7 Infra-Level Caching Wins That Can Cut Backend Load by 60% (Without Touching a Line of Code)

1. Cloudflare CDN: Cut Up to 70% of Origin Traffic

By enabling full-page caching for anonymous users and tuning cache keys for geography and device type, we shifted a massive portion of requests to be served directly from the edge.

2. Reverse Proxy Microcaching: Smooth Spikes, Save CPUs

This technique absorbs repeated traffic patterns during peak times, without affecting freshness.

3. Fix Internal Traffic Leaks: Keep Local Calls Local

We rewired these internal calls to go through Kubernetes internal DNS or private ALBs.

4. ProxySQL Query Routing & SQL Caching: Reduce Aurora Load

Aurora performs well but can become a bottleneck under heavy read traffic, risking potential downtime. By implementing ProxySQL, we:

Together, these moves offloaded Aurora's writer node and reduced replica count.

5. Redis as Shared Infra Cache: Offload App Logic

Redis is often used for sessions or queues, but we turned it into a smart shared cache layer. Without touching the app, we cached:

These were pre-warmed and managed via background workers, not app logic.

6. MySQL Index Audit: Boost Query Speed Without a Rewrite

We did a targeted audit and restructured a few tables for high-frequency queries.

7. Observability: Expose Cache Wins, Tune What Matters

Armed with cache hit ratios and traffic patterns, we adjusted TTLs, fine-tuned rules, and scaled with precision.

Total Potential Win: Up to 60% Backend Load Reduction

7 Infra-Level Caching Wins That Can Cut Backend Load by 60% (Without Touching a Line of Code)

This technique absorbs repeated traffic patterns during peak times, without affecting freshness.

Aurora performs well but can become a bottleneck under heavy read traffic, risking potential downtime. By implementing ProxySQL, we:

Together, these moves offloaded Aurora's writer node and reduced replica count.

Redis is often used for sessions or queues, but we turned it into a smart shared cache layer. Without touching the app, we cached:

These were pre-warmed and managed via background workers, not app logic.

We did a targeted audit and restructured a few tables for high-frequency queries.

Armed with cache hit ratios and traffic patterns, we adjusted TTLs, fine-tuned rules, and scaled with precision.

Related Blogs

7 Infra-Level Caching Wins That Can Cut Backend Load by 60% (Without Touching a Line of Code)

This technique absorbs repeated traffic patterns during peak times, without affecting freshness.

Aurora performs well but can become a bottleneck under heavy read traffic, risking potential downtime. By implementing ProxySQL, we:

Together, these moves offloaded Aurora's writer node and reduced replica count.

Redis is often used for sessions or queues, but we turned it into a smart shared cache layer. Without touching the app, we cached:

These were pre-warmed and managed via background workers, not app logic.

We did a targeted audit and restructured a few tables for high-frequency queries.

Armed with cache hit ratios and traffic patterns, we adjusted TTLs, fine-tuned rules, and scaled with precision.

Related Blogs