The document discusses the key components and concepts of cloud-native computing, emphasizing microservices, container packaging, and dynamic scheduling. It details the benefits of using Kubernetes for managing microservices, such as improving agility, automation, and orchestration in application development. Additionally, it covers how services are defined, discovered, and managed within Kubernetes clusters, highlighting features like service scoping and DNS integration.

1. Ingredients for micro-
services based platform
for cloud native computing
craigmcl@google.com

2. Towards cloud native computing
Container Packaged
Dynamically Scheduled
Microservices Oriented

3. Towards cloud native computing
Container Packaged
Dynamically Scheduled
Microservices Oriented
Not just Google ...
… n other internet companies

4. context
posit that “cloud native” is three things
1. container packaged
2. dynamically scheduled
3. micro-services oriented
micro-services
• lets developers assemble small, independently deployable components
• create loosely coupled, more agile systems
• a basic atom of consumption for software
• a basic atom of management for software

5. why?
Loosely coupled = easier to build and extend
• Compose applications from micro-services
• Mix in and extend third party services
• More agile systems and teams

6. why?
Separation of concerns = specialization
• Separate infrastructure ops from cluster ops from app ops
• Radically increase code reuse
• Radically reduced operations overhead

7. why?
Deeper automation = fewer bad outcomes
• Higher abstraction provides more insight into behavior
• Orchestration made far easier
• Self-healing and self-managing systems

8. Greek for “Helmsman”; also the root of the word
“Governor”, “Cybernetics’
• Container orchestrator
• Runs Docker containers
• Supports multiple cloud and bare-metal
environments
• Inspired and informed by Google’s experiences
and internal systems
• Open source, written in Go
Manage services, not machines
Kubernetes

9. libs
app
kernel
libs
app
libs
app
libs
app
libs
app
kernel
libs
app
libs
app
libs
app
Kubernetes Master
libs
app
kernel
libs
app
libs
app
libs
app
Kubernetes gives you a cluster

10. Pod
Labels
Replication Controller
Service
Kubernetes Core Concepts

11. Group of containers
Live and die together
Shared network interface
Pod
Serving app
Data updater
Log collector
Pod

12. Label anything
Name-value pair
Make your own
Grouping via label selector
Pod
App
Log Collector
...
type = Frontend
version = 1.0
Labels

13. Replication
Controller
Replicas → 2
Pod
App
Log Collector
...
type = Frontend
version = 1.0
Pod
App
Log Collector
...
type = Frontend
version = 1.0
Replication Controller

14. Replication
Controller
Replicas → 1
Pod
App
Log Collector
...
type = Frontend
version = 1.0
Pod
App
Log Collector
...
type = Frontend
version = 1.0
Replication Controller

15. Replication
Controller
Replicas → 2
Pod
frontend
Pod
type = Frontend
version = 1.0
Pod
type = Frontend
version = 1.0
Service
Label selectors:
version = 1.0
type = Frontend
(micro) Service

16. Pods are ephemeral
● Need something addressable that is not
How do one set of ephemeral things find another set?
● Discoverable through DNS
● Discoverable environment variables
In time can do fancy things
● Dynamic activation, context based scheduling, etc
Micro-services are a gateway to agile apps

17. Offers a minimum atom of software consumption
● Minimally (hostname, port)
● Endpoint API (enumerate membership; watch for changes)
● Relies on a label selector to establish service membership
Offers a simple framework for orchestration
● Route based on a label selector
● Blue/Green
● Canary deployment
● ...
Kubernetes Services Defined

18. Service Scoping
Two basic scope levels
● Cluster
● Namespace

19. {
"kind": "Service",
"apiVersion": "v1",
"metadata": {
"name": "my-service"
},
"spec": {
"selector": {
"app": "MyApp"
},
"ports": [
{
"protocol": "TCP",
"port": 80,
"targetPort": 9376
}
]
}
}
Creating a Service
Assumes a set of pods listening
on port 9376, with label ‘MyApp’
set.
POST to the API server will
create a new service object

20. Finding your service: Environment variables
Automatically adds environment variables that are available to each
container
REDIS_MASTER_SERVICE_HOST=10.0.0.11
REDIS_MASTER_SERVICE_PORT=6379
REDIS_MASTER_PORT=tcp://10.0.0.11:6379
REDIS_MASTER_PORT_6379_TCP=tcp://10.0.0.11:6379
REDIS_MASTER_PORT_6379_TCP_PROTO=tcp
REDIS_MASTER_PORT_6379_TCP_PORT=6379
REDIS_MASTER_PORT_6379_TCP_ADDR=10.0.0.11

21. Finding your service: DNS
An optional capability is DNS support (offered as a cluster add-on)
Server watches Kubernetes Services API and automatically creates
DNS records for services
Use DNS Lookup with <service-name>.<namespace> to resolve IP
Services in the same namespace can be found via <service-name>

22. Broadening the Service definition: External services
VM LB IP:Port
VM IP:Port
K8s
Pod
Other clouds/
On-prem IP:Port
Multiple Producers You may want to ‘mix in’ other
services (VM based/SaaS based)
Ideally consume them as if they
were ‘native’ to your cluster
To support this, it is possible to
create services without
specifying a selector

23. Towards a cluster environment
● A critical step towards ‘cloud native development’
● Brings a new ‘type B’ cloud
○ Run it natively
○ Overlay it on your ‘type A’ cloud infrastructure

24. Towards standards: CNCF
compute node
OS
out of scope
api specification
reference
implementation
container
runtime
infrastructure provisioning
agent
OCI reference
implementation
OCI api
specification
…. N
distributed systems services
resource scheduling
application definition and orchestration
software defined network software defined storage
container image repository
container image registry

25. Distributed systems services
compute node
OS
container
runtime
infrastructure provisioning
agent
…. N
resource scheduling
application definition and orchestration
software defined network software defined storage
container repository
container registry
distributed systems services
● a standard set of services that are not bound to a single node
○ supporting application use cases
■ naming/discovery
■ locking/quorum
■ state management/sharding
■ logging/monitoring
○ supporting cluster use cases
■ distributed state management
■ distributed control plane
■ logging/auditing
● a minimum atom of consumption for software
○ within the cluster
○ between clusters
○ from outside the cluster

26. Learn more.
Talk to me...
Twitter: @cmcluck
Email me: craigmcl@google.com
Follow Kubernetes…
Twitter: @kubernetesio
Github: https://github.com/googlecloudplatform/kubernetes
Blog: http://blog.kubernetes.io/