Migration fatigue, and how LLMs help us avoid it
How we avoided shipping a database migration by using an LLM to turn a slow active job rescue query into a single producer-state pass, producing a ~130x speedup without an index.
Blog
Announcements, engineering posts, and other news from the River team. Available as an Atom feed .
Brandur Leach River supports Turso
River v0.41 adds support for Turso, a ground-up rewrite of SQLite in Rust.
Now in Pro: Active job rescue
River Pro v0.26 adds active job rescue, which uses queue heartbeats to quickly recover jobs orphaned by crashed clients, no additional schema required.
River metrics have arrived
River v0.41 adds an extensible hook for receiving metrics, starting with job-fetch duration and locked-job counts, and with batteries-included OpenTelemetry support through otelriver.
Go's stuck goroutine problem (and why to let it fail)
Go can't kill a stuck goroutine, but River v0.40's new stuck-job handler can expose a goroutine stuck in an indefinite wait, preserve worker capacity, and trigger a restart before stuck jobs exhaust a process.
River Pro workflows V2: signals, timers, and 60% higher sustained throughput
River Pro v0.24.0 introduces workflows V2 with durable workflow signals, timers, CEL wait conditions, and a rebuilt engine with 60% higher sustained workflow throughput in local benchmarks.
Blake Gentry River for TypeScript: Emit jobs from Node to Go
A new TypeScript client for inserting River jobs from Node.js, with drivers for node-postgres and Prisma.
A better client stop (no additional channels or goroutines required)
`SoftStopTimeout` simplifies River's graceful shutdown by collapsing a previously elaborate and lengthy routine down to a single config option.
Avoiding re-work with resumable jobs
Resumable jobs break work into steps so retries skip what's already done, saving time and money on expensive operations.
Concurrent repack: Vacuum full without the pain
At long last, a prospective feature for Postgres 19, `REPACK (CONCURRENTLY)`, will provide a production-safe way to reclaim space from bloated tables without downtime.
River is SOC 2 Type II compliant
River has completed its SOC 2 Type II audit, verifying that the security controls protecting hosted Pro customer data operate effectively over time.
The evolution of background job frameworks in Ruby
From BackgrounDRb and Delayed::Job through Resque, Sidekiq, GoodJob, and Solid Queue, a history of how Ruby's job systems evolved—and what River learned from them.
Dependabot + private Go proxies: how they work and why it matters
GitHub's Dependabot can now work with private Go proxies/registries. But how do Go proxies even work? Learn how they function, how to configure them for private modules, and why ordering matters.
River on Rails: Pushing select, performance sensitive tasks from Ruby to Go
Build a Rails app that transactionally enqueues webhook jobs for Go workers using River's Ruby client, Active Record integration, retry controls, and structured job arguments.
SQLite for River, durable periodic jobs and database/sql for River Pro, better performance for all
River v0.23 and River Pro v0.15 bring 15–20% higher benchmark throughput, faster Sequences and Concurrency Limits, a SQLite preview, durable periodic jobs, and `database/sql` support for Pro.
River UI job filters, schema support, lib/pq compatibility, and more
River UI adds filters by kind, queue, ID, and priority plus per-attempt logs, while River expands alternate-schema and `lib/pq` support and adds job-kind aliases.
Defense in depth with encrypted jobs
Using encrypted jobs and NaCL Secretbox to add a layer of security protecting data even in the worst case scenario of widespread database exfiltration.
Designing River's hooks and middleware for change resistance and future extensibility
Why River offers both middleware and lightweight hooks, and how small, interface-driven extension points add customization without forcing breaking API changes.
Precision concurrency control with River Pro
River Pro now supports global concurrency limits to precisely control how many jobs can run concurrently across your infrastructure, complete with granular partitioning and operational control through River UI.
Building an idempotent email API with River unique jobs
Using unique jobs in River to build an email API that takes an idempotency key so that even in the event a request needs to be retried, it never sends a duplicate email.
Measuring River with OpenTelemetry
Monitor River job insertion and execution with `otelriver`, which emits OpenTelemetry traces and metrics for duration, outcomes, queues, and job kinds.
New Pro feature: Sequences
River Pro Sequences process related jobs one at a time while allowing independent sequences to run in parallel, preventing races without consuming worker slots.
River UI as a packaged Go module
River UI v0.5 ships as an embeddable Go module with bundled frontend assets, letting applications mount the full UI as an `http.Handler` at any path.
Launching workflows and River Pro
River Pro launches with workflows: code-defined job graphs that split complex work into observable, independently retryable tasks with first-class River UI support.
A `database/sql` escape hatch for broader ecosystem interoperability
River's expanded `riverdatabaseql` driver brings full `database/sql` support, including transactional job insertion alongside Bun, GORM, and other Go database tools.
River Python: Insert in Python, work in Go
Insert River jobs from Python with synchronous or asyncio clients, SQLAlchemy integration, transactional enqueueing, and type hints, then execute them in Go.
Announcing River UI
River UI is a self-hosted web interface for River, bringing powerful operational and development tooling to River users. It's freely available as a Docker image, a pre-built static binary, or for bundling into your own application.
Uniqueness with Postgres advisory locks and FNV hashing
How River combines Postgres transaction-level advisory locks with Go's FNV hashing to prevent duplicate jobs safely across concurrent clients.
River 2024: Stability, new APIs, and production readiness
River's first six months bring a stable core API, 4.5× higher benchmark throughput, queue controls, and new job-management APIs on the path to production readiness.
River 0.4.0: A few breaking changes
River 0.4.0's released, and it contains a few small breaking changes that've been batched together. A list of specific changes, upgrade guide, and a little rationale for why we thought they were justified.
Announcing River: Fast and reliable background jobs for Go
For the past several months, I’ve been working with Brandur to build the Postgres background job library that the Go ecosystem needs: it’s called River, and we’re launching it today in beta.