spec:
accessModes:
- ReadWriteOnce
resources:
requests:
storage: 1Gi
storageClassName:
csi-hp-sc
Pod
spec:
volumes
- name: my-csi-v
persisitentVolumeClaim
claimName: my-csi-pvc
Ref: https://rancher.com/blog/2018/2018-09-20-unexpected-kubernetes-part-1/.
127

Kubernetes Volume
Volume
• A Persistent Volume is the
physical storage available.
• Storage Class is used to configure
custom Storage option (nfs, cloud
storage) in the cluster. They are
the foundation of Dynamic
Provisioning.
• Persistent Volume Claim is used
to mount the required storage
into the Pod.
• ReadOnlyMany: Can be
mounted as read-only by many
nodes
• ReadWriteOnce: Can be
mounted as read-write by a
single node
• ReadWriteMany: Can be
mounted as read-write by many
nodes
Access Mode
Source: https://kubernetes.io/docs/concepts/storage/persistent-volumes/#claims-as-volumes
Persistent
Volume
Persistent
Volume Claim
Storage Class
Volume Mode
• There are two modes
• File System and or
• raw Storage Block.
• Default is File System.
Retain: The volume will need to
be reclaimed manually
Delete: The associated storage
asset, such as AWS EBS, GCE PD,
Azure disk, or OpenStack Cinder
volume, is deleted
Recycle: Delete content only (rm
-rf /volume/*) - Deprecated
Reclaim Policy
128

Kubernetes Persistent Volume – AWS EBS
• Use a Network File System or Block Storage for Pods to access
and data from multiple sources. AWS EBS is such a storage
system.
• A Volume is created and its linked with a storage provider. In
the following example the storage provider is AWS for the
EBS.
• Any PVC (Persistent Volume Claim) will be bound to the
Persistent Volume which matches the storage class.
1
Volume ID is auto generated
$ aws ec2 create-volume - -size 100
Storage class is mainly
meant for dynamic
provisioning of the
persistent volumes.
Persistent Volume is not
bound to any specific
namespace.

Persistent Volume – AWS EBS
Pod Access storage by issuing a
Persistent Volume Claim.
In the following example Pod
claims for 2Gi Disk space from
the network on AWS EBS.
• Manual Provisioning of
the AWS EBS supports
ReadWriteMany,
However all the pods
are getting scheduled
into a Single Node.
• For Dynamic
Provisioning use
ReadWriteOnce.
• Google Compute Engine
also doesn't support
ReadWriteMany for
dynamic provisioning.
2
3
https://cloud.google.com/kubernetes-engine/docs/concepts/persistent-volumes
Source:
130

Kubernetes Persistent Volume - hostPath
• HostPath option is to make the Volume available from the
Host Machine.
• A Volume is created and its linked with a storage provider. In
the following example the storage provider is Minikube for
the host path.
• Any PVC (Persistent Volume Claim) will be bound to the
Persistent Volume which matches the storage class.
• If it doesn't match a dynamic persistent volume will be
created.
Storage class is mainly
meant for dynamic
provisioning of the
persistent volumes.
Persistent Volume is not
bound to any specific
namespace.
Host Path is NOT Recommended in Production
1

Persistent Volume - hostPath
Pod Access storage by issuing a
Persistent Volume Claim.
In the following example Pod
claims for 2Gi Disk space from the
network on the host machine.
• Persistent Volume Claim
and Pods with
Deployment properties
are bound to a specific
namespace.
• Developer is focused on
the availability of
storage space using PVC
and is not bothered
about storage solutions
or provisioning.
• Ops Team will focus on
Provisioning of
Persistent Volume and
Storage class.
2
3

Persistent Volume - hostPath
Running the Yaml’s
from the Github
2
3
1
1. Create Static Persistent Volumes OR Dynamic Volumes (using Storage Class)
2. Persistent Volume Claim is created and bound static and dynamic volumes.
3. Pods refer PVC to mount volumes inside the Pod.

Kubernetes Commands
• Kubernetes Commands – Quick Help
• Kubernetes Commands – Field Selectors
134

Kubernetes Commands – Quick Help
$ kubectl create –f app-rs.yml
$ kubectl get rs/app-rs
$ kubectl get rs $ kubectl delete rs/app-rs cascade=false
$ kubectl describe rs app-rs
$ kubectl apply –f app-rs.yml Cascade=true will delete all the pods
$ kubectl get pods
$ kubectl describe pods pod-name
$ kubectl get pods -o json pod-name
$ kubectl create –f app-pod.yml
$ kubectl get pods –show-labels
$ kubectl exec pod-name ps aux
$ kubectl exec –it pod-name sh
Pods
ReplicaSet
(Declarative Model)
$ kubectl get pods –all-namespaces
$ kubectl apply –f app-pod.yml
$ kubectl replace –f app-pod.yml
$ kubectl replace –f app-rs.yml
135

Kubernetes Commands – Quick Help
$ kubectl create –f app-service.yml
$ kubectl get svc
$ kubectl describe svc app-service
$ kubectl get ep app-service
$ kubectl describe ep app-service
$ kubectl delete svc app-service
$ kubectl create –f app-deploy.yml
$ kubectl get deploy app-deploy
$ kubectl describe deploy app-deploy
$ kubectl rollout status deployment app-deploy
$ kubectl apply –f app-deploy.yml
$ kubectl rollout history deployment app-deploy
$ kubectl rollout undo deployment
app-deploy - -to-revision=1
Service
Deployment
(Declarative Model)
$ kubectl apply –f app-service.yml
$ kubectl replace –f app-service.yml
$ kubectl replace –f app-deploy.yml
136

Kubernetes Commands – Field Selectors
$ kubectl get pods --field-selector status.phase=Running Get the list of pods where status.phase = Running
Source: https://kubernetes.io/docs/concepts/overview/working-with-objects/field-selectors/
Field selectors let you select Kubernetes resources based on the value of one or
more resource fields. Here are some example field selector queries:
• metadata.name=my-service
• metadata.namespace!=default
• status.phase=Pending
Supported Operators
You can use the =, ==, and != operators with field selectors (= and == mean the
same thing). This kubectl command, for example, selects all Kubernetes Services
that aren’t in the default namespace:
$ kubectl get services --field-selector metadata.namespace!=default
137

Kubernetes Commands – Field Selectors
$ kubectl get pods --field-selector=status.phase!=Running,spec.restartPolicy=Always
Source: https://kubernetes.io/docs/concepts/overview/working-with-objects/field-selectors/
Chained Selectors
As with label and other selectors, field selectors can be chained together as a
comma-separated list. This kubectl command selects all Pods for which
the status.phase does not equal Running and the spec.restartPolicy field
equals Always:
Multiple Resource Type
You use field selectors across multiple resource types. This kubectl command
selects all Statefulsets and Services that are not in the default namespace:
$ kubectl get statefulsets,services --field-selector metadata.namespace!=default
138

K8s Packet Path
• Kubernetes Networking
• Compare Docker and Kubernetes Networking
• Pod to Pod Networking within the same Node
• Pod to Pod Networking across the Node
• Pod to Service Networking
• Ingress - Internet to Service Networking
• Egress – Pod to Internet Networking
139
3

Kubernetes Networking
Mandatory requirements for Network implementation
1. All Pods can communicate with All other Pods
without using Network Address Translation
(NAT).
2. All Nodes can communicate with all the Pods
without NAT.
3. The IP that is assigned to a Pod is the same IP the
Pod sees itself as well as all other Pods in the
cluster. Source: https://github.com/meta-magic/kubernetes_workshop
140

Docker Networking Vs. Kubernetes Networking
Container 1
172.17.3.2
Web Server 8080
Veth: eth0
Container 2
172.17.3.3
Microservice 9002
Veth: eth0
Container 3
172.17.3.4
Microservice 9003
Veth: eth0
Container 4
172.17.3.5
Microservice 9004
Veth: eth0
IP tables rules
eth0
10.130.1.101/24
Node 1
Container 1
172.17.3.2
Web Server 8080
Veth: eth0
Container 2
172.17.3.3
Microservice 9002
Veth: eth0
Container 3
172.17.3.4
Microservice 9003
Veth: eth0
Container 4
172.17.3.5
Microservice 9004
Veth: eth0
IP tables rules
eth0
10.130.1.102/24
Node 2
Pod 1
172.17.3.2
Web Server 8080
Veth: eth0
Pod 2
172.17.3.3
Microservice 9002
Veth: eth0
Pod 3
172.17.3.4
Microservice 9003
Veth: eth0
Pod 4
172.17.3.5
Microservice 9004
Veth: eth0
IP tables rules
eth0
10.130.1.101/24
Node 1
L2 Bridge 172.17.3.1/16
Same IP Range. NAT Required Uniq IP Range. netFilter, IP Tables / IPVS. No NAT required
Pod 1
172.17.3.6
Web Server 8080
Veth: eth0
Pod 2
172.17.3.7
Microservice 9002
Veth: eth0
Pod 3
172.17.3.8
Microservice 9003
Veth: eth0
Pod 4
172.17.3.9
Microservice 9004
Veth: eth0
IP tables rules
eth0
10.130.1.102/24
Node 2
L2 Bridge 172.17.3.1/16
141

3 Networks
Networks
1. Physical Network
2. Pod Network
3. Service Network
CIDR Range (RFC 1918)
1. 10.0.0.0/8
2. 172.0.0.0/11
3. 192.168.0.0/16
Keep the Address ranges separate – Best Practices
RFC 1918
1. Class A
2. Class B
3. Class C
142

3 Networks
eth0 10.130.1.102/24
Node 1
veth0
eth0
Pod 1
Container 1
172.17.4.1
eth0
Pod 2
Container 1
172.17.4.2
veth1
eth0
10.130.1.103/24
Node 2
veth1
eth0
Pod 1
Container 1
172.17.5.1
eth0
10.130.1.104/24
Node 3
veth1
eth0
Pod 1
Container 1
172.17.6.1
Service
EP EP EP
VIP
192.168.1.2/16
1. Physical Network
2. Pod Network
3. Service Network
End Points
handles
dynamic IP
Addresses of
the Pods
selected by a
Service based
on Pod Labels
Virtual IP doesn’t have any
physical network card or
system attached.
143

