Blog
News, releases and articles about @imqueue. Page 1 of 8.
The contract your services already publish: contract testing for Node.js microservices
Contract testing exists because two services can agree on a shape today and disagree on it next Thursday, with nothing in either repository to notice. If your clients are generated, most of that machinery is already built for you — and the part that is left is not the part the tooling advertises. Here is what an @imqueue service publishes about itself, how to pin it in a test that needs no broker, and the one place the contract can quietly disagree with your TypeScript.
read →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 →Typed at compile time, unchecked on the wire: runtime validation for TypeScript services
Your service method has a signature. The message that arrives has none — it is JSON, and JSON does not remember what it was supposed to be. This is the story of the bug that leaves no stack trace, why your compiler was never in a position to catch it, and how to put a real check at the boundary without slowing anything down.
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.
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