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Introduction to kubernetes
- 1. Introduction to Kubernetes Mete Atamel Developer Advocate for Google Cloud @meteatamel
- 2. Confidential & ProprietaryGoogle Cloud Platform 2 Mete Atamel Developer Advocate for Google Cloud Platform @meteatamel [email protected] meteatamel.wordpress.com @meteatamel
- 3. Who are you?
- 4. Agenda The Monolith What is the Monolith and why is it bad? Breaking The Monolith into Microservices Why Microservices is the way to go? Problems with Microservices Exchanging one set of problems with another? Containers and Kubernetes What are containers and Kubernetes, how do they help? Kubernetes building blocks Pods, services, replication controllers/set and more @meteatamel
- 6. Confidential & ProprietaryGoogle Cloud Platform 6 What is the Monolith? @meteatamel APP SERVER Module 1 Module 2 Module 3 DB
- 7. Confidential & ProprietaryGoogle Cloud Platform 7 Problems with the Monolith Unnecessary tight coupling among different modules All at once, or none at all update policy Hard to scale different parts independently Ignores different development velocity of different teams completely Hard to establish ownership of the whole system as it’s huge Hard to debug and test in general, hard to run on a single development machine @meteatamel
- 8. Breaking the Monolith into Microservices @meteatamel
- 9. Confidential & ProprietaryGoogle Cloud Platform 9 The Monolith to Microservices @meteatamel Microservice1 DB1 Microservice2 DB2 Microservice3 DB3
- 10. Confidential & ProprietaryGoogle Cloud Platform 10 Problems with Microservices Need to worry about multiple independent systems instead of one Can be hard to debug and test across multiple services without proper logging “But it works on my machine!” problem still applies Common maintenance problems still apply: Redundancy, resilience, rolling upgrades, rolling downgrades @meteatamel
- 12. Confidential & ProprietaryGoogle Cloud Platform 12 Quick recap of Containers @meteatamel Lightweight Hermetically sealed Isolated Easily deployable Introspectable Runnable Linux processes Improves overall developer experience Fosters code and component reuse Simplifies operations for cloud native applications Docker
- 13. Confidential & ProprietaryGoogle Cloud Platform 13 Everything at Google runs on containers Gmail, Web Search, Maps, ... MapReduce, batch, ... GFS, Colossus, ... Google’s Cloud Platform: VMs run in containers! We launch over 2 billion containers per week
- 14. Confidential & ProprietaryGoogle Cloud Platform 14 Containers are great but not enough Containers help to create a lightweight and consistent environment for apps But it does not solve common app management problems: ● Deploy your a new version of your app reliably ● Create resiliency ● Scale up and down ● Rollback a deployment ● Health checks ● Graceful shutdown ● Etc. etc. etc. @meteatamel
- 15. Confidential & ProprietaryGoogle Cloud Platform 15 Kubernetes comes to rescue http://kubernetes.io Open source container management platform Based on years of experience running Borg at Google Runs everywhere: your laptop, on-prem, different cloud platforms Helps with reliable deployment of apps, scaling, roll out and roll back of versions, autoscaling, health checks and more! @meteatamel
- 16. Confidential & ProprietaryGoogle Cloud Platform 16 Kubernetes Cluster @meteatamel K8s Master API Server Dash Board scheduler Kubelet Kubelet Kubelet Kubelet Container Registry etcdControllers web browsers kubectl web browsers Config file Image
- 17. Confidential & ProprietaryGoogle Cloud Platform 17 Kubernetes Cluster @meteatamel K8s Master API Server Dash Board scheduler Kubelet Kubelet Kubelet Kubelet etcdControllers web browsers kubectl web browsers Config file Image Container Registry
- 18. Confidential & ProprietaryGoogle Cloud Platform 18 Kubernetes Cluster on GKE @meteatamel
- 20. Confidential & ProprietaryGoogle Cloud Platform 20 Pods @meteatamel The atom of scheduling for containers Represents an application specific logical host Hosts containers and volumes Each has its own routable (no NAT) IP address Ephemeral • Pods are functionally identical and therefore ephemeral and replaceable Pod Web Server Volume Consumers
- 21. Confidential & ProprietaryGoogle Cloud Platform 21 Pods @meteatamel Pod Git Synchronizer Node.js App Container Volume Consumersgit Repo Can be used to group multiple containers & shared volumes Containers within a pod are tightly coupled Shared namespaces • Containers in a pod share IP, port and IPC namespaces • Containers in a pod talk to each other through localhost
- 22. Confidential & ProprietaryGoogle Cloud Platform 22 Pods @meteatamel Pods have IPs which are routable Pods can reach each other without NAT Even across nodes No Brokering of Port Numbers These are fundamental requirements Many solutions GCE Advanced Routes, AWS Flannel, Weave, OpenVSwitch, Cloud Provider 10.1.2.0/24 10.1.1.0/24 10.1.1.211 10.1.1.2 10.1.2.106 10.1.3.0/24 10.1.3.4510.1.3.17 10.1.3.0/24