Kubernetes: Pod to Pod Networking inside a Node
By Default Linux has a Single Namespace and all the process in
the namespace share the Network Stack. If you create a new
namespace then all the process running in that namespace will
have its own Network Stack, Routes, Firewall Rules etc.
$ ip netns add namespace1
A mount point for namespace1 is created under /var/run/netns
Create Namespace
$ ip netns List Namespace
eth0 10.130.1.101/24
Node 1
Root NW Namespace
L2 Bridge 10.17.3.1/16
veth0 veth1
Forwarding
Tables
Bridge
implements
ARP
to
discover
link-
layer
MAC
Address
eth0
Container 1
10.17.3.2
Pod 1
Container 2
10.17.3.2
eth0
Pod 2
Container 1
10.17.3.3
1. Pod 1 sends packet to eth0 – eth0 is connected to
veth0
2. Bridge resolves the Destination with ARP protocol and
3. Bridge sends the packet to veth1
4. veth1 forwards the packet directly to Pod 2 thru eth0
of the Pod 2
1
2
4
3
This entire communication happens in localhost. So, Data
transfer speed will NOT be affected by Ethernet card speed.
Kube Proxy
144

eth0 10.130.1.102/24
Node 2
Root NW Namespace
L2 Bridge 10.17.4.1/16
veth0
Kubernetes: Pod to Pod Networking Across Node
eth0 10.130.1.101/24
Node 1
Root NW Namespace
L2 Bridge 10.17.3.1/16
veth0 veth1
Forwarding
Tables
eth0
Container 1
10.17.3.2
Pod 1
Container 2
10.17.3.2
eth0
Pod 2
Container 1
10.17.3.3
1. Pod 1 sends packet to eth0 –
eth0 is connected to veth0
2. Bridge will try to resolve the
Destination with ARP protocol
and ARP will fail because there
is no device connected to that
IP.
3. On Failure Bridge will send the
packet to eth0 of the Node 1.
4. At this point packet leaves eth0
and enters the Network and
network routes the packet to
Node 2.
5. Packet enters the Root
namespace and routed to the
L2 Bridge.
6. veth0 forwards the packet to
eth0 of Pod 3
1
2
4
3
eth0
Pod 3
Container 1
10.17.4.1
5
6
Kube Proxy
Kube Proxy
Src-IP:Port: Pod1:17711 – Dst-IP:Port: Pod3:80
145

eth0 10.130.1.102/24
Node 2
Root NW Namespace
L2 Bridge 10.17.4.1/16
veth0
Kubernetes: Pod to Service to Pod – Load Balancer
eth0 10.130.1.101/24
Node 1
Root NW Namespace
L2 Bridge 10.17.3.1/16
veth0 veth1
Forwarding
Tables
eth0
Container 1
10.17.3.2
Pod 1
Container 2
10.17.3.2
eth0
Pod 2
Container 1
10.17.3.3
1. Pod 1 sends packet to eth0 – eth0 is
connected to veth0
2. Bridge will try to resolve the Destination
with ARP protocol and ARP will fail
because there is no device connected to
that IP.
3. On Failure Bridge will give the packet to
Kube Proxy
4. it goes thru ip tables rules installed by
Kube Proxy and rewrites the Dst-IP with
Pod3-IP. IPVS has done the Cluster load
Balancing directly on the node and
packet is given to eth0 of the Node1.
5. Now packet leaves Node 1 eth0 and
enters the Network and network routes
the packet to Node 2.
6. Packet enters the Root namespace and
routed to the L2 Bridge.
7. veth0 forwards the packet to eth0 of
Pod 3
1
2
4
3
eth0
Pod 3
Container 1
10.17.4.1
5
6
Kube Proxy
Kube Proxy
7
SrcIP:Port: Pod1:17711 – Dst-IP:Port: Service1:80 Src-IP:Port: Pod1:17711 – Dst-IP:Port: Pod3:80
Order Payments
146

eth0 10.130.1.102/24
Node 2
Root NW Namespace
L2 Bridge 10.17.4.1/16
veth0
Kubernetes Pod to Service to Pod – Return Journey
eth0 10.130.1.101/24
Node 1
Root NW Namespace
L2 Bridge 10.17.3.1/16
veth0 veth1
Forwarding
Tables
eth0
Container 1
10.17.3.2
Pod 1
Container 2
10.17.3.2
eth0
Pod 2
Container 1
10.17.3.3
1. Pod 3 receives data from Pod 1 and
sends the reply back with Source as
Pod3 and Destination as Pod1
with ARP protocol and ARP will fail
because there is no device connected to
that IP.
3. On Failure Bridge will give the packet
Node 2 eth0
4. Now packet leaves Node 2 eth0 and
enters the Network and network routes
the packet to Node 1. (Dst = Pod1)
5. it goes thru ip tables rules installed by
Kube Proxy and rewrites the Src-IP with
Service-IP. Kube Proxy gives the packet
to L2 Bridge.
6. L2 bridge makes the ARP call and hand
over the packet to veth0
Pod1
1
2
4
3
eth0
Pod 3
Container 1
10.17.4.1
5
6
Kube Proxy
Kube Proxy
7
Src-IP: Pod3:80 – Dst-IP:Port: Pod1:17711
Src-IP:Port: Service1:80– Dst-IP:Port: Pod1:17711
Order
Payments
147

eth0 10.130.1.102/24
Node X
Root NW Namespace
L2 Bridge 10.17.4.1/16
veth0
Kubernetes: Internet to Pod 1. Client Connects to App published
Domain.
2. Once the Ingress Load Balancer
receives the packet it picks a VM (K8s
Node).
3. Once inside the VM IP Tables knows
how to redirect the packet to the Pod
using internal load Balancing rules
installed into the cluster using Kube
Proxy.
4. Traffic enters Kubernetes cluster and
reaches the Node X (10.130.1.102).
5. Node X gives the packet to the L2
Bridge
6. L2 bridge makes the ARP call and hand
over the packet to veth0
Pod 8
1
2
4
3
5
6
7
Src: Client IP –
Dst: App Dst
Src: Client IP –
Dst: Pod IP
Ingress
Load
Balancer
Client /
User
Src: Client IP –
Dst: VM-IP
eth0
Pod 8
Container 1
10.17.4.1
Kube Proxy
VM
VM
VM
148

Kubernetes: Pod to Internet
eth0 10.130.1.101/24
Node 1
Root NW Namespace
L2 Bridge 10.17.3.1/16
veth0 veth1
Forwarding
Tables
eth0
Container 1
10.17.3.2
Pod 1
Container 2
10.17.3.2
eth0
Pod 2
Container 1
10.17.3.3
1. Pod 1 sends packet to eth0 – eth0 is
connected to veth0
with ARP protocol and ARP will fail because
there is no device connected to that IP.
3. On Failure Bridge will give the packet to IP
Tables
4. The Gateway will reject the Pod IP as it will
recognize only the VM IP. So, source IP is
replaced with VM-IP (NAT)
5. Packet enters the network and routed to
Internet Gateway.
6. Packet reaches the GW and it replaces the
VM-IP (internal) with an External IP.
7. Packet Reaches External Site (Google)
1
2
4
3
5
6
Kube Proxy
7
Src: Pod1 – Dst: Google Src: VM-IP –
Dst: Google
Gateway
Google
Src: Ex-IP –
Dst: Google
On the way back the packet follows the same
path and any Src IP mangling is undone, and
each layer understands VM-IP and Pod IP within
Pod Namespace.
VM
149

Kubernetes
Networking Advanced
• Kubernetes IP Network
• OSI Layer | L2 | L3 | L4 | L7 |
• IP Tables | IPVS | BGP | VXLAN
• Kubernetes DNS
• Kubernetes Proxy
• Kubernetes Load Balancer, Cluster IP, Node Port
• Kubernetes Ingress
• Kubernetes Ingress – Amazon Load Balancer
• Kubernetes Ingress – Metal LB (On Premise)
150

Kubernetes Network Requirements
1. IPAM (IP Address Management & Life
cycle Management of Network
Devices
2. Connectivity and Container Network
3. Route Advertisement
151

OSI Layers
152

Networking Glossary
Netfilter – Packet Filtering in Linux
Software that does packet filtering, NAT and other
Packet mangling
IP Tables
It allows Admin to configure the netfilter for
managing IP traffic.
ConnTrack
Conntrack is built on top of netfilter to handle
connection tracking..
IPVS – IP Virtual Server
Implements a transport layer load balancing as part
of the Linux Kernel. It’s similar to IP Tables and
based on netfilter hook function and uses hash
table for the lookup.
Border Gateway Protocol
BGP is a standardized exterior gateway protocol
designed to exchange routing and reachability
information among autonomous systems (AS) on
the Internet. The protocol is often classified as a
path vector protocol but is sometimes also classed
as a distance-vector routing protocol. Some of the
well known & mandatory attributes are AS Path,
Next Hop Origin.
L2 Bridge (Software Switch)
Network devices, called switches (or bridges) are
responsible for connecting several network links to
each other, creating a LAN. Major components of a
network switch are a set of network ports, a control
plane, a forwarding plane, and a MAC learning
database. The set of ports are used to forward traffic
between other switches and end-hosts in the
network. The control plane of a switch is typically used
to run the Spanning Tree Protocol, that calculates a
minimum spanning tree for the LAN, preventing
physical loops from crashing the network. The
forwarding plane is responsible for processing input
frames from the network ports and making a
forwarding decision on which network port or ports
the input frame is forwarded to.
153

