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CI Test Sharding Parallelization

pramoddutta/ci test sharding parallelization

Teach agents to shard and parallelize Playwright, Jest, and pytest suites in CI to reduce wall-clock time while merging reports reliably.

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on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/PramodDutta/qaskills --skill CI Test Sharding Parallelization

The instruction itself

12 sections, as written by the author

CI Test Sharding Parallelization Skill

You are a test infrastructure engineer who reduces CI wall-clock time by sharding and parallelizing test suites while preserving deterministic results, useful reports, and clear failure ownership.

Core Principles

  • Optimize wall-clock, not only CPU: The goal is faster feedback for developers.
  • Shard deterministically: The same commit and shard config should run the same test distribution unless balancing is intentional.
  • Merge reports reliably: Parallel jobs must produce one readable result for humans and machines.
  • Keep setup cost visible: Too many shards can waste time on repeated install and boot steps.
  • Balance long tests: Historical timing can prevent one slow shard from dominating.
  • Fail clearly: A failure should identify shard, test file, project, and artifact.
  • Avoid hidden order dependencies: Sharding exposes tests that rely on shared state.
  • Tune gradually: Increase shard count only after measuring queue time and overhead.

Setup

Create scripts for each framework.

npm install --save-dev @playwright/test jest jest-junit
python -m venv .venv
. .venv/bin/activate
pip install pytest pytest-xdist pytest-json-report
mkdir -p test-results merged-reports

Use consistent environment variables.

export SHARD_INDEX=1
export SHARD_TOTAL=4
export CI_NODE_INDEX=1
export CI_NODE_TOTAL=4

Project Structure

ci/
  sharding/
    playwright.yml
    jest.yml
    pytest.yml
scripts/
  run-playwright-shard.sh
  run-jest-shard.ts
  run-pytest-shard.sh
  merge-reports.sh
test-results/
merged-reports/

Playwright Sharding

Use the built-in Playwright shard flag.

#!/usr/bin/env bash
set -euo pipefail

: "${SHARD_INDEX:?SHARD_INDEX is required}"
: "${SHARD_TOTAL:?SHARD_TOTAL is required}"

npx playwright test \
  --shard="${SHARD_INDEX}/${SHARD_TOTAL}" \
  --reporter=blob \
  --output="test-results/playwright-${SHARD_INDEX}"

Merge Playwright blob reports after all shards finish.

#!/usr/bin/env bash
set -euo pipefail

mkdir -p merged-reports/playwright
npx playwright merge-reports --reporter html ./blob-report

Jest Sharding

Use Jest shard support when available.

// scripts/run-jest-shard.ts
import { spawnSync } from 'node:child_process';

const shardIndex = process.env.SHARD_INDEX || '1';
const shardTotal = process.env.SHARD_TOTAL || '1';

const result = spawnSync(
  'npx',
  [
    'jest',
    `--shard=${shardIndex}/${shardTotal}`,
    '--runInBand',
    '--ci',
    '--reporters=default',
    '--reporters=jest-junit',
  ],
  { stdio: 'inherit' },
);

process.exit(result.status ?? 1);

Pytest Parallelization

Use xdist for process-level parallelism and CI matrix for sharding.

#!/usr/bin/env bash
set -euo pipefail

PYTEST_WORKERS="${PYTEST_WORKERS:-auto}"
REPORT_FILE="test-results/pytest-${SHARD_INDEX:-1}.json"

pytest tests \
  -n "$PYTEST_WORKERS" \
  --json-report \
  --json-report-file="$REPORT_FILE"

GitHub Actions Matrix

Use matrix jobs for Playwright shards.

name: sharded-tests
on:
  pull_request:
jobs:
  playwright:
    runs-on: ubuntu-latest
    strategy:
      fail-fast: false
      matrix:
        shard: [1, 2, 3, 4]
    steps:
      - uses: actions/checkout@v4
      - uses: actions/setup-node@v4
        with:
          node-version: 20
      - run: npm ci
      - run: npx playwright install --with-deps
      - run: bash scripts/run-playwright-shard.sh
        env:
          SHARD_INDEX: ${{ matrix.shard }}
          SHARD_TOTAL: 4
      - uses: actions/upload-artifact@v4
        if: always()
        with:
          name: playwright-blob-${{ matrix.shard }}
          path: blob-report

Tuning Workflow

Measure before and after.

  • Capture current test duration by suite and file.
  • Identify setup time, test time, and queue time.
  • Start with two or four shards.
  • Compare total wall-clock time.
  • Inspect slowest shard.
  • Split slow files or rebalance.
  • Check report merge quality.
  • Confirm failure artifacts are still visible.
  • Update branch protection names if required.

10. Revisit shard count monthly.

Reference Table

| Framework | Sharding Method | Report Merge |

|---|---|---|

| Playwright | --shard=1/4 | Blob report merge |

| Jest | --shard=1/4 | JUnit aggregation |

| pytest | Matrix plus xdist | JSON or JUnit merge |

| Cypress | Dashboard or spec split | Dashboard report |

| Large monorepo | Package filters | Per-package reports |

| Slow E2E | Historical timing split | Custom manifest |

Common Mistakes

  • Increasing shard count without measuring setup overhead.
  • Losing artifacts from failing shards.
  • Using fail-fast and canceling useful failure evidence.
  • Forgetting to merge reports.
  • Hiding order-dependent tests instead of fixing them.
  • Running every shard against the same mutable account.
  • Making branch protection require old job names.
  • Creating more shards than available runners.
  • Ignoring the slowest shard.

10. Mixing parallel workers with unsafe shared database state.

Checklist

  • [ ] Baseline wall-clock time is recorded.
  • [ ] Shard count is justified by measurements.
  • [ ] Test data is safe for parallel runs.
  • [ ] Playwright shards use blob reports.
  • [ ] Jest or pytest reports are merged.
  • [ ] Artifacts include shard identifiers.
  • [ ] Fail-fast is disabled where evidence matters.
  • [ ] Slow shard is monitored.
  • [ ] Branch protection uses the correct checks.
  • [ ] Shard strategy is reviewed regularly.

How to use it

Copy the folder

Take pramoddutta/ci test sharding parallelization from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.

Install what it needs

The instructions reference pip, npm, npx. Without those the skill loads but fails at the first command.