- 23. Confidential & ProprietaryGoogle Cloud Platform 23 Labels @meteatamel Pod Pod frontend Pod frontend Pod Pod type = FE version = v2 type = FE version = v2 ● Metadata with semantic meaning ● Membership identifier ● The only Grouping Mechanism Behavior Benefits ➔ Allow for intent of many users (e.g. dashboards) ➔ Build higher level systems … ➔ Queryable by Selectors Dashboard selector: type = FE Dashboard selector: version = v2
- 24. Confidential & ProprietaryGoogle Cloud Platform 24 Label Expressions @meteatamel Pod Pod frontend Pod frontend Pod Pod env = qa env = test ● env = prod ● tier != backend ● env = prod, tier !=backend Expressions ● env in (test,qa) ● release notin (stable,beta) ● tier ● !tier env = prod Pod env = prod Dashboard selector: env = notin(prod)
- 25. Confidential & ProprietaryGoogle Cloud Platform 25 Services @meteatamel Client Pod Container Pod Container Pod Container A logical grouping of pods that perform the same function (the Service’s endpoints) • grouped by label selector Load balances incoming requests across constituent pods Choice of pod is random but supports session affinity (ClientIP) Gets a stable virtual IP and port • also a DNS nametype = Service Label selector: type = FE VIP type = FE type = FE type = FE
- 26. Confidential & ProprietaryGoogle Cloud Platform 26 Replication Controllers/Sets @meteatamel Replication Controller Pod frontend Pod frontend app = demo app = demo app = demo ReplicaSet #pods = 3 app = demo color in (blue,grey) show: version = v2 color = blue color = blue color = grey Behavior Benefits ● Keeps Pods running ● Gives direct control of Pod #s ● Grouped by Label Selector ➔ Recreates Pods, maintains desired state ➔ Fine-grained control for scaling ➔ Standard grouping semantics Pod Pod Pod
- 27. Confidential & ProprietaryGoogle Cloud Platform 27 Replication Controllers/Sets @meteatamel ReplicaSet - Name = “backend” - Selector = {“name”: “backend”} - Template = { ... } - NumReplicas = 4 API Server 3 Start 1 more OK 4 How many? How many? Canonical example of control loops Have one job: ensure N copies of a pod ● if too few, start new ones ● if too many, kill some ● group == selector Replicated pods are fungible ● No implied order or identity
- 28. Confidential & ProprietaryGoogle Cloud Platform 28 Scaling @meteatamel Service Label selectors: version = 1.0 type = Frontend Service name = frontend Label selector: type = BE Replication Controller Pod frontend Pod version= v1 version = v1 ReplicaSet version = v1 #pods = 1 show: version = v2 type = FE type = FE Pod frontend Pod version = v1 type = FE ReplicaSet version = v1 #pods = 2 show: version = v2 Pod Pod ReplicaSet version = v1 type = FE #pods = 4 show: version = v2 version = v1 type = FE
- 29. Confidential & ProprietaryGoogle Cloud Platform 29 Canary @meteatamel Service Label selectors: version = 1.0 type = Frontend Service name = backend Label selector: type = BE Replication Controller Pod Pod frontend Pod version= v1 version = v1 ReplicaSet version = v1 type = BE #pods = 2 show: version = v2 type = BE type = BE Replication Controller ReplicaSet version = v2 type = BE #pods = 1 show: version = v2 Pod frontend Pod version = v2 type = BE
- 30. Confidential & ProprietaryGoogle Cloud Platform 30 Autoscaling @meteatamel Replication Controller Pod frontend Pod name=locust name=locust ReplicaSet name=locust role=worker #pods = 1 show: version = v2 Pod frontend Pod name=locust ReplicaSet name=locust role=worker #pods = 2 show: version = v2 Pod Pod name=locust Scale CPU Target% = 50 Heapster role=worker role=worker role=worker role=worker ReplicaSet name=locust role=worker #pods = 4 70% CPU 40% CPU > 50% CPU< 50% CPU
- 31. Confidential & ProprietaryGoogle Cloud Platform 31 Rollout @meteatamel API DeploymentDeployment Create frontend-1234567 Deployment Create frontend-1234567 Scale frontend-1234567 up to 1 Deployment Create frontend-1234567 Scale frontend-1234567 up to 1 Scale frontend-7654321 down to 0 Pod Pod frontend Pod version = v1 ReplicaSet frontend-1234567 version = v2 type = BE #pods = 0 show: version = v2 ReplicaSet frontend-7654321 version = v1 type = BE #pods = 2 version: v2 ReplicaSet frontend-7654321 version: v1 type: BE #pods = 0 version: v1 ReplicaSet frontend-1234567 version = v2 type = BE #pods = 1 show: version = v2 ReplicaSet frontend-1234567 version: v2 type: BE #pods = 2 type = BE type = BE Pod version: v2 type = BE Servic e be-svc Deployment Create frontend-1234567 Scale frontend-1234567 up to 1 Scale frontend-7654321 down to 0 Scale frontend-1234567 up to 2 kubectl edit deployment ...
- 32. Confidential & ProprietaryGoogle Cloud Platform 32 There is much more! @meteatamel