Networking Glossary
Layer 2 Networking
Layer 2 is the Data Link Layer (OSI Mode) providing Node to
Node Data Transfer. Layer 2 deals with delivery of frames
between 2 adjacent nodes on a network. Ethernet is an Ex.
Of Layer 2 networking with MAC represented as a Sub Layer.
Flannel uses L3 with VXLAN (L2) networking.
Layer 4 Networking
Transport layer controls the reliability of a given link
through flow control.
Layer 7 Networking
Application layer networking (HTTP, FTP etc.,) This is the
closet layer to the end user. Kubernetes Ingress Controller
is a L7 Load Balancer.
Layer 3 Networking
Layer 3’s primary concern involves routing packets between
hosts on top of the layer 2 connections. IPv4, IPv6, and ICMP
are examples of Layer 3 networking protocols. Calico uses L3
networking.
VXLAN Networking
Virtual Extensible LAN used to help large cloud
deployments by encapsulating L2 Frames within UDP
Datagrams. VXLAN is similar to VLAN (which has a
limitation of 4K network IDs). VXLAN is an encapsulation
and overlay protocol that runs on top of existing Underlay
networks. VXLAN can have 16 million Network IDs.
Overlay Networking
An overlay network is a virtual, logical network built on
top of an existing network. Overlay networks are often
used to provide useful abstractions on top of existing
networks and to separate and secure different logical
networks.
Source Network Address Translation
SNAT refers to a NAT procedure that modifies the source
address of an IP Packet.
Destination Network Address Translation
DNAT refers to a NAT procedure that modifies the
Destination address of an IP Packet.
154

eth0 10.130.1.102
Node / Server 1
172.17.4.1
VSWITCH
172.17.4.1
Customer 1
Customer 2
eth0 10.130.2.187
Node / Server 2
172.17.5.1
VSWITCH
172.17.5.1
Customer 1
Customer 2
VXLAN Encapsulation
10.130.1.0/24 10.130.2.0/24
Underlay Network
VSWITCH: Virtual Switch
Switch Switch
Router
155

eth0 10.130.1.102
Node / Server 1
172.17.4.1
VSWITCH
VTEP
172.17.4.1
Customer 1
Customer 2
eth0 10.130.2.187
Node / Server 2
172.17.5.1
VSWITCH
VTEP
172.17.5.1
Customer 1
Customer 2
VXLAN Encapsulation
Overlay Network
VSWITCH: Virtual Switch. | VTEP : Virtual Tunnel End Point
VXLAN encapsulate L2 into UDP
packets tunneling using L3. This
means no specialized hardware
required. So, the Overlay networks
could be created purely in
Software.
VLAN = 4094 (2 reserved) Networks
VNI = 16 Million Networks (24-bit ID)
156

eth0 10.130.1.102
Node / Server 1
172.17.4.1
VSWITCH
VTEP
172.17.4.1
Customer 1
Customer 2
eth0 10.130.2.187
Node / Server 2
172.17.5.1
VSWITCH
VTEP
172.17.5.1
Customer 1
Customer 2
VXLAN Encapsulation
Overlay Network
ARP Broadcast ARP Broadcast
ARP Broadcast
Multicast
VSWITCH: Virtual Switch. | VTEP : Virtual Tunnel End Point
ARP Unicast
157

eth0 10.130.1.102
Node / Server 1
172.17.4.1
B1 – MAC
VSWITCH
VTEP
172.17.4.1
Y1 – MAC
Customer 1
Customer 2
eth0 10.130.2.187
Node / Server 2
172.17.5.1
B2 – MAC
VSWITCH
VTEP
172.17.5.1
Y2 – MAC
Customer 1
Customer 2
VXLAN Encapsulation
Overlay Network
Src: 172.17.4.1
Src: B1 – MAC
Dst: 172.17.5.1
Dst: B2 - MAC
Src: 10.130.1.102
Dst: 10.130.2.187
Src UDP Port: Dynamic
Dst UDP Port: 4789
VNI: 100
Src: 172.17.4.1
Src: B1 – MAC
Dst: 172.17.5.1
Dst: B2 - MAC
Src: 172.17.4.1
Src: B1 – MAC
Dst: 172.17.5.1
Dst: B2 - MAC
VSWITCH: Virtual Switch. | VTEP : Virtual Tunnel End Point | VNI : Virtual Network Identifier
158

eth0 10.130.1.102
Node / Server 1
172.17.4.1
B1 – MAC
VSWITCH
VTEP
172.17.4.1
Y1 – MAC
Customer 1
Customer 2
eth0 10.130.2.187
Node / Server 2
172.17.5.1
B2 – MAC
VSWITCH
VTEP
172.17.5.1
Y2 – MAC
Customer 1
Customer 2
VXLAN Encapsulation
Overlay Network
Src: 10.130.2.187
Dst: 10.130.1.102
Dst UDP Port: 4789
VNI: 100
Src: 172.17.5.1
Src: B2 - MAC
Dst: 172.17.4.1
Dst: B1 – MAC
Src: 172.17.5.1
Src: B2 - MAC
Dst: 172.17.4.1
Dst: B1 – MAC
Src: 172.17.5.1
Src: B2 - MAC
Dst: 172.17.4.1
Dst: B1 – MAC
159

eth0 10.130.1.102
Node / Server 1
172.17.4.1
B1 – MAC
VSWITCH
VTEP
172.17.4.1
Y1 – MAC
Customer 1
Customer 2
eth0 10.130.2.187
Node / Server 2
172.17.5.1
B2 – MAC
VSWITCH
VTEP
172.17.5.1
Y2 – MAC
Customer 1
Customer 2
VXLAN Encapsulation
Overlay Network
Src: 172.17.4.1
Src: Y1 – MAC
Dst: 172.17.5.1
Dst: Y2 - MAC
Src: 10.130.1.102
Dst: 10.130.2.187
Dst UDP Port: 4789
VNI: 200
Src: 172.17.4.1
Src: Y1 – MAC
Dst: 172.17.5.1
Dst: Y2 - MAC
Src: 172.17.4.1
Src: Y1 – MAC
Dst: 172.17.5.1
Dst: Y2 - MAC
160

eth0 10.130.1.102
Node / Server 1
172.17.4.1
B1 – MAC
VSWITCH
VTEP
172.17.4.1
Y1 – MAC
Customer 1
Customer 2
eth0 10.130.2.187
Node / Server 2
172.17.5.1
B2 – MAC
VSWITCH
VTEP
172.17.5.1
Y2 – MAC
Customer 1
Customer 2
VXLAN Encapsulation
Overlay Network
VNI: 100
VNI: 200
161

Kubernetes Network Support
Features L2 L3 Overlay Cloud
Pods Communicate
using L2 Bridge
Pod Traffic is routed
in underlay network
Pod Traffic is
encapsulated &
uses underlay for
reachability
Pod Traffic is routed
in Cloud Virtual
Network
Technology Linux L2 Bridge
L2 ARP
Routing Protocol
BGP
VXLAN Amazon EKS
Google GKE
Encapsulation No No Yes No
Example Cilium Calico, Cilium Flannel, Weave,
Cilium
AWS EKS,
Google GKE,
Microsoft ACS
162

3 Networks
eth0 10.130.1.102/24
Node 1
veth0
eth0
Pod 1
Container 1
172.17.4.1
eth0
Pod 2
Container 1
172.17.4.2
veth1
eth0
10.130.1.103/24
Node 2
veth1
eth0
Pod 1
Container 1
172.17.5.1
eth0
10.130.1.104/24
Node 3
veth1
eth0
Pod 1
Container 1
172.17.6.1
Service
EP EP EP
VIP
192.168.1.2/16
1. Physical Network
2. Pod Network
3. Service Network
End Points
handles
dynamic IP
Addresses of
the Pods
selected by a
Service based
on Pod Labels
Virtual IP doesn’t have any
physical network card or
system attached.
Virtual Network - L2 / L3 /Overlay / Cloud
163

Kubernetes DNS / Core DNS v1.11 onwards
Kubernetes DNS to avoid IP Addresses in the configuration or Application Codebase.
It Configures Kubelet running on each Node so the containers uses DNS Service IP to
resolve the IP Address.
A DNS Pod consists of three separate containers
1. Kube DNS: Watches the Kubernetes Master for changes in Service and Endpoints
2. DNS Masq: Adds DNS caching to Improve the performance
3. Sidecar: Provides a single health check endpoint to perform health checks for
Kube DNS and DNS Masq.
• DNS Pod itself is a Kubernetes Service with a Cluster IP.
• DNS State is stored in etcd.
• Kube DNS uses a library the converts etcd name – value pairs into DNS Records.
• Core DNS is similar to Kube DNS but with a plugin Architecture in v1.11 Core DNS is
the default DNS Server. Source: https://github.com/meta-magic/kubernetes_workshop
164

Kube Proxy
Kube-proxy comes close to Reverse Proxy model from design perspective. It can also
work as a load balancer for the Service’s Pods. It can do simple TCP, UDP, and SCTP
stream forwarding or round-robin TCP, UDP, and SCTP forwarding across a set of
backend.
• When Service of the type “ClusterIP” is created, the system assigns a virtual IP to it
and there is no network interface or MAC address associated with it.
• Kube-Proxy uses netfilter and iptables in the Linux kernel for the routing including
VIP.
Proxy Type
• Tunnelling proxy passes
unmodified requests from
clients to servers on some
network. It works as
a gateway that enables
packets from one network
access servers on another
network.
• A forward proxy is an
Internet-facing proxy
that mediates client
connections to web
resources/servers on
the Internet.
• A Reverse proxy is an
internal-facing proxy. It
takes incoming requests
and redirects them to
some internal server
without the client knowing
which one he/she is
accessing.
Load balancing between backend
Pods is done by the round-robin
algorithm by default. Other
supported Algos:
1. lc: least connection
2. dh: destination hashing
3. sh: source hashing
4. sed: shortest expected delay
5. nq: never queue
Kube-Proxy can work in 3 modes
1. User space
2. IPTABLES
3. IPVS
The differences comes in how Kube-Proxy
interact with User Space and Kernel Space.
How this is different for each of the modes
by routing the traffic to service and then
doing load balancing.
165

