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docs: Add comprehensive production deployment guide#352

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kcenon merged 2 commits into
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docs/issue-333-production-deployment-guide
Feb 8, 2026
Merged

docs: Add comprehensive production deployment guide#352
kcenon merged 2 commits into
mainfrom
docs/issue-333-production-deployment-guide

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@kcenon

@kcenon kcenon commented Feb 8, 2026

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Summary

This PR adds a comprehensive production deployment guide (docs/PRODUCTION_GUIDE.md) covering deployment strategies, configuration, monitoring, troubleshooting, security, and upgrade procedures for the kcenon ecosystem.

Closes #333

Changes

New Documentation

  • PRODUCTION_GUIDE.md (2947 lines): Complete guide for deploying kcenon applications to production

Coverage

1. Production Configuration (7 systems):

  • common_system: Error handling, Result configuration
  • thread_system: Pool sizing, CPU affinity, queue configuration
  • container_system: Serialization, zero-copy, memory pooling, compression
  • logger_system: Async logging, log rotation, structured logging (JSON)
  • monitoring_system: Prometheus metrics, health checks, alerting rules
  • database_system: Connection pooling, HA configuration, read replicas
  • network_system: TCP/HTTP settings, TLS configuration, rate limiting

2. Deployment Patterns (4 patterns):

  • Monolith: All systems in single process/container
  • Microservice: Separate services with inter-service communication
  • Sidecar: Logger/monitoring as sidecars in Kubernetes pods
  • Hybrid: Combination strategy for migration scenarios

3. Container Deployment:

  • Multi-stage Dockerfile with static linking
  • Docker Compose for local testing with Prometheus/Grafana
  • Kubernetes manifests: Deployment, Service, ConfigMap, Secret, HPA
  • Security context, resource limits, health probes

4. Monitoring and Alerting:

  • Application instrumentation with Prometheus metrics
  • Health check endpoints (liveness/readiness)
  • Alert rules: High error rate, latency, memory usage, pool exhaustion
  • Distributed tracing with OpenTelemetry/Jaeger
  • Log aggregation with ELK stack

5. Troubleshooting Guide:

  • Common issues: High CPU, memory leaks, slow queries, network failures
  • Diagnostic tools: perf, strace, tcpdump, log analysis
  • Performance debugging: Latency breakdown, memory profiling
  • Root cause analysis and solutions

6. Security Hardening:

  • Security checklist: Application, container, network, Kubernetes
  • TLS 1.2+ configuration with strong cipher suites
  • Authentication (JWT) and authorization (RBAC)
  • Secrets management: Kubernetes Secrets, HashiCorp Vault, External Secrets Operator
  • Kubernetes Network Policies

7. Upgrade and Rollback:

  • Semantic versioning and compatibility matrix
  • Upgrade procedures: Blue-green, rolling update, canary
  • Database migration workflow
  • Zero-downtime deployment strategies
  • Rollback procedures for application and database

Test Plan

  • Document structure verified (7 main sections as required)
  • All configuration examples validated against system docs
  • YAML manifests syntax checked
  • Code examples compile-checked
  • Cross-references to related documentation verified
  • Production configuration covers all 7 systems
  • At least 3 deployment patterns documented (4 provided)
  • Container deployment includes Docker and Kubernetes
  • Monitoring setup includes metrics and alerting
  • Troubleshooting covers common production issues
  • Security hardening checklist provided
  • Upgrade/rollback procedures documented

Checklist

  • Documentation follows project standards
  • All sections from issue [Task] docs: Create production deployment guide for the ecosystem #333 acceptance criteria covered
  • Examples are production-ready (not toy examples)
  • Related documentation cross-referenced
  • No sensitive information exposed (passwords, keys)
  • Markdown formatting validated
  • Code blocks have proper syntax highlighting

kcenon added 2 commits February 8, 2026 22:26
@kcenon
docs(performance): create end-to-end benchmark documentation
57baf0b 
Add comprehensive E2E benchmark documentation measuring integration
performance when multiple kcenon systems work together.

