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Kubernetes Boulder - Kit Merker - Cloud Native Deployment
This document discusses cloud-native deployment and Kubernetes. It describes how containers isolate applications and enable portable, consistent deployment across environments. Kubernetes provides a platform for automating deployment, scaling, and management of containerized applications. It schedules containers on hosts and provides services for load balancing and discovery. The document outlines how Kubernetes uses immutable deployments, secrets, and configuration maps to deploy applications in a cloud-native way without breaking production systems during upgrades.
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Similar to Kubernetes Boulder - Kit Merker - Cloud Native Deployment
Kubernetes Boulder - Kit Merker - Cloud Native Deployment
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- 2. What is “CloudNative” How do you deploy applications built for the Cloud? Don’t break production Complex upgrades Secrets and reuse
- 3. Kit Merker Product Manager GoogleCloud Platform @kitmerker | kitm@google.com
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- 5. Old way: installapplications on host kernel libs app app app Application and OS share filesystem Use OS distribution package manager Entangled with each other and with host • Executables • Configuration • Shared libraries • Process and lifecycle management Immutable VM images provide predictable rollouts and rollbacks • but are heavyweight and not portable app
- 6. New way: deploycontainers libs app kernel libs app libs app libs app OS-level virtualization Isolated, from each other and from the host • filesystems • processes • resources Small and fast ⇒ enables 1:1 app to image • Unlocks benefits of microservices • Decouple build (Dev) from deployment (Ops) • Consistency from development to production • Portable across OS distros and clouds • Application-centric management
- 7. Everything at Google runsin containers
- 8. Everything at Google runsin containers Launch over 2 billion containers per week.
- 9. job hello_world ={ runtime = { cell = 'ic' } // Cell (cluster) to run in binary = '.../hello_world_webserver' // Program to run args = { port = '%port%' } // Command line parameters requirements = { // Resource requirements ram = 100M disk = 100M cpu = 0.1 } replicas = 5 // Number of tasks } 10000 Developer View
- 10. web browsers BorgMaster link shard UIshardBorgMaster link shard UI shardBorgMaster link shard UI shardBorgMaster link shard UI shard Scheduler borgcfg web browsers scheduler Borglet Borglet Borglet Borglet Config file BorgMaster link shard UI shard persistent store (Paxos) Binary Developer View What just happened?
- 11. Hello world! Hello world! Hello world! Hello world!Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world!Hello world! Hello world! Hello world! Hello world! Hello world! Hello world!Hello world! Hello world! Hello world! Hello world! Image by Connie Zhou Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world!
- 12. Kubernetes Greek for “Helmsman”;also the root of the words “governor” and “cybernetic” ● Infrastructure for containers ● Schedules, runs, and manages containers on virtual and physical machines ● Platform for automating deployment, scaling, and operations ● Inspired and informed by Google’s experiences and internal systems ● 100% Open source, written in Go
- 13. gcr.io web browsers Scheduler kubectl webbrowsers scheduler Kubelet Kubelet Kubelet Kubelet Config file Kubernetes Master Container Image Developer View What just happened?
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- 15. Google Cloud Platform15 Building block: Sets of Containers Pod /data Containers: ● Handle package dependencies ● Different versions, same machine ● No “DLL hell” python 3.4.2 glibc 2.21 MySite python 2.7.9 glibc 2.19 MyCachePods: ● Co-locate containers ● Shared volumes ● IP address, independent port space ● Unit of deployment, migration
- 16. Google Cloud Platform16 Unit of deployment: Services Service IP Service: ● Replicated pods ○ Source pod is a template ● Auto-restart member pods ● Abstract name (DNS) ● IP address for the service ○ in addition to the members ● Load balancing among replicas Load Balancer
- 17. Google Cloud Platform17 The Flow of Deployment Deploy flags, scripts, keys, … Package lock binary dependencies (containers) Build lock binary version source control binary libraries resources static config image ?
