Building a Scalable Python gRPC Service using Kubernetes

Transcript

1. Building a Scalable Python
   gRPC Service using Kubernetes
   @ PyCon APAC
   Ian Lewis, Developer Advocate
   

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2. Ian Lewis
   Developer Advocate
   Google Cloud Platform
   google.com/+IanLewis-hoge
   @IanMLewis
   

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4. gRPC Concepts
   gRPC & Python
   Containers & Kubernetes Concepts
   Running a Kubernetes Service
   Wrap Up
   1
   2
   3
   4
   Agenda
   5
   

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5. Section Slide Template Option 2
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   gRPC Concepts
   Wait…. RPC? What happened to REST?
   

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6. Remote Procedure Call
   HTTP/2
   Protocol Buffers
   gRPC in a Nutshell
   

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7. HTTP/2
   

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8. ● is binary ( no telnet :( )
   ● is fully multiplexed (fewer connections)
   ● uses header compression to reduce overhead
   ● allows servers to “push” responses
   HTTP/2 ...
   

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9. Protocol Buffers
   

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10. ● are a way to serialize structured data
    ● are binary ( really no love for telnet :( )
    ● can be parsed quickly
    ● are flexible (easy to add new fields, supports addons)
    ● support code generation
    Protocol Buffers ...
    

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11. message Person {
    required string name = 1;
    required int32 id = 2;
    optional string email = 3;
    }
    Protocol Buffers
    

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12. // The greeting service definition.
    service Greeter {
    // Gets my Person data
    rpc GetMe () returns (Person) {}
    }
    Protocol Buffers
    

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13. Section Slide Template Option 2
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    gRPC & Python
    Python!
    

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14. git clone https://github.com/grpc/grpc.git
    

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15. make shared_c static_c bins/opt/grpc_python_plugin
    

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16. protoc -I ../../protos --python_out=. --grpc_out=. --
    plugin=protoc-gen-
    grpc=/path/to/bins/opt/grpc_python_plugin ../..
    /protos/helloworld.proto
    Generate Code
    

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17. Section Slide Template Option 2
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    Containers & Kubernetes
    Concepts
    What that thar be?!?!
    

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18. Current Practice
    

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19. Database
    Batch
    processing
    Cache
    Webservers
    Webservers
    Webservers
    Webservers
    

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20. kernel
    libs
    app
    app app
    No isolation
    No namespacing
    Common libs
    Highly coupled apps and OS
    app
    Shared Machines
    

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21. Some isolation
    Expensive and inefficient
    Still highly coupled to the guest OS
    Hard to manage
    app
    libs
    kernel
    libs
    app app
    kernel
    app
    libs
    libs
    kernel
    kernel
    Virtual Machines
    

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22. Containers
    

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23. build and deploy vm images
    ● Curated runtimes
    ● Rich services
    ● Auto-everything
    ● … just add code
    ● Managed collections
    ● Declarative + Dynamic
    Compute as a Continuum
    Platform
    Cluster
    ● Basic atom
    ● Run anything
    VM
    More agility
    More Flexibility
    build and deploy containers build and deploy apps
    

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24. libs
    app
    kernel
    libs
    app
    libs
    app
    libs
    app
    Containers
    

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25. Everything at Google runs in
    containers:
    • Gmail, Web Search, Maps, ...
    • MapReduce, batch, ...
    • GFS, Colossus, ...
    • Even Google Compute Engine:
    VMs in containers!
    

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26. Everything at Google runs in
    containers:
    • Gmail, Web Search, Maps, ...
    • MapReduce, batch, ...
    • GFS, Colossus, ...
    • Even Google Compute Engine:
    VMs in containers!
    We launch over 2 billion
    containers per week.
    

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27. Why containers?
    • Performance
    • Repeatability
    • Isolation
    • Quality of service
    • Accounting
    • Visibility
    • Portability
    A fundamentally different way of
    managing applications
    

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28. Kubernetes
    

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29. Greek for “Helmsman”; also the root of
    the word “Governor”
    • 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 applications, not machines
    

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30. ● 0.18.0 released
    ● 369 contributors
    ● over 8000 github stars
    ● CoreOS
    ● HP
    ● IBM
    ● Mesosphere
    ● Microsoft
    ● Pivotal
    ● Red Hat
    ● SaltStack
    ● VMWare
    ● Binary releases
    ● Logging and monitoring
    ● Richer scheduling
    ○ Labels based constraints
    ○ Smart bin-packing
    ○ Run-to-completion
    ● Updated service model
    ○ IP per service
    ● DNS integration
    Project Partners New
    Introducing Google Container Engine
    Community
    

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31. ● Group of containers
    ● Settings in a template
    ➔ Reuse across environments
    ➔ Repeatable, manageable
    Behavior Benefits
    Pod
    Web Server
    Content
    Management
    Server
    Pods
    more at pod.md
    

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32. Dashboard
    show: FE
    Labels
    ● Metadata with semantic meaning
    ● Membership identifier
    ➔ Allow for intent of many users (e.g. dashboards)
    ➔ Build higher level systems …
    Behavior Benefits
    Pod
    Pod
    frontend
    Pod
    frontend
    Pod Pod
    FE BI, FE v2
    Dashboard
    show: v2
    more at labels.md
    

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33. Replication Controllers
    Behavior Benefits
    Replication
    Controller
    #Pods → 2
    label selector: v1
    Pod
    Pod
    frontend
    Pod
    frontend
    Pod Pod
    v1 v1
    Replication
    Controller
    #Pods → 1
    label selector: v2
    v2
    more at rc.md
    ● Keeps Pods running
    ● Gives direct control of Pod #s
    ➔ Restarts Pods, desired state
    ➔ Fine-grained control for scaling
    

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34. Pod
    Services
    Behavior Benefits
    Pod
    FE FE
    Pod
    FE
    Service
    label selector: Front End
    more at services.md
    ➔ Clients shielded from implementation details
    ➔ Independently control each, build for resiliency
    ● Stable address
    ● Decoupled from Controllers
    

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35. Section Slide Template Option 2
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    Running a Kubernetes Service
    Steer me ship captain!
    

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36. #pyconapac
    plus.google.com/+IanLewis-hoge
    twitter.com/IanMLewis
    Thank you!
    

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