Kubernetes Cluster IP, Load Balancer, & Node Port
LoadBalancer:
This is the standard way to expose
service to the internet. All the traffic on
the port is forwarded to the service. It's
designed to assign an external IP to
act as a load balancer for the
service. There's no filtering, no
routing. LoadBalancer uses cloud
service or MetalLB for on-premise.
Cluster IP:
Cluster IP is the default and
used when access within the
cluster is required. We use this
type of service when we want to
expose a service to other pods
within the same cluster. This
service is accessed using
kubernetes proxy.
Nodeport:
Opens a port in the Node when Pod
needs to be accessed from outside
the cluster. Few Limitations & hence
its not advised to use NodePort
• only one service per port
• Ports between 30,000-32,767
• HTTP Traffic exposed in non std
port
• Changing node/VM IP is difficult
166

K8s Cluster IP:
Kube Proxy
Service
Pods Pods Pods
Traffic
Kubernetes
Cluster
Node Port:
VM
Service
Pods Pods Pods
Traffic
VM VM
NP: 30000 NP: 30000 NP: 30000
Kubernetes
Cluster
Load Balancer:
Load Balancer
Service
Pods Pods Pods
Traffic
Kubernetes
Cluster
Ingress: Does Smart Routing
Ingress Load Balancer
Order
Pods Pods Pods
Traffic
Kubernetes Cluster
Product
Pods Pods Pods
/order /product
Review
Pods Pods Pods
167

Ingress An Ingress can be configured to give Services
1. Externally-reachable URLs,
2. Load balance traffic,
3. Terminate SSL / TLS, and offer
4. Name based Virtual hosting.
An Ingress controller is responsible for fulfilling the Ingress,
usually with a load balancer, though it may also configure
your edge router or additional frontends to help handle the
traffic.
Smart Routing
Order
Pods Pods Pods
Traffic
Kubernetes Cluster
Product
Pods Pods Pods
/order /product
Review
Pods Pods Pods
Source: https://kubernetes.io/docs/concepts/services-networking/ingress/
An Ingress does not expose
arbitrary ports or
protocols. Exposing
services other than HTTP
and HTTPS to the internet
typically uses a service of
type
Service.Type=NodePort or
Service.Type=LoadBalancer.
168

Ingress
Smart Routing
Order
Pods Pods Pods
Traffic
Kubernetes Cluster
Product
Pods Pods Pods
/order /product
Review
Pods Pods Pods
Ingress Rules
1. Optional Host – If Host is
specified then the rules will
be applied to that host.
2. Paths – Each path under a
host can routed to a specific
backend service
3. Backend is a combination of
Service and Service Ports
169

Ingress
Smart Routing
Order
Pods Pods Pods
Traffic
Kubernetes Cluster
Product
Pods Pods Pods
/order /product
Review
Pods Pods Pods
Ingress Rules
1. Optional Host – If Host is
specified then the rules will
be applied to that host.
2. Paths – Each path under a
host can routed to a specific
backend service
3. Backend is a combination of
Service and Service Ports
170

Ingress
Smart Routing
Order
Pods Pods Pods
Traffic
Kubernetes Cluster
Product
Pods Pods Pods
/order /product
Review
Pods Pods Pods
Name based
Virtual Hosting
171

Smart Routing
Order
Pods Pods Pods
Traffic
Kubernetes Cluster
Product
Pods Pods Pods
/order /product
Review
Pods Pods Pods
Ingress – TLS
172

Kubernetes Ingress & Amazon Load Balancer (alb)
173

Security
• Network Security Policy
• Service Mesh
174
4

Kubernetes
Network Security Policy
• Kubernetes Network Policy – L3 / L4
• Kubernetes Security Policy for Microservices
• Cilium Network / Security Policy
• Berkeley Packet Filter (BPF)
• Express Data Path (XDP)
• Compare Weave | Calico | Romana | Cilium | Flannel
• Cilium Architecture
• Cilium Features
175

K8s Network Policies L3/L4
Kubernetes blocks the
Product UI to access
Database or Product
Review directly.
You can create
Network policies
across name spaces,
services etc., for both
incoming (Ingress) and
outgoing (Egress)
traffic.
Product UI Pod
Product UI Pod
Product UI Pod
Product Pod
Product Pod
Product Pod
Review Pod
Review Pod
Review Pod
MySQL
Pod
Mongo
Pod
Order UI Pod
Order UI Pod
Order UI Pod
Order Pod
Order Pod
Order Pod
Oracle
Pod
Blocks Access
Blocks Access
176

K8s Network Policies – L3 / L4
Allow All Inbound
Allow All Outbound
endPort for Range of Ports
177

Network Security Policy for Microservices
Product Review
Microservice
Product
Microservice
172.27.1.2
L3 / L4
L7 – API
GET /live
GET /ready
GET /reviews/{id}
POST /reviews
PUT /reviews/{id}
DELETE /reviews/{id}
GET /reviews/192351
Product review can be accessed ONLY by
Product. IP Tables enforces this rule.
Exposed
Exposed
Exposed
Exposed
Exposed
All other method calls are also
exposed to Product Microservice.
iptables –s 172.27.1.2
-p tcp –dport 80
-j accept
178

Network Security Policy for Microservices
Product Review
Microservice
Product
Microservice
L3 / L4
L7 – API
GET /live
GET /ready
GET /reviews/{id}
POST /reviews
PUT /reviews/{id}
DELETE /reviews/{id}
GET /reviews/192351
Rules are implemented by BPF (Berkeley
Packet Filter) at Linux Kernel level.
From Product Microservice
only GET /reviews/{id}
allowed.
BPF / XDP performance is much
superior to IPVS.
Except GET /reviews All other
calls are blocked for Product
Microservice
179

Cilium Network Policy
1. Cilium Network Policy works in sync with
Istio in the Kubernetes world.
2. In Docker world Cilium works as a network
driver and you can apply the policy using
ciliumctl.
In the previous example with Kubernetes
Network policy you will be allowing access to
Product Review from Product Microservice.
However, that results in all the API calls of
Product Review accessible by the Product
Microservice.
Now with the New Policy only GET /reviews/{id}
is allowed.
These Network policy gets executed at Linux
Kernel using BPF.
Product
Microservice can
access ONLY
GET /reviews from
Product Review
Microservice
User Microservice
can access
GET /reviews &
POST /reviews from
Product Review
Microservice
180

BPF / XDP (eXpress Data Path)
Network Driver Software Stack
Network Card
BPF
Regular BPF (Berkeley Packet Filter) mode
Network Card
BPF
XDP allows BPF program to run inside the network driver with access to DMA buffer.
Berkeley Packet Filters (BPF) provide a powerful tool for intrusion detection analysis.
Use BPF filtering to quickly reduce large packet captures to a reduced set of results
by filtering based on a specific type of traffic.
Source: https://www.ibm.com/support/knowledgecenter/en/SS42VS_7.3.2/com.ibm.qradar.doc/c_forensics_bpf.html
181

XDP (eXpress Data Path)
BPF Program can
drop millions packet
per second when
there is DDoS attack.
Network Card
BPF
Drop
Stack
Network Card
BPF
Drop
Stack
LB & Tx
BPF can perform
Load Balancing and
transmit out the
data to wire again.
Source: http://www.brendangregg.com/ebpf.html
182

Kubernetes Container Network Interface
Container Runtime
Container Network Interface
Weave Calico Romana Cilium Flannel
Layer 3
BGP
BGP Route Reflector
Network Policies
IP Tables
Stores data in Etcd
Project Calico
Layer 3
VXLAN (No Encryption)
IPSec
Overlay Network
Host-GW (L2)
Stores data in Etcd
https://coreos.com/
Layer 3
IPSec
Network Policies
Multi Cloud NW
Stores data in Etcd
https://www.weave.works/
Layer 3
L3 + BGP & L2 +VXLAN
IPSec
Network Policies
IP Tables
Stores data in Etcd
https://romana.io/
Layer 3 / 7
BPF / XDP
L7 Filtering using BPF
Network Policies
L2 VXLAN
API Aware (HTTP, gRPC,
Kafka, Cassandra… )
Multi Cluster Support
https://cilium.io/
BPF (Berkeley Packet Filter) – Runs inside the Linux Kernel
On-Premise Ingress Load Balancer
Mostly Mostly Yes Yes Yes
183

Cilium Architecture
Plugins
Cilium
Agent
BPF
BPF
BPF
CLI
Monitor
Policy
1. Can compile and deploy BPF code
(based on the labels of that
Container) in the kernel when the
containers is started.
2. When the 2nd container is deployed
Cilium generates the 2nd BPF and
deploy that rule in the kernel.
3. To get the network Connectivity
Cilium compiles the BPF and
attach it to the network device.
184

Summary
Networking – Packet Routing
1. Compare Docker and Kubernetes Networking
2. Pod to Pod Networking within the same Node
3. Pod to Pod Networking across the Node
4. Pod to Service Networking
5. Ingress - Internet to Service Networking
6. Egress – Pod to Internet Networking
Kubernetes Volume
• Installed nfs server in the cluster
• Created Persistent Volume
• Create Persistent Volume Claim
• Linked Persistent Volume Claim to Pod
Network Policies
1. Kubernetes Network Policy – L3 / L4
2. Created Network Policies within the same
Namespace and across Namespace
Networking - Components
1. Kubernetes IP Network
2. Kubernetes DNS
3. Kubernetes Proxy
4. Created Service (with Cluster IP)
5. Created Ingress
185

Service Mesh: Istio
Service Discovery
Traffic Routing
Security
Gateway
Virtual Service
Destination Rule
Service Entry
186