- 18. Google Cloud Platform18 Example: Rolling Upgrade with Labels Pods: Labels: frontend v1.2 frontend v1.2 frontend v1.2 frontend v1.2 frontend v1.3 frontend v1.3 frontend v1.3 frontend v1.3 frontend Replication Controller replicas: 4 v1.2 Replication Controller replicas: 1 v1.3 replicas: 3 replicas: 2replicas: 3replicas: 2replicas: 1 replicas: 4replicas: 0
- 19. Google Cloud Platform19 The Flow of Configuration: Immutable + Cloud libraries resources static config Package lock binary dependencies source control binary image Build lock binary version load balancer Deploy lock runtime state (flags, keys, …) load balancer auto-scaler each step removes degrees of freedom
- 20. Google Cloud Platform20 Need Secrets & Deploy-time Configuration Some things cannot be baked into a container 1. Credentials/key material a. Kubernetes has solved this with the secret model b. A volume, containing secrets, that is mapped into a pod 2. Environment-specific metadata a. Kubernetes has solved this with the configMap model b. A volume mapped into a pod with key/value pairs c. Can also be used to via environment variables
- 21. Google Cloud Platform21 The Flow of Configuration - with Secrets/Config libraries resources static config Package lock binary dependencies source control binary image Build lock binary version load balancer Deploy lock runtime state (flags, keys, …) load balancer auto-scaler each step removes degrees of freedom Mounted Volumes
- 22. Google Cloud Platform22 Holy War: Scripting vs. DSL Holy War: Scripting vs. DSL Image credit - larping.com
- 23. Google Cloud Platform23 Holy War: Scripting vs. DSL Scripting ● Pros: ○ Simple ○ Turing Complete ● Cons: ○ No model to support introspection ○ No declaration of intent ○ Fragile - needs to be coordinated with app changes Configuration language (DSL) ● Pros: ○ Less verbose ○ Establishes a model ● Cons: ○ DSL lags resource types ○ Becomes a language without full tooling ○ Interpreted in production environment: many moving parts Image credit - larping.com
- 24. Google Cloud Platform24 Solution: Construction as deployment step 1. Want a simple declarative framework to construct deployments a. If you need deep logic, it should be written in a first-class language b. Code, if needed, generates the (immutable) configuration 2. We need to support encapsulation and composition a. Much like abstract data types or objects The entire deployment graph becomes immutable.
- 25. Google Cloud Platform25 The Flow of Configuration libraries resources static config Package lock binary dependencies source control binary image Build lock binary version load balancer Deploy lock runtime state (flags, keys, …) load balancer auto-scaler load balancer Construct lock topology compose, physical resources each step removes degrees of freedom load balancer auto-scaler
- 26. Google Cloud Platform26 Immutable VM spec: VM(cores, RAM, image, zone) REST “create” call to instantiate Start with Cloud Primitive Types load balancer auto-scaler network routes kubernetes cluster vm disk managed instance group ...
- 27. Google Cloud Platform27 “Frontend” builds on Cloud Primitive Types FE Template Frontend FE.yaml ... resources: - name: FE_App type: FE properties: zone:us-central1-a FEimage:https://www.googleapis… publish: true load balancer auto-scaler network routes managed instance group config type
- 28. Google Cloud Platform28 Nested Deployment model imports: path: myapp.jinja resources: - name: MyApp_1 type: MyApp.jinja properties: zone:us-central1-a FEimage:https://www.googleapis… BEImage:https://www.googleapis… deployment:production ... MyApp Template MyApp.yaml Frontend Backend Encapsulated Nested Types
- 29. Google Cloud Platform29 Nested resource model - fully expanded imports: path: myapp.jinja resources: - name: MyApp_1 type: MyApp.jinja properties: zone:us-central1-a FEimage:https://www.googleapis… BEImage:https://www.googleapis… deployment:production ... MyApp Template FE TemplateMyApp.yaml type Frontend FE.yaml ... resources: - name: FE_App type: FE properties: zone:us-central1-a FEimage:https://www.googleapis… publish: true BE Template FE.yaml ... resources: - name: FE_App type: FE properties: zone:us-central1-a BEimage:https://www.googleapis… numberinstances: 3 instancetype: n1-standard-8 load balancer load balancer auto-scaler load balancer auto-scaler network routes managed instance group load balancer network routes vm 1 vm 2 vm 3 disk 1 disk 2 disk 3 config type Backend construction deployment
- 30. Google Cloud Platform30 Kubernetes Velocity Top 0.01% of all GitHub projects 1200+ external projects based on Kubernetes 720+ unique contributors 1.0 1.1 1.2 45+ commits / day over the last year! 100+ Meetup groups around the world
- 31. Google Cloud Platform31 Chat: slack.k8s.io Visit: kubernetes.io Share: @kubernetesio Code: github.com/kubernetes/kubernetes open community open design open source open to ideas Invitation: Kubernetes is Open
- 32. Try out GoogleContainer Engine https://cloud.google.com/container-engine/
- 33. What is “CloudNative” How do you deploy applications built for the Cloud? Don’t break production Complex upgrades Secrets and reuse Construct deploy graph offline, roll it out immutably Use a real language to generate declarative instructions Mount volumes for secrets & runtime config (Hint: use Helm & Kubernetes!)
- 34.