Mykhailo Stadnyk
Web developer, software engineer and architect — mainly TypeScript, Go, JavaScript, Node.js, Python and C. Mykhailo is the creator and maintainer of the @imqueue framework.
// POSTS BY MYKHAILO STADNYK
Meeting compliance: how to talk to your Redis broker over TLS
The questionnaire asks whether data is encrypted in transit, and you know the answer for the edge. Then you remember the broker — the one connection every service holds open all day, carrying every argument and every return value, and speaking a protocol that puts them on the wire as text. Here is what encrypting it takes, what it costs, and the two places it is easy to get wrong.
read →Checking an IP against 10,000 networks without comparing it to 10,000 networks
Every request asks the same question — is this one of ours? — and the loop you wrote to answer it gets slower every time someone adds a partner range. Here is how to answer it in logarithmic time instead, what an address really is once you stop treating it as a string, and the quiet precondition that a fast implementation must uphold or it will lie to you.
read →Autoscale on queue depth, not CPU
CPU tells you a process is busy, not whether anyone is waiting. An @imqueue service's backlog is a Redis list, so KEDA can scale on it with no exporter, no Prometheus and no code change — and the metrics server covers the case where you need more.
read →Cache invalidation across services: a TTL, a tag, or the database
Caching a service method is one decorator. Deciding when the entry dies is the whole job. Here are the three mechanisms measured — a guessed TTL, a tag invalidated by an event, and PostgreSQL dropping the entry 6ms after the row changes — plus the four ways a cache goes on serving data it already knows is stale, and a fifth that got fixed while this was being written.
read →How Node.js services talk to each other in 2026: the honest options
REST, gRPC, tRPC, NATS, a framework like NestJS or Moleculer, or RPC over a message queue. Six real approaches, what each one costs, and the two questions that actually decide it — including when @imqueue is the wrong answer.
read →Delayed and scheduled work without adding a job system
"Send that email in 24 hours" usually turns into a second deployment, a second data model, and a job record shadowing a service method you already wrote. Often the message queue you already run can just do it. Here's how deferral works as a parameter, and what it costs.
read →BullMQ alternatives for Node.js: an honest 2026 guide
BullMQ is the default Redis job queue for Node.js — but it isn't the only choice. Here's an even-handed map of the alternatives (Bee-Queue, pg-boss, Agenda, @imqueue/job and more), what each is actually good at, and how to pick.
read →RPC between Node.js microservices over a message queue
Why route internal service-to-service calls through a message queue instead of HTTP or gRPC — and how @imqueue makes those calls fully typed with zero client boilerplate.
read →Load balancing microservices without a load balancer
For internal service-to-service traffic, the load balancer you run and operate is often solving a problem a message queue solves for free. Here's the competing-consumers pattern, why pull beats push, and what you give up.
read →Do your Node.js back-ends really need service discovery?
Consul, etcd, DNS-SD — service discovery is a lot of machinery to stand up. Sometimes you genuinely need it; often you don't. Here's how to tell, and how a queue makes the question disappear.
read →Back-pressure for Node.js services
When a downstream service slows down, HTTP tends to turn that into a cascading failure. A queue absorbs the spike instead. Here's the difference, and the trade-offs to watch.
read →Guaranteed message delivery: cost and when to use it
"Will I lose messages if a worker dies?" is the right question — and the answer is a trade-off, not a yes/no. Here's how guaranteed delivery works, what it costs, and how to choose per workload.
read →Redis as a message bus: patterns beyond pub/sub
Most people know Redis pub/sub and stop there. Redis has richer primitives — lists, blocking pops, and streams — that make it a capable message bus. Here's a tour, and where each fits.
read →gRPC vs message-queue RPC for internal Node.js services
gRPC is the default answer for typed RPC — and a great one, especially across languages. For an all-Node.js back-end, routing RPC through a queue trades some of gRPC's strengths for a lot less infrastructure.
read →Benchmarking @imqueue: throughput and delivery modes
Real measured throughput for @imqueue's message queue — ~200k msg/sec unreliable, ~120k guaranteed on a 24-core box — what the delivery modes cost, and a reproducible harness to measure the figures that matter: yours.
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