---
title: "Check for leaks after this test cleans up"
description: "Run the leak check at the end of the test, where it inspects this test's own resources."
url: https://starsling.dev/ci-playbooks/techniques/check-cleanup-at-test-end
canonicalUrl: https://starsling.dev/ci-playbooks/techniques/check-cleanup-at-test-end
---

# Check for leaks after this test cleans up

Run the leak check at the end of the test, where it inspects this test's own resources.

## How to choose an approach

This technique currently has one documented company example. Validate its prerequisites, tradeoffs and original CI environment against your repository before adapting it.

- **[Uber](https://starsling.dev/ci-playbooks/uber#check-cleanup-at-test-end)**: Use it when A cleanup assertion runs before the test allocates or releases the resources it is meant to inspect. Check before adopting: Understand defer ordering and asynchronous shutdown, and keep a final assertion that still catches an intentional leak.

## Apply this technique

````text
Evaluate and apply this CI technique to my repository: Check for leaks after this test cleans up.

Run the leak check at the end of the test, where it inspects this test's own resources.

Read the technique and its source-backed company examples: https://starsling.dev/ci-playbooks/techniques/check-cleanup-at-test-end.md

Inspect this repository’s CI workflows, build and test commands, dependencies, and recent run timings. Identify where this technique applies and explain the expected benefit using this repository’s evidence.
Measure a baseline from recent comparable runs: elapsed time, queue time, runner minutes and failures where available. If data is unavailable, say what cannot be measured.
Compare relevant company approaches, checking prerequisites, platform differences and tradeoffs. Rank applicable options by evidence, fit and measurable opportunity; do not present company results as predictions for this repo.
Recommend the smallest safe change, show what checks and fallback paths remain, and ASK ME WHICH CHANGE TO APPROVE BEFORE EDITING ANY FILES.
Only after approval, work on a new feature branch, make one reversible change, and open a reviewable pull request. Never merge or push to a default or protected branch.
Keep required checks, test coverage, deployment and release behavior intact. Validate the change and compare equivalent runs where possible; report limitations and what should be monitored after merge.
````

## How Uber used this technique

Read what Uber changed and follow the original sources.

### Uber: Check for leaks after this test cleans up

Cadence moved goleak.VerifyNone from test entry into a deferred call in three election tests, so the check runs after the test body and its cleanup defers and inspects this test's goroutines.

Evidence: Source PR/commit evidence

The author reports that the flaky-test detector fired 5 times in CI from January through April 2026 and ten repeated race-enabled runs passing after the change. ([Source](https://github.com/cadence-workflow/cadence/pull/7969))

Use it when: A cleanup assertion runs before the test allocates or releases the resources it is meant to inspect.

Before applying it: Understand defer ordering and asynchronous shutdown, and keep a final assertion that still catches an intentional leak.

[Read more in the Uber playbook](https://starsling.dev/ci-playbooks/uber#check-cleanup-at-test-end)

[Primary source](https://github.com/cadence-workflow/cadence/pull/7969)

## CI optimization is continuous work.

Apply this technique yourself, or use StarSling Runners for faster GitHub Actions and optional agent-driven optimization PRs, which teams on eligible paid plans can turn on.

[Get self-improving CI](https://starsling.dev/products/runners)

## Related techniques

### [Make unordered results deterministic before comparing](https://starsling.dev/ci-playbooks/techniques/normalize-unordered-results)

Sort values whose order was never guaranteed, so an equivalent result passes on the first run.

1 implementation · 1 company (Uber)

### [Prove a new test is stable before it joins the blocking suite](https://starsling.dev/ci-playbooks/techniques/flakiness-gate-before-blocking)

Run each new end-to-end test many times in a dedicated pipeline, and admit it to the blocking checks only if it stays under a failure threshold.

1 implementation · 1 company (Shopify)

### [Wait for the state transition before asserting](https://starsling.dev/ci-playbooks/techniques/synchronize-assertions)

Synchronize with the event that makes the assertion true, so the test stops needing reruns.

1 implementation · 1 company (Uber)

## Company Playbooks

### [Anthropic](https://starsling.dev/ci-playbooks/anthropic)

Run only affected tests

### [DoorDash](https://starsling.dev/ci-playbooks/doordash)

Run build and test in parallel, sharded across CI agents

### [Linear](https://starsling.dev/ci-playbooks/linear)

Benchmark the same job on faster hardware

### [Mastra](https://starsling.dev/ci-playbooks/mastra)

StarSling runners for the slowest test workflow

### [OpenAI](https://starsling.dev/ci-playbooks/openai)

Rank CI fixes by the minutes they save

### [Ramp](https://starsling.dev/ci-playbooks/ramp)

Move a CPU-bound test suite to a faster CPU

### [Shopify](https://starsling.dev/ci-playbooks/shopify)

Let an agent iterate against one CI metric

### [Spotify](https://starsling.dev/ci-playbooks/spotify)

Build arm64 on native arm64 runners

### [Stripe](https://starsling.dev/ci-playbooks/stripe)

Run only the tests a change can reach

### [Uber](https://starsling.dev/ci-playbooks/uber)

Build the merge-queue speculations most likely to be needed
