1.
Introduction
AKS
Overview
Introduction
Top
scenarios
Open source
culture
Resources

2.
Containers and Kubernetes momentum
Nearly 50% of organizations1
running 1000 or more hosts
have adopted containers.
Larger companies
are leading the
adoption.1
50%
Half of
container
environment is
orchestrated.1
77%
77% of companies2 who use
container orchestrators choose
Kubernetes.
75%
The average size
of a container
deployment
has grown 75%
in one year. 1
“By 2020, more than 50% of enterprises
will run mission-critical, containerized
cloud-native applications in production.”
1 Datadog report: 8 Surprising Facts About Real Docker Adoption
2 CNCF survey: cloud-native-technologies-scaling-production-applications

3.
What is a container?
Virtualize the hardware
VMs as units of scaling
Virtual machines
App
Containers
Virtualize the operating system
Applications as units of scaling
Container
App

4.
Kubernetes: the industry leading orchestrator
Portable
Public, private, hybrid,
multi-cloud
Extensible
Modular, pluggable,
hookable, composable
Self-healing
Auto-placement, auto-restart,
auto-replication, auto-scaling

5.
1. Kubernetes users communicate
with API server and apply desired
state
2. Master nodes actively enforce
desired state on worker nodes
3. Worker nodes support
communication between
containers
Kubernetes
Kubernetes
control
API server
replication, namespace,
serviceaccounts, etc.
-controller-
manager -scheduler
etcd
Master node
Worker node
kubelet kube-proxy
Docker
Prod Prod
Containers Containers
Worker node
kubelet kube-proxy
Docker
Prod Prod
Containers Containers
Internet
4. Worker nodes support
communication from the
Internet

6.
API server
Controller
ManagerScheduler
etcd
Store
Cloud
Controller
Self-managed master node(s)
How managed Kubernetes on Azure works
• Automated upgrades, patches
• High reliability, availability
• Easy, secure cluster scaling
• Self-healing
• API server monitoring
• At no charge
Customer VMs
App/
workload
definitionUser
Docker
Pods
Docker
Pods
Docker
Pods
Docker
Pods
Docker
Pods
Schedule pods over
private tunnel
Kubernetes
API endpoint
Azure managed control plane

7.
From infrastructure to innovation
Responsibilities DIY with Kubernetes Managed Kubernetes on Azure
Containerization
Application iteration,
debugging
CI/CD
Cluster hosting
Cluster upgrade
Patching
Scaling
Monitoring and logging
Customer
Microsoft
Managed Kubernetes
empowers you to do more
Focus on your containers
and code, not the plumbing
of them

8.
Azure Kubernetes Service (AKS) Overview
AKS
Overview
Introduction
Top
scenarios
Open source
culture
Resources

9.
AKS: Simplify the deployment, management,
and operations of Kubernetes
Deploy and manage
Kubernetes with ease
Scale and run applications
with confidence
Secure your Kubernetes
environment
Accelerate containerized
application development
Work how you want with
open-source tools & APIs
Set up CI/CD in a
few clicks

10.
Azure Kubernetes momentum
10x
Kubernetes on Azure
usage grew 10x
5x
Kubernetes on Azure
customers grew 5x
Last 12 months

11.
Deploy and manage Kubernetes with ease
Task The old way With Azure
Create a cluster Provision network and VMs
Install dozens of system components including etcd
Create and install certificates
Register agent nodes with control plane
az aks create
Upgrade a cluster Upgrade your master nodes
Cordon/drain and upgrade worker nodes individually
az aks upgrade
Scale a cluster Provision new VMs
Install system components
Register nodes with API server
az aks scale
Azure makes Kubernetes easy

12.
Database tier
AKS production cluster
Source
code control
Helm
chart
Inner loop
Test
Debug
Azure
DevSpaces
AKS dev
cluster
Azure
Container
Registry
Azure Pipelines/
DevOps Project
Auto-build
Business
logic
Front end
Azure
Monitor
CI/CD

