Developer Knowledge Base

Knowledge locked in people's heads is lost when they leave, unavailable when they're busy, and forces repeated explanations. A developer knowledge base captures decisions, patterns, troubleshooting guides, and institutional wisdom, making the team more resilient and efficient.

Knowledge Base Value

Knowledge Base Structure

Recommended Organization

DEVELOPER KNOWLEDGE BASE STRUCTURE
══════════════════════════════════

📁 GETTING STARTED
├── README - Start here
├── Quick start guide
├── Environment setup
├── First contribution
└── Who to ask for what

📁 ARCHITECTURE
├── System overview
├── Architecture Decision Records (ADRs)
├── Service map
├── Data flows
├── Technology choices
└── Design patterns

📁 DEVELOPMENT
├── Coding standards
├── Git workflow
├── Code review guidelines
├── Testing strategy
├── CI/CD pipeline
└── Development environment

📁 OPERATIONS
├── Deployment guide
├── Monitoring and alerts
├── Incident response
├── Runbooks
├── On-call procedures
└── Infrastructure overview

📁 TROUBLESHOOTING
├── Common issues
├── Debug guides
├── FAQ
├── Error messages explained
└── Environment problems

📁 REFERENCE
├── Glossary
├── Team contacts
├── External services
├── Vendor accounts
└── Resource links

Key Content Types

Architecture Decision Records

ARCHITECTURE DECISION RECORD TEMPLATE
═════════════════════════════════════

# ADR-001: Use PostgreSQL for Primary Database

## Status
Accepted (2024-01-15)

## Context
We need to choose a primary database for our application.
Requirements include:
- Strong consistency
- Complex queries
- JSON support
- Proven reliability

## Decision
Use PostgreSQL 15 as our primary database.

## Consequences

Positive:
- Strong ecosystem and tooling
- JSON support for flexible schemas
- Proven at scale
- Team familiarity

Negative:
- Not ideal for time-series (future consideration)
- Horizontal scaling more complex than NoSQL

## Alternatives Considered
- MySQL: Less JSON support
- MongoDB: Eventual consistency concerns
- CockroachDB: Overkill for current scale

## Related
- ADR-015: Time-series data solution
- Architecture overview doc

Troubleshooting Guides

TROUBLESHOOTING GUIDE TEMPLATE
══════════════════════════════

# Database Connection Issues

## Symptoms
- Error: "Connection refused"
- Error: "Too many connections"
- Slow query response times

## Quick Checks

### Connection Refused
1. Is PostgreSQL running?
   docker ps | grep postgres
   
2. Can you connect locally?
   psql -h localhost -U postgres
   
3. Environment variables set?
   echo $DATABASE_URL

### Too Many Connections
1. Check connection count:
   SELECT count(*) FROM pg_stat_activity;
   
2. Kill idle connections:
   See "Reset connections" runbook

3. Check for connection leaks in code

### Slow Queries
1. Enable query logging:
   SET log_statement = 'all';
   
2. Use EXPLAIN ANALYZE:
   EXPLAIN ANALYZE SELECT ...
   
3. Check common slow queries doc

## Escalation
If none of the above works:
1. Post in #db-help with error details
2. Page on-call DBA if production
3. See incident response runbook

Runbooks

RUNBOOK TEMPLATE
════════════════

# Deploy Hotfix to Production

## Purpose
Emergency deployment of critical fix outside normal release.

## Prerequisites
- [ ] Fix merged to main
- [ ] Tests passing
- [ ] Two approvals on PR
- [ ] On-call engineer available
- [ ] Incident channel open

## Steps

### 1. Notify Team (2 min)
Post in #engineering:
"🚨 Starting hotfix deploy: [brief description]"

### 2. Create Release (5 min)
git checkout main
git pull origin main
git tag -a hotfix-YYYY-MM-DD-description
git push origin hotfix-YYYY-MM-DD-description

### 3. Deploy (10 min)
# Trigger deploy
./scripts/deploy-production.sh

# Monitor logs
./scripts/tail-production-logs.sh

### 4. Verify (5 min)
- [ ] Health check passing
- [ ] Affected feature working
- [ ] No error spike in monitoring
- [ ] Confirm with reporter

### 5. Notify Complete
Post in #engineering:
"✅ Hotfix deployed and verified"

## Rollback
If issues occur:
./scripts/rollback-production.sh

## Post-Deployment
- [ ] Update incident timeline
- [ ] Schedule post-mortem if incident
- [ ] Update changelog

Building the Knowledge Base

Initial Setup

KNOWLEDGE BASE SETUP STEPS
══════════════════════════

STEP 1: Choose Platform
─────────────────────────────────────
Options:
├── GitScrum NoteVault (integrated)
├── GitHub/GitLab Wiki (close to code)
├── Notion (flexible, searchable)
├── Docs as code (in repository)
└── Confluence (enterprise standard)

Consider:
├── Search quality
├── Edit ease
├── Version history
├── Access control
├── Integration with tools

STEP 2: Create Structure
─────────────────────────────────────
Start with 5 core sections:
├── Getting Started
├── Architecture  
├── Development
├── Operations
├── Troubleshooting

STEP 3: Seed Initial Content
─────────────────────────────────────
Most valuable first:
├── Environment setup (blocks new hires)
├── Deployment process (critical path)
├── Common issues FAQ (saves time)
├── Key architecture decisions (context)
└── Team contacts (who to ask)

STEP 4: Establish Workflow
─────────────────────────────────────
├── Fix issue → Update docs
├── Answer question twice → Document it
├── New hire friction → Document solution
├── Quarterly review of sections
└── Assign section owners

Keeping It Current

KNOWLEDGE BASE MAINTENANCE
══════════════════════════

CONTINUOUS:
├── Fix issue → Update relevant doc
├── Answer question → Add to FAQ
├── Find outdated info → Update it
├── New tool/process → Document it
└── Someone leaves → Capture knowledge

WEEKLY:
├── Review recently added content
├── Check for broken links
├── Respond to doc feedback
└── Update recently changed areas

MONTHLY:
├── Review search analytics
├── Identify gaps from questions
├── Archive obsolete content
├── Check section ownership
└── Onboarding feedback review

QUARTERLY:
├── Full section audit
├── Remove stale content
├── Update screenshots/examples
├── Refresh architecture docs
└── Knowledge sharing session

GitScrum NoteVault Integration

Using NoteVault

NOTEVAULT FOR KNOWLEDGE BASE
════════════════════════════

STRUCTURE:
├── Create spaces for each section
├── Link notes to tasks/projects
├── Tag for discoverability
└── Pin important notes

LINKING:
├── Task → Related documentation
├── Project → Architecture notes
├── Incidents → Runbooks
└── Decisions → ADRs

SEARCH:
├── Full-text search across notes
├── Tag-based filtering
├── Recent activity
└── Linked content discovery

WORKFLOW:
├── Create during work
├── Update after incidents
├── Reference in tasks
├── Review in onboarding

Best Practices

For Knowledge Bases

1. Document decisions, not just facts — Why matters
2. Keep it close to code — Easy to update
3. Update continuously — Not big rewrites
4. Make it searchable — Discovery is key
5. Assign owners — Someone responsible

Anti-Patterns

KNOWLEDGE BASE MISTAKES:
✗ Writing everything up front
✗ Never updating
✗ Too formal/polished requirements
✗ Buried in hard-to-find location
✗ No search capability
✗ No ownership
✗ Duplicating across tools
✗ Information without context

Related Solutions

• Documenting project decisions in NoteVault
• Documenting architectural decisions
• Building knowledge-sharing teams