Rails Performance: Query Plans, Cache, and Queue Latency
Guides for Rails performance work that starts with evidence: query plans, cache behavior, queue latency, time-series growth, and deploy cost checks. The useful question is not "how do we make Rails faster"; it is which measured path is slow, expensive, or fragile enough to change.
SLOW PAGE OR REPORT
Start with request traces, query count, `pg_stat_statements`, and the worst `EXPLAIN ANALYZE` plan before adding a cache.
CACHE CHURN OR REDIS COST
Use the Solid Cache guide only after measuring hit rate, write churn, object size, and PostgreSQL headroom.
GROWING EVENT DATA
TimescaleDB is worth considering when retention, compression, and time-bucket aggregates are already database work.
QUEUE LATENCY
Use Mission Control and queue metrics before changing workers. Separate stuck jobs, retry storms, and ordinary throughput pressure.
Bad Fit For This Hub
Do not start here if the problem is only "the app feels slow" and nobody can name the affected page, job, report, or API path. First collect one trace, one slow query list, queue latency, cache hit-rate data, or the business path users are waiting on. Without that evidence, performance work turns into guesswork.
Rails PostgreSQL Performance: Start With the Query Plan
Use EXPLAIN ANALYZE to find the real database bottleneck before adding indexes, caches, materialized views, or PgBouncer.
TimescaleDB vs Postgres in Rails
When hypertables, compression, continuous aggregates, and retention policies are worth adding to a Rails app.
Solid Cache in Rails 8
How database-backed caching changes the Redis decision, including setup, capacity, and gotchas under real traffic.
Deploy Rails 8 with Kamal to a VPS
Server hardening, Docker, SSL, migrations, and zero-downtime deploys for cost-conscious Rails infrastructure.
Mission Control Jobs
Queue visibility, failed job handling, dashboard access, and alerts for background work.
Need a Rails performance audit?
Performance work starts at the query log, the slow-query table, and the three worst query plans, not at a caching layer. Show me the endpoint or job users actually feel and the `pg_stat_statements` rows behind it, and the profiling points at the real fix: a query, an index, a cache boundary, a job split, or more capacity. If the fix turns out to be removing Redis, the Rails 8 Solid Stack hub covers that path.
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