13.
Secure your Kubernetes environment
Compliant Kubernetes
service with
certifications covering
SOC, HIPAA, and PCI
Control access through
AAD and RBAC
Safeguard keys and
secrets with Key Vault
Secure network
communications with
VNET and CNI

14.
Scale and run with confidence
Built-in
auto scaling
Global
data center
Geo-replicated
container registry
Elastically burst
using ACI
Browser
Traffic
manager
Geo-replicated
container registry
AKS clusters
Azure Container Instances
Pod Pod
Pod Pod
Pod Pod

15.
Top scenarios
AKS
Overview
Introduction
Top
scenarios
Open source
culture
Resources

16.
Performance
Low latency
processing
Machine
learning
Portability
Build once, run
anywhere
IoT
Agility
Faster application
development
Microservices
Top scenarios for Kubernetes on Azure
Cost saving
without refactoring
your app
Lift and shift
to containers

17.
Lift and shift to
containers
Microservices Machine learning IoT
App modernization without code changes
• Speed application deployments
by using container technology
• Defend against infrastructure
failures with container
orchestration
• Increase agility with continuous
integration and continuous
delivery
Azure
Container
Registry
Existing
application
Kubernetes cluster
Cloud
Database
Modernized
application
Modernized
application
Modernized
application
CI/CD

18.
Lift and shift to
containers
Microservices Machine learning IoT
Microservices: for faster app development
• Independent deployments
• Improved scale and resource
utilization per service
• Smaller, focused teams
Monolithic
APP APP APP
Microservices
Large, all-inclusive app Small, independent services

19.
Lift and shift to
containers
Microservices Machine learning IoT
Microservices: for faster app development
1. Use Azure Dev Spaces to iteratively
develop, test, and debug microservices
targeted for AKS clusters.
2. Easily access to SLA-backed Azure
Services such as Azure Database for
MySQL using Open Service Broker for
Azure (OSBA)
3. Azure Monitor provides a single pane
of glass for monitoring over app
telemetry, cluster-to-container level
health analytics.
Monolithic
APP APP APP
Microservices
Large, all-inclusive app Small, independent services

20.
Maersk uses AKS for a customer service process to elevate
NSAT, an industry-wide challenge
Needs: Get near-real-time data to provide better customer service
Collect data for future Machine Learning driven features
Challenges: Compute & memory intensive features
Data integration difficulties
Limited organisational experience in Cloud & Kubernetes
Requirements: Spend less time on container software management
Automation and continuous delivery
Full visibility to application, container and infrastructure
Fine grained security and access control
Click icon to learn more

21.
Architectural approach
1. Azure Pipelines for automation
and CI/CD pipelines; adding
Terraform for further automation
2. Key Vault to secure secrets and
for persistent configuration store
3. Azure Monitor for containers
provides better logging,
troubleshooting, with no direct
container access
4. RBAC control for fine grained
Kubernetes resources access
control
Firewall
App Gateway
AKS w/
RBAC
Azure
Monitor
Azure
Pipeline
SQL
Database
Cosmos
DB
Performance
Document DB
Key
Vault
Event Hub
Batch processing
Event Simulation
Data
Factory
Data
Management
Gateway
On-premises
database
Express
Route
Service Bus
Internal Queuing
SQL
Database

22.
Results
Reduced environment
provisioning time from
1+ weeks to 2.5 hours
Deploy times reduced
to minutes with the
introduction of
terraform
Increased developer
autonomy with ARM
and terraform
<>
Less time spend on
managing secrets with
AKS and Key Vault
AKS and CaaS can
potentially save 33%
on run cost
100% automated
production
deployments

23.
Lift and shift to
containers
Microservices Machine learning IoT
Data science in a box
• Quick deployment and high
availability
• Low latency data processing
• Consistent environment across
test, control and production
https://github.com/Azure/kubeflow-labs
Compute
Training
data
Algorithm
GPU-enabled VMs
AKS trained
model
AI model in
production
Developer
<>
Data
Scientist
Serve the
model