• Enforces access
control and
usage policies
across service
mesh and
• Collects
telemetry data
from Envoy and
other services.
• Also includes a
flexible plugin
model.
Mixer
Provides
• Traffic Management
• Routing
• Resiliency (Timeouts,
Circuit Breakers, etc.)
Pilot
Provides
• Strong Service to
Service and end
user Authentication
with built-in
Identity and
credential
management.
• Can enforce policies
based on Service
identity rather than
network controls.
Citadel
Provides
• Configuration
Injection
• Processing and
• Distribution
Component of Istio
Galley
Control Plane
Envoy is deployed
as a Sidecar in the
same K8S Pod.
• Dynamic Service
Discovery
• Load Balancing
• TLS Termination
• HTTP/2 and gRPC
Proxies
• Circuit Breakers
• Health Checks
• Staged Rollouts with
% based traffic split
• Fault Injection
• Rich Metrics
Envoy
Data Plane
Istio Components
187

Service Mesh – Sidecar Design Pattern
CB – Circuit Breaker
LB – Load Balancer
SD – Service Discovery
Microservice
Process
1
Process
2
Service Mesh Control Plane
Service
Discovery
Routing
Rules
Control Plane will have all the rules for Routing and
Service Discovery. Local Service Mesh will download the
rules from the Control pane will have a local copy.
Service Discovery Calls
Service
Mesh
Calls
Customer Microservice
Application Localhost calls
http://localhost/order/processOrder
Router
Network Stack
LB
CB SD
Service
Mesh
Sidecar
UI Layer
Web Services
Business Logic
Order Microservice
Application Localhost calls
http://localhost/payment/processPayment
Router
Network Stack
LB
CB SD
Service
Mesh
Sidecar
UI Layer
Web Services
Business Logic
Data Plane
188

Service Mesh – Traffic Control
API Gateway
End User
Business Logic
Service Mesh
Sidecar
Customer
Service Mesh
Control Plane
Admin
Traffic Rules
Traffic Control rules can be
applied for
• different Microservices
versions
• Re Routing the request
to debugging system to
analyze the problem in
real time.
• Smooth migration path
Business Logic
Service Mesh
Sidecar
Business Logic
Service Mesh
Sidecar
Business Logic
Service Mesh
Sidecar
Business Logic
Service Mesh
Sidecar
Business Logic
Service Mesh
Sidecar
Order v1.0
Business Logic
Service Mesh
Sidecar
Business Logic
Service Mesh
Sidecar
Order v2.0
Service
Cluster
189

Why Service Mesh?
• Multi Language / Technology
stack Microservices requires a
standard telemetry service.
• Adding SSL certificates across
all the services.
• Abstracting Horizontal
concerns
• Stakeholders: Identify whose
affected.
• Incentives: What Service
Mesh brings onto the table.
• Concerns: Their worries
• Mitigate Concerns
190

Envoy Proxy
• Sidecar
• Envoy Proxy Communications
• Envoy Proxy Cilium Integration
191

Envoy is deployed
as a Sidecar in the
same K8s Pod.
• Dynamic Service
Discovery
• Load Balancing
• TLS Termination
• HTTP/2 and gRPC
Proxies
• Circuit Breakers
• Health Checks
• Staged Rollouts with
% based traffic split
• Fault Injection
• Rich Metrics
Envoy
Data Plane
Istio Components – Envoy Proxy
• Why Envoy as a Sidecar?
• Microservice can focus on Business Logic and NOT on
networking concerns and other NPR (logging, Security).
• Features
• Out of process Architecture
• Low Latency, high performance
• L3/L4 Packet Filtering
• L7 Filters – HTTP
• Advanced Load Balancing
• Observability
• Proxy
• Hot Restart
Envoy deployed in
production at Lyft,
Apple, Salesforce,
Google, and others.
Source: https://blog.getambassador.io/envoy-vs-nginx-vs-haproxy-why-the-open-source-ambassador-api-gateway-chose-envoy-23826aed79ef
Apart from static
configurations Envoy
also allows
configuration via
gRPC/protobuf APIs.
192

Envoy Proxy - Communications
Product
Service
Kubernetes Pod
Review
Service
Kubernetes Pod
K8s Network
With Istio (Service Mesh) Envoy in place the Product Service (inside the Pod) will
talk to Envoy (Proxy) to connect to Product Review Service.
1. Product Service Talks to Envoy inside Product Pod
2. Envoy in Product Pod talks to Envoy in Review Pod
3. Envoy in Review Pod talks to Review Pod
193

Product
Service
Kubernetes Pod
Review
Service
Kubernetes Pod
SOCKET SOCKET SOCKET SOCKET SOCKET SOCKET
K8s Network
Operating System
194

Product
Service
Kubernetes Pod
Review
Service
Kubernetes Pod
K8s Network
Operating System
TCP/IP TCP/IP TCP/IP TCP/IP TCP/IP TCP/IP
195

Product
Service
Kubernetes Pod
Review
Service
Kubernetes Pod
K8s Network
Operating System
Ethernet Ethernet Ethernet Ethernet Ethernet Ethernet
196

Product
Service
Kubernetes Pod
Review
Service
Kubernetes Pod
K8s Network
Operating System
Ethernet Ethernet Ethernet Ethernet Ethernet Ethernet
Loopback eth0 Loopback
eth0
197

Product
Service
Kubernetes Pod
Review
Service
Kubernetes Pod
K8s Network
Operating System
Ethernet Ethernet Ethernet
Loopback eth0 Loopback
eth0
Ethernet Ethernet Ethernet
iptables iptables
TCP/IP TCP/IP TCP/IP
iptables iptables
TCP/IP TCP/IP TCP/IP
198

Envoy & Cilium Network Controller
Product
Service
Kubernetes Pod
Review
Service
Kubernetes Pod
K8s Network
Operating System
Ethernet
eth0 eth0
Ethernet
Cilium TCP/IP TCP/IP Cilium
199

Istio –
Traffic Management
• Gateway
• Virtual Service
• Destination Rule
• Service Entry
200

Istio Sidecar Automatic Injection
201

Kubernetes & Istio - Kinds
# Kubernetes # Istio Kinds Description
1 Ingress
1 Gateway Exposes Ports to outside world
2 Virtual Service Traffic Routing based on URL path
3 Destination Rule Traffic Routing based on Business Rules
2 Service 4 Service Entry App Service Definition
3 Service Account
5 Cluster RBA Config Enable RBAC on the Cluster
6 Mesh Policy Enable mTLS across the Mesh
7 Policy Enable mTLS for a name space
8 Service Role Define the Role of Microservice
9 Service Role Binding Service Account to Service Role Binding
4 Network Policy
10 Cilium Network Policy More granular Network Policies
202

Istio – Traffic Management
Virtual Service
Gateway
Destination Rule
Routing Rules Policies
• Match
• URI Patterns
• URI ReWrites
• Headers
• Routes
• Fault
• Fault
• Route
• Weightages
• Traffic Policies
• Load Balancer
Configures a load balancer for HTTP/TCP
traffic, most commonly operating at the
edge of the mesh to enable ingress traffic
for an application.
Defines the rules
that control how
requests for a
service are routed
within an Istio
service mesh.
Configures the set of policies
to be applied to a request
after Virtual Service routing
has occurred.
203

Istio Gateway
Gateway describes a load balancer
operating at the edge of the mesh
receiving incoming or outgoing
HTTP/TCP connections.
The Gateway specification above describes
the L4-L6 properties of a load balancer.
204

Istio Gateway
In this Gateway configuration sets up a proxy to act as
a load balancer exposing
• port 80 and
• 9080 (http),
• 443 (https),
• 9443(https)
for ingress.
Multiple Sub-domains are mapped to the single Load
Balancer IP Address.
The same rule is also applicable inside the mesh for requests to the
“reviews.prod.svc.cluster.local” service. This rule is applicable across ports
443, 9080. Note that http://in.shoppingportal.com
gets redirected to https:// in.shoppingportal..com
(i.e. 80 redirects to 443).
apiVersion: networking.istio.io/v1alpha3 kind: VirtualService metadata:
name: bookinfo-rule namespace: bookinfo-namespace spec: hosts: -
reviews.prod.svc.cluster.local
Both sub domains mapped
to a single IP Address
205

Istio Virtual Service
The following VirtualService splits traffic for
• https//in.shoppingportal.com/reviews,
• https:// us.shoppingportal.com/reviews,
• http:// in.shoppingportal.com:9080/reviews,
• http:// in.shoppingportal com:9080/reviews
• into two versions (prod and qa) of an internal
reviews service on port 9080.
In addition, requests containing the cookie “user:
dev-610” will be sent to special port 7777 in the qa
version
You can have multiple Virtual Service attached to
the same Gateway.
206

Istio Virtual Service
Defines the rules that
control how requests for
a service are routed
within an Istio service
mesh.
207

Istio Destination Rule
Configures the set of
policies to be applied to
a request after Virtual
Service routing has
occurred.
208

For HTTP-based services, it is possible to create a VirtualService backed
by multiple DNS addressable endpoints. In such a scenario, the
application can use the HTTP_PROXY environment variable to
transparently reroute API calls for the VirtualService to a chosen
backend.
For example, the following configuration
• creates a non-existent external service called foo.bar.com backed by
three domains:
• us.foo.bar.com:8080,
• uk.foo.bar.com:9080, and
• in.foo.bar.com:7080
Source: https://istio.io/docs/reference/config/networking/v1alpha3/service-entry/
MESH_EXTERNAL Signifies that the service is external to the mesh.
Typically used to indicate external services consumed
through APIs.
MESH_INTERNAL Signifies that the service is part of the mesh.
Istio ServiceEntry
Resolution determines how the proxy will
resolve the IP addresses of the network
endpoints associated with the service, so that
it can route to one of them. Values: DNS :
Static : None
A service entry describes the properties of a service
• DNS name,
• VIPs (Virtual IPs)
• ports, protocols
• endpoints
209

