Rails Hosting in Production: Sidekiq, Postgres, Assets, and Scaling

Production Rails deployments are presented as a four-part architecture consisting of a Puma web service, a separate Sidekiq background worker, Render Postgres for durable data, and Render Key Value for queues and caching, though newer, lower-volume applications can use database-backed Solid Queue instead. The guidance emphasizes sizing Puma workers, threads, Sidekiq concurrency, and service instances within PostgreSQL’s hard connection limits, reserving capacity for maintenance and optionally using PgBouncer when more client connections are needed. Long-running work should move from HTTP requests to retry-safe, idempotent background jobs, while Sidekiq workers should have shutdown settings that allow unfinished jobs to be requeued during deployments. For queue reliability, Key Value should use noeviction and paid persistent storage, with attention to Redis and Valkey version compatibility. Deployments should compile assets during builds, store uploads in object storage rather than local disks, run migrations as pre-deploy commands, and use Rails’ `/up` endpoint for HTTP health checks. The comparison estimates a minimal always-on Render stack at about $30 monthly before bandwidth and workspace costs, while describing trade-offs in pricing, operational complexity, scaling, and managed infrastructure across Heroku, Fly.io, AWS Elastic Beanstalk, and Railway.

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