24.
OpenAI uses cloud to drive flexibility and scalability for deep
learning experiments
Challenge: OpenAI needed infrastructure for deep learning that would
allow experiments to run either in the cloud or in its own data
center, and to easily scale.
Solution: OpenAI migrated its Kubernetes clusters to Azure, running key
experiments in fields including robotics and gaming both in
Azure and in its own data centers.
Outcome: Researchers now spend far less time launching experiments and
scaling them out to hundreds of GPUs. OpenAI has also
benefited from greater portability and lower costs given the
ability to use its own data centers when appropriate.
Because Kubernetes provides a consistent
API, we can move our research experiments
very easily between clusters… [We] have a
number of teams that run their experiments
both in Azure and in our own data centers,
just depending on which cluster has free
capacity, and that's hugely valuable.”
— Christopher Berner, Head of Infrastructure
OpenAI
“
Click icon to learn more

25.
Lift and shift to
containers
Microservices Machine learning IoT
Scalable Internet of Things solutions
• Portable code, runs anywhere
• Elastic scalability and
manageability
• Quick deployment and high
availability
AKS
Database
for MySQL
Azure
Cosmos DB
SQL
Database
IoT Hub
IoT Edge
devices
IoT Edge
Connector

26.
Azure IoT Edge
Compress
Encrypt
Send to Cloud
Azure
Lift and shift to
containers
Microservices Machine learning IoT
Consistent management between cloud and edge
2. Virtual node, an implementation
of Virtual Kubelet, serves as the
translator between cloud and edge
3. IoT Edge Provider in virtual node
redirects containers to IoT Edge
and extend AKS cluster to target
millions of Edge devices
4. Consistent update, manage, and
monitoring as one unit in AKS
using single pod definition
Kubernetes cluster
Node
Docker
container
Docker
container
Node
Docker
container
Docker
container
Virtual node
IoT Edge
Provider
Docker
container
Docker
containers
Decrypt
Decompress
Send to Storage
1. Azure IoT Edge encrypts data and
send to Azure, which then decrypts
the data and send to storage

27.
Challenge: For the NobelPrize.org relaunch, Nobel needed simplicity at scale
to modernize their 10,000+ page worldwide site ahead of the
quickly-approaching Nobel Prize announcements, bringing millions
of visits each year.
Solution: To leverage the scalability and ease of PaaS, Nobel brought their
containerized Linux application to Azure App Service Environment
to ensure that their popular site can handle high traffic loads and
meets their security requirements.
Outcome: Because the Linux on ASE PaaS offering abstracts away the
complications of maintaining infrastructure, it was simple for Nobel
to quickly shift their traditional application to a modern, flexible
app in time for announcement week. Simple to get started, but can
seamlessly handle scale with little maintenance.
Relaunching the home of Nobel Prize awarded laureates
and their discoveries
The use of [Azure App Service] allows us to rapidly test and implement new ideas with
the mission to inform, inspire and engage our global audience on the Nobel Prize.”
— Hans Mehlin, Chief Technology Office, Nobel Media Click icon to visit the Nobel Prize website

28.
App Service
Environment (ASE)
Developer
Docker
Image
App Service Plan
…or…
Webhook
…or…
Docker
Hub
Azure
Container
Registry
Private
Registry
App
Deployment Deployment
Slots
App Service
Diagnostics
Authentication/
Authorization
Domains &
Certs
Docker Container(s)
Azure Portal
CLI
ARM Template
(
(
Autoscale
Rules
Testing &
Production
A look into a production-ready app on App Service…
• Run containerized applications
without worrying about the
infrastructure
• Leave the scaling orchestration to
our PaaS platform for hassle-free
scaling for higher traffic loads
• Secure your applications in an
Azure Virtual Network to meet
security requirements
Simple to get started, but also
robust to handle global scale
with little maintenance

