In this slide deck, Lakmal discusses best practices for deploying applications in Docker and Kubernetes while discussing Docker and Kubernetes concepts.

1. Senior Director Cloud Architecture, WSO2
@lakwarus
Deploying Applications in K8S and
Docker
Lakmal Warusawithana

2. Old Way
Install Application on

3. New Way
Deploy as a Container

4. Docker
Docker provides an easy-to-use
packaging model to bundle the
application

5. Reality
However in many cases, a single
container is not enough to run an
application

7. K8S
Kubernetes is an open source
container orchestration system that
helps to automate deployment,
scaling, and management of
containerized applications.

8. K8S Architecture (From Above 5000 ft)

9. K8S Core Primitive

10. Small group of containers and
volume
Tightly coupled
● The atom of replication
and placement
Logical host for containers
● Echo pod get an IP address
● Share data: localhost,
volume, IPC, etc.
K8S POD

11. Storage automatically
attached to a Pod
● Local storage
● Cloud block storage
○ AWS EBS, GCE persistent
● Cluster storage
○ NSF, Gluster
○ iSCSI, Cinder
● Special volumes
○ Git repo, secret
K8S Volume

12. Ensures N copies of Pod
● If too few, start new one
● If too many, kill some
Enables self-healing
Facilitates auto scaling
K8S Replication Controller

13. Group of pods thats work
together
DNS name
Load balanced: name map to
a stable virtual IP
Decoupled from Pods and
Replication controllers
K8S Service

14. Secrets: Tokens, credentials,
certs, etc.
Don’t put them in a container
image.
Inject them as virtual volume
into pods
● Not backed into images
nor pod config
● Kept in memory, never
touches disk
K8S Secret

15. Multi tenancy in K8S
is namespace has its own
● Resources (Pods, Services,
etc.)
● Policies (who can or
cannot perform an action
in their tenancy)
● Constrain (how much
quota, etc.)
K8S Namespace

16. 12-factor says config comes
from the environment.
● Should not be baked into
Docker image
ConfigMap inject config as a
virtual volume into the Pods
● Late binding, live update
(atomic)
● Also available as env vars
K8S ConfigMap

17. Services are assumed L4
Ingress in L7
Ingress maps HTTP/HTTPS
incoming traffic to backend
services
● By host headers
● By URL paths
K8S Ingress

18. K8S Rolling Update

19. K8S Rolling Update

20. K8S Rolling Update

21. K8S Rolling Update

22. K8S Rolling Update

23. K8S Rolling Update

24. K8S Rolling Update

25. K8S Rolling Update

26. Rolling update too imperative
Deployment manage RC
changes for you
● Kubectl edit /apply is all
you need
Aggregate stats
Can have multiple updates
inflight
K8S Deployment

27. How to run pod in every
node? Or subset of nodes?
Daemonset
● Like ReplicationController
● Do one thing
● Don’t overload
Which node is a selector
K8S Daemonset

28. Give Pods time to clean up
Catch SIGTERM, clean-up exit
ASAP
Pods status Terminating
30 seconds by default
● Finish inflight operation
● Flush to disk
● Log state
K8S Graceful Termination

29. Automatically scale RCs to a
target utilization
● CPU utilization for now
Operate within user-defined
min/max bound
Set it and forget it
K8S Horizontal Pod Autoscaler

30. Demo: Hello World with kubectl

31. ● Draft
● Gitkube
● Helm
● Ksonnet
● Skaffold
● Metaparticle
● Ballerina
Tools and framework for K8S

32. ● Draft
● Gitkube
● Helm
● Ksonnet
● Skaffold
● Metaparticle
● Ballerina
Tools and framework for K8S
● deploy code to k8s cluster (automates
build-push-deploy)
● deploy code in draft-pack supported
languages without writing dockerfile or
k8s manifests
● needs draft cli, helm cli, tiller on cluster,
local docker, docker registry

33. ● Draft
● Gitkube
● Helm
● Ksonnet
● Skaffold
● Metaparticle
● Ballerina
Tools and framework for K8S
● deploy code to k8s cluster (automates
build-push-deploy)
● git push to deploy, no dependencies on
your local machine
● needs dockerfile, k8s manifests in the
git repo, gitkube on cluster

34. ● Draft
● Gitkube
● Helm
● Ksonnet
● Skaffold
● Metaparticle
● Ballerina
Tools and framework for K8S
● deploy and manage charts (collection
of k8s objects defining an application)
on a k8s cluster
● ready made charts for many common
applications, like mysql, mediawiki etc.
● needs helm cli, tiller on cluster, chart
definition locally or from a repo

35. ● Draft
● Gitkube
● Helm
● Ksonnet
● Skaffold
● Metaparticle
● Ballerina
Tools and framework for K8S
● define k8s manifests in jsonnet, deploy
them to k8s cluster
● reusable components for common
patterns and stacks, like
deployment+service, redis
● needs jsonnet knowledge, ksonnet cli

36. ● Draft
● Gitkube
● Helm
● Ksonnet
● Skaffold
● Metaparticle
● Ballerina
Tools and framework for K8S
● deploy code to k8s cluster (automates
build-push-deploy)
● watches source code and triggers
build-push-deploy when change
happens, configurable pipeline
● needs skaffold cli, dockerfile, k8s
manifests, skaffold manifest in folder,
local docker, docker registry

37. ● Draft
● Gitkube
● Helm
● Ksonnet
● Skaffold
● Metaparticle
● Ballerina
Tools and framework for K8S
● deploy your code in metaparticle
supported languages to k8s
(automates build-push-deploy)
● define containerizing and deploying to
k8s in the language itself, in an
idiomatic way, without writing
dockerfile or k8s yaml
● needs metaparticle library for
language, local docker

38. ● Draft
● Gitkube
● Helm
● Ksonnet
● Skaffold
● Metaparticle
● Ballerina
Tools and framework for K8S
● Generate docker images, k8s artifacts
depending on annotation defined in
the code.
● Support many Kubernetes
functionalities like; all kind of
Kubernetes services, deployment,
ingress, secrets, persistent volumes,
config maps, liveness probe and
horizontal pod autoscaling.

39. Demo: Metaparticles with K8S

40. Demo: Ballerina with K8S

41. ● https://kubernetes.io/docs/concepts
● https://www.youtube.com/watch?v=A4A7ybtQujA
● https://www.slideshare.net/DanielSmith272/whats-new-in-k
ubernetes
● https://blog.hasura.io/draft-vs-gitkube-vs-helm-vs-ksonnet
-vs-metaparticle-vs-skaffold-f5aa9561f948
References

42. THANK YOU
wso2.com