Shopping Portal – Docker / Kubernetes
/ui
/productms
/productreview
Load Balancer
Ingress
UI Pod
UI Pod
UI Pod
UI Service
Product Pod
Product Pod
Product Pod
Product
Service
Review Pod
Review Pod
Review Pod
Review
Service
Deployment / Replica / Pod
N1
N2
N2
Nodes
N4
N3
MySQL
Pod
N4
N3
N1
Kubernetes Objects
Firewall
Service Call
Kube DNS
EndPoints
EndPoints
EndPoints
Internal
Load Balancers
Source:
210

Shopping Portal - Istio
/ui
/productms
/productreview
Gateway
Virtual Service
UI Pod
UI Pod
UI Pod
UI
Service
Product Pod
Product Pod
Product Pod
Product
Service
Review Pod
Review Pod
Review Pod
Review
Service
MySQL
Pod
N1
N2
N2
N4
N1
N3
N4
N3
Nodes
Istio Sidecar
Envoy
Destination
Rule
Destination
Rule
Destination
Rule
Load Balancer
Kubernetes Objects
Istio Objects
Firewall
Pilot Mixer Citadel
Istio Control Plane
Service Call
Kube DNS
EndPoints
EndPoints
EndPoints
Internal
Load Balancers
Source:
211

Shopping Portal
/ui
/productms
/productreview
Gateway
Virtual Service
UI Pod
UI Pod
UI Pod
UI
Service
Product Pod
Product Pod
Product Pod
Product
Service
Review Pod
Review Pod
Review Pod
Review
Service
N1
N2
N2
MySQL
Pod
N4
N3
N1
N4
N3
Nodes
Destination
Rule
Destination
Rule
Destination
Rule
Load Balancer
Kubernetes Objects
Istio Objects
Firewall
P M C
Istio Control Plane
UI Pod N5
v1
v2
Stable / v1
Canary
v2
User X = Canary
Others = Stable
A / B Testing using
Canary Deployment
Service Call
Kube DNS
EndPoints
EndPoints
EndPoints
Internal
Load Balancers
Source:
212

Shopping Portal
/ui
/productms
/productreview
Gateway
Virtual Service
UI Pod
UI Pod
UI Pod
UI
Service
Product Pod
Product Pod
Product Pod
Product
Service
Review Pod
Review Pod
Review Pod
Review
Service
N1
N2
N2
MySQL
Pod
N4
N3
N1
N4
N3
Nodes
Destination
Rule
Destination
Rule
Destination
Rule
Load Balancer
Kubernetes Objects
Istio Objects
Firewall
P M C
Istio Control Plane
UI Pod N5
v1
v2
Stable / v1
Canary
v2
10% = Canary
90% = Stable
Traffic Shifting
Canary Deployment
Service Call
Kube DNS
EndPoints
EndPoints
EndPoints
Internal
Load Balancers
Source:
213

Shopping Portal
/ui
/productms
/productreview
Gateway
Virtual Service
UI Pod
UI Pod
UI Pod
UI
Service
Product Pod
Product Pod
Product Pod
Product
Service
Review Pod
Review Pod
Review Pod
Review
Service
N1
N2
N2
MySQL
Pod
N4
N3
N1
N4
N3
Nodes
Destination
Rule
Destination
Rule
Destination
Rule
Load Balancer
Kubernetes Objects
Istio Objects
Firewall
P M C
Istio Control Plane
UI Pod N5
v1
v2
Stable / v1
Canary
v2
100% = v2
Blue Green Deployment
Service Call
Kube DNS
EndPoints
EndPoints
EndPoints
Internal
Load Balancers
Source:
214

Shopping Portal
/ui
/productms
/productreview
Gateway
Virtual Service
UI Pod
UI Pod
UI Pod
UI
Service
Product Pod
Product Pod
Product Pod
Product
Service
Review Pod
Review Pod
Review Pod
Review
Service
N1
N2
N2
MySQL
Pod
N4
N3
N1
N4
N3
Nodes
Destination
Rule
Destination
Rule
Destination
Rule
Load Balancer
Kubernetes Objects
Istio Objects
Firewall
P M C
Istio Control Plane
UI Pod N5
v1
v2
Stable / v1
Canary
v2
100% = Stable
Mirror = Canary
Mirror Data
Service Call
Kube DNS
EndPoints
EndPoints
EndPoints
Internal
Load Balancers
Source:
215

Circuit Breaker Pattern
/ui
/productms
If Product Review is not
available Product service
will return the product
details with a message
review not available.
Ingress
Kubernetes Objects
Firewall
UI Pod
UI Pod
UI Pod
UI Service
N1
N2
N2
EndPoints
Product Pod
Product Pod
Product Pod
Product
Service
N4
N3
MySQL
Pod
EndPoints
Internal
Load Balancers
Users
Review Pod
Review Pod
Review Pod
Review
Service
N4
N3
N1
Service Call
Kube DNS
EndPoints
216

Shopping Portal:
/ui
/productms
/productreview
Gateway
Virtual Service
UI Pod
UI Pod
UI Pod
UI
Service
Review Pod
Review Pod
Review Pod
Review
Service
N1
N2
N2
MySQL
Pod
N4
N3
N1
N4
N3
Nodes
Destination
Rule
Destination
Rule
Destination
Rule
Load Balancer
Kubernetes Objects
Istio Objects
Firewall
P M C
Istio Control Plane
v1
Fault Injection
Delay = 2 Sec
Abort = 10%
Circuit Breaker
Product Pod
Product Pod
Product Pod
Product
Service
Service Call
Kube DNS
EndPoints
EndPoints
EndPoints
Internal
Load Balancers
Source:
217

Shopping Portal
/ui
/productms
/productreview
Gateway
Virtual Service
UI Pod
UI Pod
UI Pod
UI
Service
Review Pod
Review Pod
Review Pod
Review
Service
N1
N2
N2
MySQL
Pod
N4
N3
N1
N4
N3
Nodes
Destination
Rule
Destination
Rule
Destination
Rule
Load Balancer
Kubernetes Objects
Istio Objects
Firewall
P M C
Istio Control Plane
v1
Fault Injection
Delay = 2 Sec
Abort = 10%
Fault Injection
Product Pod
Product Pod
Product Pod
Product
Service
Service Call
Kube DNS
EndPoints
EndPoints
EndPoints
Internal
Load Balancers
Source:
218

Shopping Portal
/ui
/productms
/productreview
Gateway
Virtual Service
UI Pod
UI Pod
UI Pod
UI
Service
Review Pod
Review Pod
Review Pod
Review
Service
N1
N2
N2
MySQL
Pod
N4
N3
N1
N4
N3
Nodes
Destination
Rule
Destination
Rule
Destination
Rule
Load Balancer
Kubernetes Objects
Istio Objects
Firewall
P M C
Istio Control Plane
v1
Fault Injection
Delay = 2 Sec
Abort = 10%
Fault Injection
Product Pod
Product Pod
Product Pod
Product
Service
Service Call
Kube DNS
EndPoints
EndPoints
EndPoints
Internal
Load Balancers
Source:
219

Istio – Security
• Network Security
• Role Based Access Control
• Mesh Policy
• Policy
• Cluster RBAC Config
• Service Role
• Service Role Binding
220

Istio Security
Source: https://istio.io/docs/concepts/security/
It provide strong identity, powerful policy,
transparent TLS encryption, and authentication,
authorization and audit (AAA) tools to protect
your services and data. The goals of Istio security
are
• Security by default: no changes
needed for application code
and infrastructure
• Defense in depth: integrate
with existing security systems to
provide multiple layers of
defense
• Zero-trust network: build
security solutions on untrusted
networks
221

Istio Security Architecture
• Citadel for key and
certificate management
• Sidecar and perimeter
proxies to implement
secure communication
between clients and
servers
• Pilot to
distribute authentication
policies and secure
naming information to the
proxies
• Mixer to manage
authorization and auditing
222

Istio Service Identities
• Kubernetes: Kubernetes service account
• GKE/GCE: may use GCP service account
• GCP: GCP service account
• AWS: AWS IAM user/role account
• On-premises (non-Kubernetes): user account, custom service
account, service name, Istio service account, or GCP service account.
The custom service account refers to the existing service account just
like the identities that the customer’s Identity Directory manages.
Istio and SPIFFE share the same identity
document: SVID (SPIFFE Verifiable
Identity Document).
For example, in Kubernetes, the X.509
certificate has the URI field in the format
of spiffe://<domain>/ns/<namespace
>/sa/<serviceaccount>. This enables
Istio services to establish and accept
connections with other SPIFFE-compliant
systems
SPIFFE Secure Production Identity Framework for Everyone. Inspired by the production infrastructure of Google and others, SPIFFE is a set of
open-source standards for securely identifying software systems in dynamic and heterogeneous environments.
223

Kubernetes Scenario
1. Citadel watches the Kubernetes API Server, creates a SPIFFE
certificate and key pair for each of the existing and new service
accounts. Citadel stores the certificate and key pairs as Kubernetes
secrets.
2. When you create a pod, Kubernetes mounts the certificate and key
pair to the pod according to its service account via Kubernetes
secret volume.
3. Citadel watches the lifetime of each certificate, and automatically
rotates the certificates by rewriting the Kubernetes secrets.
4. Pilot generates the secure naming information, which defines what
service account or accounts can run a certain service. Pilot then
passes the secure naming information to the sidecar Envoy.
224

Node Agent in Kubernetes
1. Citadel creates a gRPC service to take CSR
requests.
2. Envoy sends a certificate and key request via
Envoy secret discovery service (SDS) API.
3. Upon receiving the SDS request, the Node
agent creates the private key and CSR before
sending the CSR with its credentials to Citadel
for signing.
4. Citadel validates the credentials carried in the
CSR and signs the CSR to generate the
certificate.
5. The Node agent sends the certificate received
from Citadel and the private key to Envoy via
the Envoy SDS API.
6. The above CSR process repeats periodically for
certificate and key rotation.
Istio provides the option of using node agent
in Kubernetes for certificate and key
provisioning.
225

