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Performance· Case study 11

Distributed load testing & performance benchmarking

A containerized k6 load-testing harness on Kubernetes that replays realistic dashboard query traffic against Rill and its OLAP backends, plus benchmarks for comparing engines, schemas, and cluster sizes.

Before go-live

every engine, schema, and cluster size tested

Architecture at a glance

  1. k6 scenarios
  2. Helm on Kubernetes
  3. Rill + OLAP
  4. Query benchmarks

01 The problem

Customer go-lives and upgrades needed evidence that dashboards would stay fast under real traffic, before real users arrived.

02 What I built

  1. 1A containerized k6 load-testing harness deployed on Kubernetes with Helm.
  2. 2Replays of realistic dashboard query traffic against Rill and its OLAP backends.
  3. 3A benchmarking project that records query metrics for comparing engines, schemas, and cluster sizes.

03 Impact

Sizing and schema decisions before go-lives and upgrades are based on measured query performance instead of guesses.

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08 · Contact

Let’s build something that holds up in production.

If something here resonates, whether it’s a data problem, an idea, or a conversation worth having, I’d love to hear from you. The fastest way to reach me is a message on LinkedIn.

Message me on LinkedIn Résumé (PDF)

Good reasons to reach out

  • Data platform help

    ClickHouse or Druid performance, Kubernetes operations, migrations, and cost reviews.

  • Collaboration

    Open-source work, writing, talks, or comparing notes on a hard data problem.

  • Just to talk shop

    Real-time analytics, AdTech data, MCP and agent tooling, or life as an FDE.

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