This document provides an introduction and overview of Kubernetes for deploying and managing containerized applications at scale. It discusses Kubernetes' key features like self-healing, dynamic scaling, networking and efficient resource usage. It then demonstrates setting up a Kubernetes cluster on AWS and deploying a sample application using pods, deployments and services. While Kubernetes provides many benefits, the document notes it requires battle-testing to be production-ready and other topics like logging, monitoring and custom autoscaling solutions would need separate discussions.

1. Kubernetes 101

2. whoami
DevOps Engineer @ Spreaker
h"p://twi"er.com/jnardiello

3. What to expect

4. A Kubernetes primer

5. Tips, tricks, sweat and blood
real life experience bringing k8s to produc5on

7. High-load system
Distributed architecture
Our whole infrastructure is on AWS

8. Our pain points

9. Underused machines

10. Autoscaling would take minutes

11. Non-athomic provisioning makes it difficult to
roll-out upgrades or migrate services

12. The solu)on: Docker!
Perfectly determinis/c, ephemeral, light-
weight

13. Unfortunately
containers are just half
of the equa3on
Real costs will emerge as you
try to make containers work
together

14. Kubernetes

15. def.
(Opinionated) Orchestra1on framework to
organise and deploy container-based
applica1ons

16. Agnos&c sandbox where you
provide the desired state of your
services/apps. Kubernetes aims to
take care of everything else

17. Disclaimer!
From the outside Kubernetes is a
black box

18. But inner mechanisms makes it a
complex beast to master

20. We got the cookies!
a.k.a. features

21. Self-healing services
Health checks on your containers,
rescheduling failing jobs

22. Dynamic scaling
Ensure current state and scale your pods (but
it's s4ll on you to scale the nodes)

23. Networking and rou/ng
Route traffic to your containers

24. Efficient physical resources usage
Scheduling containers on physical/vms nodes
according to their effec7ve needs

25. Enough talking

26. Crea%ng a cluster
MULTIZONE=1 KUBERNETES_PROVIDER=aws
KUBE_AWS_ZONE=eu-west-1b NON_MASQUERADE_CIDR="172.16.0.0/14"
SERVICE_CLUSTER_IP_RANGE="172.16.0.0/16" DNS_SERVER_IP="172.16.0.10"
MASTER_IP_RANGE="172.17.0.0/24" CLUSTER_IP_RANGE="172.18.0.0/16"
MASTER_SIZE=m3.medium NODE_SIZE=m3.medium NUM_NODES=1
./cluster/kube-up.sh

27. h"ps://asciinema.org/a/
4xnz9hc3lvs6zp3eakrf2qcjn

28. $ kubectl get nodes
NAME STATUS AGE
ip-172-20-0-209.eu-west-1.compute.internal Ready 47m
ip-172-20-0-210.eu-west-1.compute.internal Ready 47m
ip-172-20-0-211.eu-west-1.compute.internal Ready 47m
ip-172-20-0-212.eu-west-1.compute.internal Ready 47m
ip-172-20-0-213.eu-west-1.compute.internal Ready 47m

29. kubectl is your local CLI command
center.
You can issue commands to the cluster either by kubectl or
directly calling REST APIs exposed by the master

30. We got the nodes, we are ready
Our first container on kubernetes!

31. YAML all the things!

32. Pods
A pod is a group of one or more containers. Pods are the smallest
deployable units that can be created and managed in Kubernetes.

33. Replica(on Controllers
A replica*on controller ensures that a specified number of pod
“replicas” are running at any one *me

34. Deployments
Pod + Replica-onController

35. apiVersion: extensions/v1beta1
kind: Deployment
metadata:
name: dummy-worker
spec:
replicas: 1
template:
metadata:
labels:
app: dummy-worker
spec:
containers:
- name: dummy-worker
image: jnardiello/forever
env:
- name: SOME_ENV_VAR
value: envvarvalue
resources:
limits:
cpu: "256m"
memory: "128Mi"
requests:
cpu: "5m"
memory: "8Mi"

36. Services
A Kubernetes Service is an abstrac0on which defines a logical set
of Pods and a policy by which to access them.

37. kind: Service
metadata:
name: dummy-worker-service
spec:
ports:
- port: 80·
targetPort: 8000
protocol: TCP
selector:
app: dummy-worker
externalIPs: [53.8.3.2]

38. There are different types of services
NodePorts, proxied by the master
LoadBalancer, crea'ng an actual ELB on AWS
Ingress [beta] - WARNING, do not use

39. Deploy the container
h"ps://asciinema.org/a/7c42c8itmyz3982p6fmo9ecvi

40. Resilient applica,ons
h"ps://asciinema.org/a/2bxo51ond7ac4haaguneingmv

41. Kubernetes is truly amazing
(for POCs)

42. Ba#le-tested cluster
A long way before reaching produc4on ready
There will be blood!

43. Opinionated Logging

44. Opinionated Monitoring

45. Master skynet, then implement your
own solu4on

46. Custom metrics-based Autoscaling
OpsFactory/Kappa

47. These topics are for another /me
(We should probably do Kubernetes102)

48. Ques%ons?
@jnardiello