A practical, “ship-it” guide to idempotency keys, request hashing, persistence,

<p>Two things quietly decide whether a small application survives being used: whether its reads<br /> are indexed, and whether its writes can be repeated safely. They are usually

<h1> Idempotency Keys: The API Pattern That Saves You From Duplicate Payments and Phantom Records </h1> <p>Your user clicks "Pay" and nothing happens. So they click again. Your

<p><em>Originally published on <a href="https://loopandretry.github.io/posts/what-idempotent-means/?ref=devto" rel="noopener noreferrer">Loop &amp; Retry</a> — field notes on

<p>In distributed systems, failure is not an exception—it’s the default.</p> <p>Network calls fail. Services timeout. APIs return 500s. The real question isn’t <em>“Will things

<p>You hit "Submit Order" and nothing happens. The spinner just spins. Is it processing? Did the request get lost? You click again.</p> <p>If the API on the other end does not

<p>A user clicks “Pay”, the network drops, the client retries… and your backend creates <strong>two</strong> payments.</p> <p>This isn’t a “frontend bug”. Retries happen

<p>Your HTTP client raises <code>ETIMEDOUT</code> on <code>POST /charges</code>. Something has to be written to the database, the status column has two useful values, and so the

<h1> Mitigating DB Lock Contention and Race Conditions in Asynchronous Webhook Ingestion </h1> <h2> 1. The Production Reality: Why Check-Then-Act Fails Under Load </h2> <p>In