DAG Optimization: Sequential Pipeline Bottlenecks and needs-based Parallelism

Problem/Feature Description

A data engineering team's GitLab CI pipeline takes 22 minutes end-to-end. The team lead suspects that independent jobs are running sequentially because of how the stage model was set up, and that switching to DAG-based execution with needs: would cut pipeline time significantly.

Analyze the pipeline below for parallelism opportunities. Identify which jobs are genuinely dependent on each other and which can run in parallel. Produce a DAG-optimized version of the pipeline and document the expected improvement.

Output Specification

Produce:

• An optimized .gitlab-ci.yml using needs: to enable parallel execution where appropriate
• A dag-optimization-report.md that: (1) lists each parallelism opportunity found with the jobs involved, (2) shows the before/after critical path length (in stages), and (3) explains how needs: achieves the parallelism

Input Files

The following file is provided as input.

=============== FILE: inputs/.gitlab-ci.yml =============== stages:

• build
• lint
• test
• security
• package
• deploy

default: image: python:3.11-slim

build: stage: build script: - pip install -r requirements.txt artifacts: paths: - .venv/ expire_in: 1 hour

lint_code: stage: lint script: - pip install flake8 - flake8 src/

lint_types: stage: lint script: - pip install mypy - mypy src/

unit_tests: stage: test script: - pytest tests/unit/ artifacts: reports: junit: unit-test-results.xml

integration_tests: stage: test script: - pytest tests/integration/

sast_scan: stage: security script: - pip install bandit - bandit -r src/

dependency_scan: stage: security script: - pip install safety - safety check

package: stage: package script: - python setup.py bdist_wheel artifacts: paths: - dist/ expire_in: 1 week

deploy: stage: deploy script: - ./deploy.sh rules: - if: '$CI_COMMIT_BRANCH == "main"'