What's Next for Kubernetes

Google Cloud NEXT 2021

In the beginning, Kubernetes aimed to provide users around the world with the tools to run their applications at scale. Google and the Kubernetes community created a shared vision for a platform with the flexibility to grow and shift, serving the needs of many different business types. While engineers work within the contributor community to develop new capabilities, Google Kubernetes Engine (GKE) has grown accordingly in the areas of multi-cluster deployments, improvements to support batch AI, machine learning workloads, and much more. Watch and learn about the latest features coming to the Kubernetes project that can help scale operations.

https://www.youtube.com/watch?v=yV6njtx9fXM

Transcript

1. What's next in
   Kubernetes
   Bob Killen
   Program Manager, Google Cloud
   

   View Slide

2. Bob Killen
   Program Manager,
   Google Cloud
   .
   

   View Slide

3. Building the
   Foundation
   

   View Slide

4. June
   Kubernetes
   announced and
   open sourced at
   Dockercon
   2014 2015 2019
   2016 2018 2020 2021
   July
   Kubernetes 1.0
   Released &
   donated to the
   CNCF
   August
   GKE launched as first
   commercial
   Kubernetes offering
   January
   Core Workloads go
   GA in 1.9 Release
   March
   Kubernetes is the
   first project to
   graduate to stable in
   the CNCF
   July
   Google Cloud
   Services Platform
   launched
   April
   Google
   Anthos
   Launched
   September
   Custom Resources
   go GA in the 1.16
   Release
   August
   Kubernetes support
   window extended
   to 1 year in the 1.19
   release
   

   View Slide

5. Why multi-cluster?
   Security
   Maximize security by restricting
   access at the cluster level and
   only advertise select services
   across clusters.
   Resiliency
   Ensure application and service
   availability by spreading the
   load across multiple clusters.
   Scalability
   Scale components or burst to
   the cloud to meet the demands
   of your application.
   Latency
   Deploy your apps globally to
   minimize latency and improving
   the user experience.
   

   View Slide

6. Clusters are the
   new Pod
   

   View Slide

7. Current state
   us-west
   us-east
   API Gateway
   API Gateway
   Business Logic
   Business Logic
   Cache
   Database
   Load Balancer
   Load Balancer
   Load Balancer
   Global
   Load Balancer
   Multi-Cluster systems are complex.
   

   View Slide

8. Multi-cluster services
   us-west
   Multi-Cluster
   Gateway
   us-east
   API Gateway
   API Gateway
   Business Logic
   Business Logic
   Cache
   Database
   New API that addresses the complexities of
   cross-cluster networking and service discovery.
   

   View Slide

9. Gateway API
   us-west
   Multi-Cluster
   Gateway
   us-east
   Service
   Next generation of Ingress management
   designed to support both multi-tenant and
   multi-cluster use cases.
   - matches:
   - path:
   type: Prefix
   value: /store
   - matches:
   - path:
   type: Prefix
   value: /store
   - matches:
   - path:
   type: Prefix
   value: /admin
   Web Server
   Service Web Server
   Web Server
   Service
   

   View Slide

10. One GKE: Two modes
    Standard
    ● Configuration flexibility
    ● No security restrictions
    ● Pay by the node
    Autopilot
    ● Managed node configuration
    ● Greater default security posture
    ● Pay by the pod
    GKE (us-east)
    GKE (us-west)
    Standard Cluster
    GKE
    Standard Cluster
    GKE
    Autopilot Cluster
    GKE
    Autopilot Cluster
    GKE
    Multi-Cluster
    Gateway
    Multi-Cluster Services
    

    View Slide

11. What’s next for
    AI/ML and batch
    

    View Slide

12. Why is it so hard?
    Scheduling
    Batch and AI/ML workloads have
    complex scheduling requirements that
    clash with the default Kubernetes
    scheduler and resource types.
    Scalability
    Batch and AI/ML workloads can have
    hundreds of thousands of tasks and
    require both large singular clusters and
    the capability to burst.
    Performance
    Requires a highly optimized underlying
    system, access to specialty hardware
    and a tuned backend to handle the high
    throughput requests.
    

    View Slide

13. Work queues
    data-0
    data-1
    data-2
    data-N
    Job - dproc
    Pod
    dproc-5rwd7
    GCS Bucket
    Pub/Sub
    External system
    required to keep
    track of work queue
    Pod
    dproc-z3e25
    Pod
    dproc-q26l4
    Pod
    dproc-l6d9a
    

    View Slide

14. Reduced complexity: Indexed Job
    data-0
    data-1
    data-2
    data-N
    Job - dproc
    Pod
    dproc-0
    GCS Bucket
    Pod
    dproc-1
    Pod
    dproc-2
    Pod
    dproc-N
    New Job completion mode: Indexed
    ● Built in method to partition work
    ● Consistent Pod Hostname
    ● Job Index exposed to Pod for easy integration
    

    View Slide

15. ● Scheduler framework
    ● Suspended jobs
    ● API priority and fairness
    Other improvements for batch workloads
    

    View Slide

16. Kubernetes is Foundational
    Kubernetes is Extensible
    Kubernetes is Mature
    Kubernetes is...
    ✔
    ✔
    ✔
    

    View Slide

17. ✔
    ✔
    ✔
    Easy?
    Kubernetes is Foundational
    Kubernetes is Extensible
    Kubernetes is Mature
    Kubernetes is...
    

    View Slide

18. ✔
    ✔
    ✔
    Getting
    easier
    every day
    Kubernetes is Foundational
    Kubernetes is Extensible
    Kubernetes is Mature
    Kubernetes is...
    

    View Slide

19. ● Kubernetes Essentials from Google Cloud
    ● Learn Kubernetes with Google
    ● Google Open Source Live
    ● Hybrid and multi-cloud: Anthos and Google
    Kubernetes Engine
    Learn more
    

    View Slide

20. Thank you
    

    View Slide