bitwikiorg Example: Technical Investigation
User Request
"Research our current caching strategy and create a technical summary"
Workflow Execution
Step 1: Search for Caching Information
Notion:notion-search
query: "caching strategy architecture"
query_type: "internal"
teamspace_id: "engineering-teamspace-id"
Results Found:
- "System Architecture Overview" (Engineering)
- "Redis Implementation Guide" (Backend Docs)
- "Performance Optimization - Q3 2024" (Engineering)
- "API Caching Decision Record" (Architecture)
Step 2: Fetch Relevant Pages
Notion:notion-fetch
id: "system-architecture-page-url"
Extracted: Current caching architecture uses Redis for API responses, Memcached for session storage.
Notion:notion-fetch
id: "redis-implementation-guide-url"
Extracted: Implementation details, TTL settings, invalidation strategies.
Notion:notion-fetch
id: "api-caching-decision-record-url"
Extracted: Why Redis was chosen over alternatives, trade-offs considered.
Step 3: Synthesize Findings
Key findings identified:
- Two-tier caching: Redis (API responses) + Memcached (sessions)
- TTL strategy: 5 minutes for dynamic data, 1 hour for static
- Invalidation: Event-driven for critical updates
- Performance impact: 75% reduction in database load
- Known issues: Cache stampede on popular endpoints
Step 4: Create Technical Summary
Notion:notion-create-pages
parent: { page_id: "engineering-docs-parent-id" }
pages: [{
properties: {
"title": "Technical Summary: Caching Strategy - Oct 2025"
},
content: "[Structured technical summary using template]"
}]
Output Document
# Technical Summary: Caching Strategy - Oct 2025
## Executive Summary
Our caching infrastructure uses a two-tier approach with Redis for API response caching and Memcached for session management. This strategy has reduced database load by 75% and improved API response times from 200ms to 50ms average.
## Architecture Overview
### Layer 1: API Response Caching (Redis)
**Technology**: Redis 7.0 cluster (3 nodes)
**Purpose**: Cache GET endpoint responses
**TTL Strategy**:
- Dynamic content: 5 minutes
- Static content: 1 hour
- User-specific: 15 minutes
**Source**: <mention-page url="...">System Architecture Overview</mention-page>
### Layer 2: Session Storage (Memcached)
**Technology**: Memcached 1.6
**Purpose**: User session data, temporary state
**TTL**: 24 hours (session lifetime)
## Implementation Details
### Cache Key Format
api:v1:{endpoint}:{params_hash} session:{user_id}:{session_id}
### Invalidation Strategy
- **Event-driven**: Critical data changes trigger immediate invalidation
- **Time-based**: TTL expiration for non-critical data
- **Manual**: Admin tools for emergency cache clear
**Source**: <mention-page url="...">Redis Implementation Guide</mention-page>
## Decision Rationale
### Why Redis for API Caching?
**Pros**:
- Advanced data structures (sorted sets, hashes)
- Built-in TTL with automatic eviction
- Pub/sub for cache invalidation events
- Persistence options for durability
**Cons**:
- Higher memory usage than Memcached
- More complex cluster management
**Decision**: Chosen for flexibility and rich feature set needed for API caching.
**Source**: <mention-page url="...">API Caching Decision Record</mention-page>
### Why Memcached for Sessions?
**Pros**:
- Simpler, lighter weight
- Excellent for key-value storage
- Lower memory footprint
**Cons**:
- No persistence
- Limited data structures
**Decision**: Perfect fit for ephemeral session data where simplicity is valued.
## Performance Impact
| Metric | Before Caching | After Caching | Improvement |
|--------|----------------|---------------|-------------|
| Avg Response Time | 200ms | 50ms | 75% faster |
| Database Load | 100% | 25% | 75% reduction |
| Cache Hit Rate | - | 85% | - |
| Peak RPS Handled | 1,000 | 4,000 | 4x increase |
**Source**: <mention-page url="...">Performance Optimization - Q3 2024</mention-page>
## Known Issues & Limitations
### Cache Stampede
**Issue**: When popular cache entries expire, multiple requests hit database simultaneously
**Mitigation**: Implemented probabilistic early expiration and request coalescing
**Status**: Reduced by 90% but not eliminated
### Stale Data Risk
**Issue**: Cached data can be up to TTL duration stale
**Mitigation**: Event-driven invalidation for critical data paths
**Status**: Acceptable trade-off for performance gains
## Monitoring & Observability
**Metrics tracked**:
- Cache hit/miss rates per endpoint
- Memory usage and eviction rates
- Response time distributions
- Invalidation event frequency
**Tools**: DataDog dashboards, CloudWatch alarms
## Future Considerations
1. **Edge Caching**: Evaluate CDN integration for static assets
2. **Cache Warming**: Pre-populate cache for predictable traffic spikes
3. **Adaptive TTLs**: Adjust TTLs based on data change frequency
4. **Regional Caching**: Multi-region cache replication for global performance
## Related Documentation
- <mention-page url="...">System Architecture Overview</mention-page>
- <mention-page url="...">Redis Implementation Guide</mention-page>
- <mention-page url="...">API Caching Decision Record</mention-page>
- <mention-page url="...">Performance Optimization - Q3 2024</mention-page>
## Appendix: Configuration Examples
### Redis Configuration
```yaml
maxmemory: 8gb
maxmemory-policy: allkeys-lru
tcp-keepalive: 60
Common Cache Operations
# Set with TTL
cache.set(key, value, ttl=300)
# Get with fallback
value = cache.get(key) or fetch_from_db(key)
# Invalidate pattern
cache.delete_pattern("api:v1:users:*")
## Key Success Factors
1. **Multiple source integration**: Combined architecture docs, implementation guides, and decision records
2. **Technical depth**: Included configuration, code examples, metrics
3. **Decision context**: Explained why choices were made, not just what
4. **Practical focus**: Real performance numbers and known issues
5. **Future-looking**: Noted areas for improvement
6. **Well-cited**: Every major point links back to source material
## Workflow Pattern Demonstrated
This example shows the complete research workflow:
- **Scoped search** (teamspace filter for engineering)
- **Multi-page synthesis** (4 different sources)
- **Technical template** (architecture-focused format)
- **Proper placement** (under engineering docs)
- **Comprehensive citations** (links to all sources)