---
# System prepended metadata

title: ADR Example

---

\# ADR-001: Adopt Redis for Caching Layer

  

\*\*Status:\*\* Accepted\\

\*\*Date:\*\* 2025-08-17\\

\*\*Author:\*\* John Doe\\

\*\*Reviewers:\*\* Backend Team

  

\------------------------------------------------------------------------

  

\## Context

  

Our web application frequently queries the database for user session

data and configuration settings.\\

This has led to \*\*performance bottlenecks\*\* under high traffic. We need

a caching solution that:\\

\- Reduces database load\\

\- Provides sub-millisecond reads\\

\- Supports distributed deployment for future scaling

  

\------------------------------------------------------------------------

  

\## Considered Options

  

1\.  \*\*Rely only on PostgreSQL\*\*

    -   Pros: Simple, no new infrastructure\\

    -   Cons: High latency under load, risk of DB saturation

2\.  \*\*Use Memcached\*\*

    -   Pros: Very fast, simple key-value store\\

    -   Cons: Limited feature set, no persistence, weaker ecosystem

3\.  \*\*Use Redis (chosen)\*\*

    -   Pros: Fast, supports persistence, pub/sub, wide adoption, rich

        ecosystem\\

    -   Cons: Slightly more complex setup and maintenance

  

\------------------------------------------------------------------------

  

\## Decision

  

We decided to \*\*adopt Redis as the primary caching layer\*\* because it

balances performance, reliability, and ecosystem maturity.\\

Redis will be used for:\\

\- Session storage\\

\- Frequently accessed configuration values\\

\- Future use cases (rate limiting, queues)

  

\------------------------------------------------------------------------

  

\## Consequences

  

\-   \*\*Positive:\*\* Reduced DB load, faster response times, scalability

    for traffic spikes\\

\-   \*\*Negative:\*\* Adds infrastructure dependency (Redis cluster must be

    monitored and maintained)\\

\-   \*\*Mitigations:\*\* High-availability Redis setup with monitoring and

    alerting

  

\------------------------------------------------------------------------

  

\## Implementation Roadmap

  

1\.  Deploy Redis cluster in staging environment\\

2\.  Update application code to read/write session data to Redis\\

3\.  Configure monitoring and failover strategies\\

4\.  Roll out changes to production

  

\------------------------------------------------------------------------

  

\## Success Metrics

  

\-   Average response time reduced by 30%\\

\-   Database CPU utilization \\< 60% under peak load\\

\-   99.9% cache hit rate for session data

  

\------------------------------------------------------------------------

  

\## Future Considerations

  

Evaluate Redis Streams for event-driven features.\\

Consider managed Redis services (e.g., AWS ElastiCache) if operational

overhead grows.