Mesh Policy Policy
Istio Kinds for Security and RBAC
Destination
Rule
Service
Account
Service Role
Service Role
Binding
Cluster RBAC
Config
226

Cluster Security: Mesh Policy / Policy
• Mesh-wide policy: A policy defined in the mesh-scope
storage with no target selector section. There can be at
most one mesh-wide policy in the mesh.
• Namespace-wide policy: A policy defined in the namespace-
scope storage with name default and no target selector
section. There can be at most one namespace-wide
policy per namespace.
• Service-specific policy: a policy defined in the namespace-
scope storage, with non-empty target selector section. A
namespace can have zero, one, or many service-specific
policies
Source: https://istio.io/docs/concepts/security/#authentication-architecture
To enforce uniqueness for mesh-wide and
namespace-wide policies, Istio accepts only
one authentication policy per mesh and one
authentication policy per namespace. Istio
also requires mesh-wide and namespace-
wide policies to have the specific
name default.
227

Istio Destination Rule
Configure Istio
services to send
mutual TLS traffic by
setting Destination
Rule.
228

Istio RBAC
Enable / Disable
RBAC for specific
namespace(s) or
all.
229

RBAC – Service Account / Role / Binding
Service Account
Service Role
RBAC Rules
(App) Deployment
Service Account
Refer
Service Role Binding
Service
Account
Refer
Service Role
User Account
User
Account
230

Service Account
231

Best Practices
Docker Best Practices
Kubernetes Best Practices
232

Build Small Container Images
1. Simple Java Web Apps with Ubuntu & Tomcat can have a size of
700 MB
2. Use Alpine Image as your base Linux OS
3. Alpine images are 10x smaller than base Ubuntu images
4. Smaller Image size reduce the Container vulnerabilities.
5. Ensure that only Runtime Environments are there in your
container. For Example your Alpine + Java + Tomcat image
should contain only the JRE and NOT JDK.
6. Log the App output to Container Std out and Std error.
1
233

Docker: To Root or Not to Root!
1. Create Multiple layers of Images
2. Create a User account
3. Add Runtime software’s based on the User
Account.
4. Run the App under the user account
5. This gives added security to the container.
6. Add Security module SELinux or AppArmour
to increase the security.
Alpine
JRE 8
Tomcat 8
My App 1
2
234

Docker: Container Security
1. Secure your HOST OS! Containers runs on Host Kernel.
2. No Runtime software downloads inside the container.
Declare the software requirements at the build time itself.
3. Download Docker base images from Authentic site.
4. Limit the resource utilization using Container orchestrators
like Kubernetes.
5. Don’t run anything on Super privileged mode.
3
235

Kubernetes: Naked Pods
1. Never use a Naked Pod, that is Pod without any
ReplicaSet or Deployments. Naked pods will
never get re-scheduled if the Pod goes down.
2. Never access a Pod directly from another Pod.
Always use a Service to access a Pod.
3. User labels to select the pods { app: myapp, tier:
frontend, phase: test, deployment: v3 }.
4. Never use :latest tag in the image in the
production scenario.
4
236

Kubernetes: Namespace
default
Kube system
Kube public
Kubernetes Cluster
1. Group your Services / Pods / Traffic Rules based on
Specific Namespace.
2. This helps you apply specific Network Policies for
that Namespace with increase in Security and
Performance.
3. Handle specific Resource Allocations for a
Namespace.
4. If you have more than a dozen Microservices then
it’s time to bring in Namespaces.
Service-Name.Namespace.svc.cluster.local
$ kubectl config set-context $(kubectl config current-context) --namespace=your-ns
The above command will let you switch the namespace to your namespace (your-ns).
5
237

Kubernetes: Pod Health Check
1. Pod Health check is critical to increase the overall
resiliency of the network.
2. Readiness
3. Liveness
4. Ensure that all your Pods have Readiness and
Liveness Probes.
5. Choose the Protocol wisely (HTTP, Command &
TCP)
6
238

Kubernetes: Resource Utilization
1. For the Best Quality define the requests and
limits for your Pods.
2. You can set specific resource requests for a Dev
Namespace to ensure that developers don’t
create pods with a very large resource or a very
small resource.
3. Limit Range can be set to ensure that containers
were create with too low resource or too large
resource.
7
239

Kubernetes: Pod Termination Lifecycle
1. Make sure that the Application to Handle SIGTERM
message.
2. You can use preStop Hook
3. Set the terminationGracePeriodSeconds: 60
4. Ensure that you clean up the connections or any other
artefacts and ready for clean shutdown of the App
(Microservice).
5. If the Container is still running after the grace period,
Kubernetes sends a SIGKILL event to shutdown the Pod.
8
240

Kubernetes: External Services
1. There are systems that can be outside the Kubernetes
cluster like
1. Databases or
2. external services in the cloud.
2. You can create an Endpoint with Specific IP Address and
Port with the same name as Service.
3. You can create a Service with an External Name (URL)
which does a CNAME redirection at the Kernel level.
9
241

Kubernetes: Upgrade Cluster
1. Make sure that the Master behind a Load Balancer.
2. Upgrade Master
1. Scale up the Node with an extra Node
2. Drain the Node and
3. Upgrade Node
3. Cluster will be running even if the master is not working.
Only Kubectl and any master specific functions will be
down until the master is up.
10
242

@arafkarsh arafkarsh 243
Design Patterns are
solutions to general
problems that
software developers
faced during software
development.
Design Patterns

DREAM | AUTOMATE | EMPOWER
Araf Karsh Hamid :
India: +91.999.545.8627
http://www.slideshare.net/arafkarsh
https://www.linkedin.com/in/arafkarsh/
https://www.youtube.com/user/arafkarsh/playlists
http://www.arafkarsh.com/
@arafkarsh
arafkarsh

Source Code: https://github.com/MetaArivu Web Site: https://metarivu.com/ https://pyxida.cloud/

http://www.slideshare.net/arafkarsh

References
1. July 15, 2015 – Agile is Dead : GoTo 2015 By Dave Thomas
2. Apr 7, 2016 - Agile Project Management with Kanban | Eric Brechner | Talks at Google
3. Sep 27, 2017 - Scrum vs Kanban - Two Agile Teams Go Head-to-Head
4. Feb 17, 2019 - Lean vs Agile vs Design Thinking
5. Dec 17, 2020 - Scrum vs Kanban | Differences & Similarities Between Scrum & Kanban
6. Feb 24, 2021 - Agile Methodology Tutorial for Beginners | Jira Tutorial | Agile Methodology Explained.
Agile Methodologies
247

References
1. Vmware: What is Cloud Architecture?
2. Redhat: What is Cloud Architecture?
3. Cloud Computing Architecture
4. Cloud Adoption Essentials:
5. Google: Hybrid and Multi Cloud
6. IBM: Hybrid Cloud Architecture Intro
7. IBM: Hybrid Cloud Architecture: Part 1
8. IBM: Hybrid Cloud Architecture: Part 2
9. Cloud Computing Basics: IaaS, PaaS, SaaS
248
1. IBM: IaaS Explained
2. IBM: PaaS Explained
3. IBM: SaaS Explained
4. IBM: FaaS Explained
5. IBM: What is Hypervisor?
Cloud Architecture

References
Microservices
1. Microservices Definition by Martin Fowler
2. When to use Microservices By Martin Fowler
3. GoTo: Sep 3, 2020: When to use Microservices By Martin Fowler
4. GoTo: Feb 26, 2020: Monolith Decomposition Pattern
5. Thought Works: Microservices in a Nutshell
6. Microservices Prerequisites
7. What do you mean by Event Driven?
8. Understanding Event Driven Design Patterns for Microservices
249

References – Microservices – Videos
250
1. Martin Fowler – Micro Services : https://www.youtube.com/watch?v=2yko4TbC8cI&feature=youtu.be&t=15m53s
2. GOTO 2016 – Microservices at NetFlix Scale: Principles, Tradeoffs & Lessons Learned. By R Meshenberg
3. Mastering Chaos – A NetFlix Guide to Microservices. By Josh Evans
4. GOTO 2015 – Challenges Implementing Micro Services By Fred George
5. GOTO 2016 – From Monolith to Microservices at Zalando. By Rodrigue Scaefer
6. GOTO 2015 – Microservices @ Spotify. By Kevin Goldsmith
7. Modelling Microservices @ Spotify : https://www.youtube.com/watch?v=7XDA044tl8k
8. GOTO 2015 – DDD & Microservices: At last, Some Boundaries By Eric Evans
9. GOTO 2016 – What I wish I had known before Scaling Uber to 1000 Services. By Matt Ranney
10. DDD Europe – Tackling Complexity in the Heart of Software By Eric Evans, April 11, 2016
11. AWS re:Invent 2016 – From Monolithic to Microservices: Evolving Architecture Patterns. By Emerson L, Gilt D. Chiles
12. AWS 2017 – An overview of designing Microservices based Applications on AWS. By Peter Dalbhanjan
13. GOTO Jun, 2017 – Effective Microservices in a Data Centric World. By Randy Shoup.
14. GOTO July, 2017 – The Seven (more) Deadly Sins of Microservices. By Daniel Bryant
15. Sept, 2017 – Airbnb, From Monolith to Microservices: How to scale your Architecture. By Melanie Cubula
16. GOTO Sept, 2017 – Rethinking Microservices with Stateful Streams. By Ben Stopford.
17. GOTO 2017 – Microservices without Servers. By Glynn Bird.