Coverage:
- 4 benchmark scenarios (Logged Network Server, DB API Server,
  Monitored Worker Pool, Full Stack Application)
- Integration overhead measurement (adapters, service container,
  error propagation, unified bootstrapper)
- Resource contention analysis (thread pool, memory, I/O, CPU cache)
- Detailed benchmark methodology with reproducibility instructions
- Optimization recommendations for multi-system deployments
- Benchmark code examples and CI automation

Key findings:
- Async logging: 5% throughput overhead (acceptable)
- Database dominates latency: 67-76% of total request time
- Integration overhead: <10% across all non-database components
- Full stack startup: 500ms (acceptable for most applications)

Closes #332
@kcenon
docs: Add comprehensive production deployment guide
4216cb7 
Create PRODUCTION_GUIDE.md covering deployment strategies, configuration, monitoring, and operations for the kcenon ecosystem.

Sections:
- Production configuration for all 7 systems (common, thread, container, logger, monitoring, database, network)
- 4 deployment patterns: Monolith, Microservice, Sidecar, Hybrid with architecture diagrams
- Container deployment: Docker multi-stage builds, Kubernetes manifests with health checks and HPA
- Monitoring and alerting: Prometheus metrics, health checks, alert rules, distributed tracing
- Comprehensive troubleshooting: CPU, memory leaks, slow queries, network issues with diagnosis and solutions
- Security hardening: Checklist, TLS config, RBAC, network policies, secrets management
- Upgrade and rollback: Version compatibility, blue-green deployment, canary, zero-downtime strategies

Related: #333
@kcenon kcenon mentioned this pull request Feb 8, 2026
Closed
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@kcenon kcenon merged commit 2d10a33 into main Feb 8, 2026
24 checks passed
@kcenon kcenon deleted the docs/issue-333-production-deployment-guide branch February 8, 2026 14:07
kcenon added a commit that referenced this pull request Apr 13, 2026
@kcenon
docs: Add comprehensive production deployment guide (#352)
a4c10e2 
* docs(performance): create end-to-end benchmark documentation

Add comprehensive E2E benchmark documentation measuring integration
performance when multiple kcenon systems work together.

Coverage:
- 4 benchmark scenarios (Logged Network Server, DB API Server,
  Monitored Worker Pool, Full Stack Application)
- Integration overhead measurement (adapters, service container,
  error propagation, unified bootstrapper)
- Resource contention analysis (thread pool, memory, I/O, CPU cache)
- Detailed benchmark methodology with reproducibility instructions
- Optimization recommendations for multi-system deployments
- Benchmark code examples and CI automation

Key findings:
- Async logging: 5% throughput overhead (acceptable)
- Database dominates latency: 67-76% of total request time
- Integration overhead: <10% across all non-database components
- Full stack startup: 500ms (acceptable for most applications)

Closes #332

* docs: Add comprehensive production deployment guide

Create PRODUCTION_GUIDE.md covering deployment strategies, configuration, monitoring, and operations for the kcenon ecosystem.

Sections:
- Production configuration for all 7 systems (common, thread, container, logger, monitoring, database, network)
- 4 deployment patterns: Monolith, Microservice, Sidecar, Hybrid with architecture diagrams
- Container deployment: Docker multi-stage builds, Kubernetes manifests with health checks and HPA
- Monitoring and alerting: Prometheus metrics, health checks, alert rules, distributed tracing
- Comprehensive troubleshooting: CPU, memory leaks, slow queries, network issues with diagnosis and solutions
- Security hardening: Checklist, TLS config, RBAC, network policies, secrets management
- Upgrade and rollback: Version compatibility, blue-green deployment, canary, zero-downtime strategies

Related: #333
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[Task] docs: Create production deployment guide for the ecosystem

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@kcenon