29.
Nobel Prize website
Deploy a global website using Linux containers in a PaaS environment
Visitor/editor/
developer
Full page cache and
SSL termination
CDN
Digital asset
management
Public-facing
endpoint
Microsoft Azure
Linux on ASE
Containerized apps
Prod, staging slots,
dev tools
Container
Registry
ASE Azure Redis
Cache
Gateway
Subnets
VPN
Azure Blob
Storage
Azure
MySQL
Azure Redis
Cache
Main virtual network
Internet
Elastic Search
traffic
Container Registry
traffic
Site 2
site VPN
Candidator DC
Network
Point 2
site VPN
Developer
• Run containerized applications
without worrying about the
infrastructure
• Leave the scaling orchestration to
our PaaS platform for hassle-free
scaling for higher traffic loads
• Secure your applications in an
Azure Virtual Network to meet
security requirements
Simple to get started, but also
robust to handle global scale
with little maintenance

30.
Xerox Docushare Flex—Before
• Each customer instance assigned
to dedicated Java and Postgres
VMs
• Set of backing services for
authentication, file sharing,
common data sources
Typical 3-tier architecture
using VMs
Problem: Due to overhead and
management burden of VMs,
adding a new customer takes 24
hours, slowing down customer
onboarding through sales and
partner network
Postgres
Java
Customer A
Postgres
Java
Customer B
Postgres
Java
Customer C
Virtual Machines
Backing Services
LDAP SFTP PRIZM
Internet

31.
Xerox Docushare Flex—After
• Convert Postgres database to a
shared backing service
• Run Java application in containers
with no code modification
• Switch to NGINX-based web-tier
with LetsEncrypt for free SSL/TLS
• New Helm chart created to
automate customer onboarding
to AKS
Typical 3-tier architecture
using AKS
Outcome: Run the Java application
in containers on AKS, decreasing
provisioning time from 24 hours to
10 minutes, accelerating sales and
customer onboarding with no
code changes required
Java
Customer A
Java
Customer B
Java
Customer C
AKS
Internet
NGINX
Backing Services
LDAP SFTP PRIZM Postgres
Azure
Container
Registry

32.
Benefits: • Onboard prospective customers faster through automation
• Enable self-service demo environments for large partners
• Reduce administrative overhead for small Ops team
• No code modification required
Xerox moves to containers in Azure for faster demo
environment releases
Thanks to Azure Kubernetes Service, we can now spin up new demo
environments in 10 minutes instead of 24 hours. Moving
Docushare Flex from virtual machines to containers in Azure allows
us to provision environments faster, empowering our sales and
partner network.”
— Robert Bingham, Director of DocuShare
Cloud Operations at Xerox

33.
Open source culture
AKS
Overview
Introduction
Top
scenarios
Open source
culture
Resources

34.
Development DevOps Monitoring Networking Storage Security
Take advantage
of services and
tools in the
Kubernetes
ecosystem
…or…
Leverage growing
Azure support
RBAC
VS Code
Azure
DevOps
ARM
Azure Monitor Azure VNET Azure Storage
Azure
Container
Registry
AAD
Key Vault
Work how you want with opensource tools and APIs

35.
#2 overall
individual
contributor to
Kubernetes
(Brendan Burns)
#4 overall individual
contributor to Docker
(John Howard)
#1-3 overall
individual
contributors to
Helm
70 Microsoft
employees have
made
contributions to
Kubernetes
Microsoft contributes open source containers

36.
Resources
AKS
Overview
Introduction
Top
scenarios
Open source
culture
Resources

37.
• Azure Kubernetes Service (AKS)
• Containers on Azure pitch deck
• Smart Hotel 360 Demo
• Documentation resources
• Ebook for distributed systems
• Distributed system HoL
• AKS HoL
Sign up for a free Azure account
Hone your skills with Azure training
Check out the Azure container videos page
Get the code from GitHub
AKS resources