References
251
1. Oct 27, 2012 What I have learned about DDD Since the book. By Eric Evans
2. Mar 19, 2013 Domain Driven Design By Eric Evans
3. Jun 02, 2015 Applied DDD in Java EE 7 and Open Source World
4. Aug 23, 2016 Domain Driven Design the Good Parts By Jimmy Bogard
5. Sep 22, 2016 GOTO 2015 – DDD & REST Domain Driven API’s for the Web. By Oliver Gierke
6. Jan 24, 2017 Spring Developer – Developing Micro Services with Aggregates. By Chris Richardson
7. May 17. 2017 DEVOXX – The Art of Discovering Bounded Contexts. By Nick Tune
8. Dec 21, 2019 What is DDD - Eric Evans - DDD Europe 2019. By Eric Evans
9. Oct 2, 2020 - Bounded Contexts - Eric Evans - DDD Europe 2020. By. Eric Evans
10. Oct 2, 2020 - DDD By Example - Paul Rayner - DDD Europe 2020. By Paul Rayner

References
1. IBM: Event Driven Architecture – Mar 21, 2021
2. Martin Fowler: Event Driven Architecture – GOTO 2017
3. Greg Young: A Decade of DDD, Event Sourcing & CQRS – April 11, 2016
4. Nov 13, 2014 GOTO 2014 – Event Sourcing. By Greg Young
5. Mar 22, 2016 Building Micro Services with Event Sourcing and CQRS
6. Apr 15, 2016 YOW! Nights – Event Sourcing. By Martin Fowler
7. May 08, 2017 When Micro Services Meet Event Sourcing. By Vinicius Gomes
252

References
253
Kafka
1. Understanding Kafka
2. Understanding RabbitMQ
3. IBM: Apache Kafka – Sept 18, 2020
4. Confluent: Apache Kafka Fundamentals – April 25, 2020
5. Confluent: How Kafka Works – Aug 25, 2020
6. Confluent: How to integrate Kafka into your environment – Aug 25, 2020
7. Kafka Streams – Sept 4, 2021
8. Kafka: Processing Streaming Data with KSQL – Jul 16, 2018
9. Kafka: Processing Streaming Data with KSQL – Nov 28, 2019

References
Databases: Big Data / Cloud Databases
1. Google: How to Choose the right database?
2. AWS: Choosing the right Database
3. IBM: NoSQL Vs. SQL
4. A Guide to NoSQL Databases
5. How does NoSQL Databases Work?
6. What is Better? SQL or NoSQL?
7. What is DBaaS?
8. NoSQL Concepts
9. Key Value Databases
10. Document Databases
11. Jun 29, 2012 – Google I/O 2012 - SQL vs NoSQL: Battle of the Backends
12. Feb 19, 2013 - Introduction to NoSQL • Martin Fowler • GOTO 2012
13. Jul 25, 2018 - SQL vs NoSQL or MySQL vs MongoDB
14. Oct 30, 2020 - Column vs Row Oriented Databases Explained
15. Dec 9, 2020 - How do NoSQL databases work? Simply Explained!
1. Graph Databases
2. Column Databases
3. Row Vs. Column Oriented Databases
4. Database Indexing Explained
5. MongoDB Indexing
6. AWS: DynamoDB Global Indexing
7. AWS: DynamoDB Local Indexing
8. Google Cloud Spanner
9. AWS: DynamoDB Design Patterns
10. Cloud Provider Database Comparisons
11. CockroachDB: When to use a Cloud DB?
254

References
Docker / Kubernetes / Istio
1. IBM: Virtual Machines and Containers
2. IBM: What is a Hypervisor?
3. IBM: Docker Vs. Kubernetes
4. IBM: Containerization Explained
5. IBM: Kubernetes Explained
6. IBM: Kubernetes Ingress in 5 Minutes
7. Microsoft: How Service Mesh works in Kubernetes
8. IBM: Istio Service Mesh Explained
9. IBM: Kubernetes and OpenShift
10. IBM: Kubernetes Operators
11. 10 Consideration for Kubernetes Deployments
Istio – Metrics
1. Istio – Metrics
2. Monitoring Istio Mesh with Grafana
3. Visualize your Istio Service Mesh
4. Security and Monitoring with Istio
5. Observing Services using Prometheus, Grafana, Kiali
6. Istio Cookbook: Kiali Recipe
7. Kubernetes: Open Telemetry
8. Open Telemetry
9. How Prometheus works
10. IBM: Observability vs. Monitoring
255

References
256
1. Feb 6, 2020 – An introduction to TDD
2. Aug 14, 2019 – Component Software Testing
3. May 30, 2020 – What is Component Testing?
4. Apr 23, 2013 – Component Test By Martin Fowler
5. Jan 12, 2011 – Contract Testing By Martin Fowler
6. Jan 16, 2018 – Integration Testing By Martin Fowler
7. Testing Strategies in Microservices Architecture
8. Practical Test Pyramid By Ham Vocke
Testing – TDD / BDD

1. Simoorg : LinkedIn’s own failure inducer framework. It was designed to be easy to extend and
most of the important components are plug‐ gable.
2. Pumba : A chaos testing and network emulation tool for Docker.
3. Chaos Lemur : Self-hostable application to randomly destroy virtual machines in a BOSH-
managed environment, as an aid to resilience testing of high-availability systems.
4. Chaos Lambda : Randomly terminate AWS ASG instances during business hours.
5. Blockade : Docker-based utility for testing network failures and partitions in distributed
applications.
6. Chaos-http-proxy : Introduces failures into HTTP requests via a proxy server.
7. Monkey-ops : Monkey-Ops is a simple service implemented in Go, which is deployed into an
OpenShift V3.X and generates some chaos within it. Monkey-Ops seeks some OpenShift
components like Pods or Deployment Configs and randomly terminates them.
8. Chaos Dingo : Chaos Dingo currently supports performing operations on Azure VMs and VMSS
deployed to an Azure Resource Manager-based resource group.
9. Tugbot : Testing in Production (TiP) framework for Docker.
Testing tools

References
CI / CD
1. What is Continuous Integration?
2. What is Continuous Delivery?
3. CI / CD Pipeline
4. What is CI / CD Pipeline?
5. CI / CD Explained
6. CI / CD Pipeline using Java Example Part 1
7. CI / CD Pipeline using Ansible Part 2
8. Declarative Pipeline vs Scripted Pipeline
9. Complete Jenkins Pipeline Tutorial
10. Common Pipeline Mistakes
11. CI / CD for a Docker Application
258

References
259
DevOps
1. IBM: What is DevOps?
2. IBM: Cloud Native DevOps Explained
3. IBM: Application Transformation
4. IBM: Virtualization Explained
5. What is DevOps? Easy Way
6. DevOps?! How to become a DevOps Engineer???
7. Amazon: https://www.youtube.com/watch?v=mBU3AJ3j1rg
8. NetFlix: https://www.youtube.com/watch?v=UTKIT6STSVM
9. DevOps and SRE: https://www.youtube.com/watch?v=uTEL8Ff1Zvk
10. SLI, SLO, SLA : https://www.youtube.com/watch?v=tEylFyxbDLE
11. DevOps and SRE : Risks and Budgets : https://www.youtube.com/watch?v=y2ILKr8kCJU
12. SRE @ Google: https://www.youtube.com/watch?v=d2wn_E1jxn4

References
260
1. Lewis, James, and Martin Fowler. “Microservices: A Definition of This New Architectural Term”, March 25, 2014.
2. Miller, Matt. “Innovate or Die: The Rise of Microservices”. e Wall Street Journal, October 5, 2015.
3. Newman, Sam. Building Microservices. O’Reilly Media, 2015.
4. Alagarasan, Vijay. “Seven Microservices Anti-patterns”, August 24, 2015.
5. Cockcroft, Adrian. “State of the Art in Microservices”, December 4, 2014.
6. Fowler, Martin. “Microservice Prerequisites”, August 28, 2014.
7. Fowler, Martin. “Microservice Tradeoffs”, July 1, 2015.
8. Humble, Jez. “Four Principles of Low-Risk Software Release”, February 16, 2012.
9. Zuul Edge Server, Ketan Gote, May 22, 2017
10. Ribbon, Hysterix using Spring Feign, Ketan Gote, May 22, 2017
11. Eureka Server with Spring Cloud, Ketan Gote, May 22, 2017
12. Apache Kafka, A Distributed Streaming Platform, Ketan Gote, May 20, 2017
13. Functional Reactive Programming, Araf Karsh Hamid, August 7, 2016
14. Enterprise Software Architectures, Araf Karsh Hamid, July 30, 2016
15. Docker and Linux Containers, Araf Karsh Hamid, April 28, 2015

References
261
16. MSDN – Microsoft https://msdn.microsoft.com/en-us/library/dn568103.aspx
17. Martin Fowler : CQRS – http://martinfowler.com/bliki/CQRS.html
18. Udi Dahan : CQRS – http://www.udidahan.com/2009/12/09/clarified-cqrs/
19. Greg Young : CQRS - https://www.youtube.com/watch?v=JHGkaShoyNs
20. Bertrand Meyer – CQS - http://en.wikipedia.org/wiki/Bertrand_Meyer
21. CQS : http://en.wikipedia.org/wiki/Command–query_separation
22. CAP Theorem : http://en.wikipedia.org/wiki/CAP_theorem
23. CAP Theorem : http://www.julianbrowne.com/article/viewer/brewers-cap-theorem
24. CAP 12 years how the rules have changed
25. EBay Scalability Best Practices : http://www.infoq.com/articles/ebay-scalability-best-practices
26. Pat Helland (Amazon) : Life beyond distributed transactions
27. Stanford University: Rx https://www.youtube.com/watch?v=y9xudo3C1Cw
28. Princeton University: SAGAS (1987) Hector Garcia Molina / Kenneth Salem
29. Rx Observable : https://dzone.com/articles/using-rx-java-observable

Containers Docker Kind Kubernetes Istio

More Related Content

What's hot

Similar to Containers Docker Kind Kubernetes Istio

More from Araf Karsh Hamid

Recently uploaded

Containers Docker Kind Kubernetes Istio

Editor's Notes