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ContinuousIntegration:ImplementationGuide

lastmod 2025-12-12created 2025-12-1124 edits

CI/CD Platform Implementation Guide

A CI/CD platform is a system that automates code integration, testing, building, and deployment in the software development life cycle.

This page covers the technical requirements, architecture design, and implementation procedure for building your own CI/CD platform similar to Drone CI.

Pipeline

Gitlab_cicd_pipeline_infograph.png

+ See GitLab CI#Pipeline

In the case of Drone CI:

Drone_CI_-_architecture_diagram.png

Minimum requirements

To cut to the chase ...

Set it up, then use the API.

Developing

At minimum, a WebHook Server/Client for the VCS is needed

CI PIPELINE

An isolated build environment is needed:

A DNS server is needed to run custom scripts: (things like sudo apt install ... access the debian repo. -> the dns resolver does the quering)

CD PIPELINE

Continuous delivery vs Continuous deployment: which of the two is the goal?

Build Agent (Runner)

The Runner that performs the actual build jobs:

Runner execution Flow

  1. Receive event - a push/PR event fires from the Git repository via a Korean: 웹훅
  2. Load pipeline - fetch the yml (or similar file) from the repository
  3. Parse and validate - validate the pipeline definition (e.g. JSON Schema) and split it into jobs
  4. Load environment and secrets - requires Key management such as vault. Load Environment Variables definitions.
  5. Queue jobs - add each job to a message queue (Kafka, redis, RDBMS, etc ...)
  6. Assign jobs - the scheduler finds an idle runner and assigns the job (Event scheduler)
    • Matrix builds possible? - concurrent builds/tests across multiple environment/version combinations
  7. Load cache - if caches from previous jobs exist, load them.
  8. Run container - the runner creates an isolated container and runs the build script
    • What about the dependency repository registry? - a mirror server is possible
    • What about integration with the build plugin marketplace? - most have no mirror server - can pre-cache in a container registry
  9. Korean: 로그 스트리밍 - send logs to the server in real time (WebSocket/gRPC etc ...)
  10. Collect results - collect build success/failure status, artifacts, and test results (S3, minio, etc ...)
  11. Send notifications - notify build results via Korean: 이메일, Slack, etc.

In GitLab

GitLab_Runner_GitLab_Docs_-_Runner_execution_flow.png

Implementation steps

Step 1: Core architecture design

  • Design the Server-Agent distributed architecture
  • Define a gRPC-based communication protocol
  • Design the database schema (pipelines, builds, logs, etc.)

Step 2: Basic Server implementation

  • Basic skeleton of the HTTP API server (REST API)
  • User authentication/authorization system
  • Webhook receiving endpoint for repository (Git) integration
  • Database integration (PostgreSQL/SQLite)

Step 3: Pipeline parser implementation

  • YAML pipeline file parser
  • Define and validate Pipeline syntax
  • Parse the Step/Stage structure
  • Logic for handling environment variables and secrets

Step 4: Basic Runner(Agent) implementation

  • Agent registration and authentication mechanism
  • gRPC communication client for the Server
  • Job queue polling and receiving
  • Heartbeat and status reporting

Step 5: Container execution engine

  • Docker API integration
  • Container creation, execution, and deletion
  • Volume mounts and network configuration
  • Log streaming implementation

Step 6: Job scheduling and queue system

  • Job queue management (Redis/memory-based)
  • Agent load balancing and job assignment
  • Priority handling
  • Concurrent execution limits and resource management

Step 7: Git repository integration

  • GitHub/GitLab/Gitea Webhook handling
  • OAuth authentication integration
  • Repository clone and checkout logic
  • Commit status update API

Step 8: Log collection and storage

  • Real-time log streaming (WebSocket/SSE)
  • Persistent log storage (file/DB)
  • Log search and filtering
  • Log retention policy

Step 9: Secret management

  • Encrypted secret storage
  • Repository/organization/global secret hierarchy
  • Runtime secret injection
  • Secret masking (in logs)

Step 10: Web UI implementation

  • Dashboard (build list, status)
  • Pipeline detail view
  • Real-time log viewer
  • Settings management page

Step 11: Cache system

  • Dependency caching mechanism
  • Volume-based cache storage
  • Cache key management and invalidation
  • S3/MinIO integration (optional)

Step 12: Plugin/extension system

  • Define the plugin interface
  • Custom step execution engine
  • Marketplace or registry (optional)

Step 13: Monitoring and metrics

  • Expose Prometheus metrics
  • Statistics such as build success rate and execution time
  • Agent status monitoring
  • Notification system integration

Step 14: Advanced features

  • Matrix builds (parallel execution)
  • Conditional execution (when conditions)
  • Manual approval steps
  • Artifact storage and deployment

Step 15: Performance optimization and stabilization

  • Concurrency and parallel processing optimization
  • Database query optimization
  • Error handling and retry logic
  • Load testing and tuning

See also

author Zer0 sitemap