How does Alibaba ensure performance of system components in a 10,000-node Kubernetes cluster?

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The production environment of Alibaba consists of more than 10,000 containerized applications, with the entire network of Alibaba being a massive system using millions of containers running on more than 100,000 hosts. This is how they run it. By

When running common loads in the simulated cluster, the team encountered extremely high latency, up to 10s in fact, for some basic operations such as pod scheduling. Moreover, the cluster was also unstable.

The article then describes, how:

  • Storage capacity of etcd was improved by separating indexes and data and sharding data. The performance of etcd in storing massive data was greatly improved by optimizing the block allocation algorithm of the bbolt db storage engine at the bottom layer of etcd. Last, the system architecture was simplified by building large-scale Kubernetes clusters based on a single etcd cluster
  • List performance bottleneck was removed to enable the stability of operation of 10,000-node Kubernetes clusters through a series of enhancements, such as Kubernetes lightweight heartbeats, improved load balancing among API servers in high-availability (HA) clusters, List-Watch bookmark, indexing, and caching
  • Hot standby mode greatly reduced the service interruption time during active/standby failover on controllers and schedulers. This also improved cluster availability
  • Performance of Alibaba-developed schedulers was effectively optimized through equivalence classes and relaxed randomization

Excellent read, well worth your time!

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Tags devops kubernetes cloud containers software-architecture