Problems / Kubernetes and containers, medium

A rolling update at the busy hour

To finish deploys quickly, the update strategy lets half the pods be unavailable and adds none extra (maxUnavailable 50%, maxSurge 0). A release goes out at 30 s, at 170 requests a second.

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Your goals

Keep success at 99% or more and p99 under 800 ms through the deploy.

Test cases

Like a coding problem, a solution has to pass every case, not just the one it was built for. Submit in the lab runs all 5; 2 of them are hidden until then.

  1. As given. The problem’s own traffic, scheduled failures and seed.
  2. Peak hour. 25% more traffic than the problem states, with the same failures.
  3. A slow dependency. The main data store or model answers twice as slowly for part of the run.

The traffic

170 requests a second for 150 seconds: 100% api (reads).

The system

What each component does in this design, and what calls it. The simulator mimics each one from these settings.

ComponentIts job hereSettings
Load balancerLoad balancerTraffic enters here.Calls API (pods).Layer 4 balancers route by IP and port; layer 7 balancers read HTTP and can route by path or header.–
API (pods)Container platformLoad balancer forwards to it.Calls Postgres.Kubernetes places pods on nodes by their CPU and memory requests, and only replaces a lost node's pods after about 5 minutes.20 slots
PostgresSQL databaseAPI (pods) calls it.Postgres runs one process per connection, which is why poolers like PgBouncer sit in front of busy databases.32 vCPU · 300 connections

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