Debugging methodology, code review, bug reports, testing strategy and postmortem culture.
Four engineers, one invoicing product, no QA team. This is the risk-based testing strategy we settled on: integration tests over mocks, contract tests at service edges, a handful of E2E happy paths and test data that does not rot.
Sending teams a monthly cost spreadsheet changes nothing. Charging their budgets before they trust the numbers starts arguments. This guide covers a showback program that works: ownership mapping, a short report with actions, budgets per service, and when to move to chargeback.
A pipeline you are afraid to re-run is a pipeline that will eventually corrupt data. This guide covers partition overwrite, MERGE upserts, dedup keys, watermarks and why exactly-once is a property you build, not a setting you enable.
A field guide to receiving webhooks reliably: verify signatures on the raw body, respond fast, queue the work, deduplicate by event ID, tolerate out-of-order delivery, replay safely and monitor the whole pipeline. With code you can adapt.
The pre-launch security checklist we run on every new web app, organised by the OWASP Top 10:2025 categories: authorization tests, injection, secrets, headers and CSP, supply chain, error handling and logging, each with a concrete check you can automate.
A cloud bill that grows 30 percent can be great news or a disaster, depending on what grew with it. Unit costs, such as cost per active customer or per thousand requests, tell you which. This guide shows how to choose units, allocate shared costs and use the numbers in decisions.
Most review comments are about naming and style, while the bugs walk past. How we review for correctness instead: follow the data, probe edge cases and error paths, look for races and trust boundaries, keep PRs small and hand style to machines.
Most trading bot failures we have seen are not strategy bugs; they are state bugs: lost fills, duplicate orders, wrong positions after a restart. This guide describes an architecture that keeps state correct: separated components, an order state machine, persistence, risk checks and reconciliation.
We once spent two weeks optimizing SQL for an endpoint whose real cost was a logging call. Since then every performance task starts with a profile. Here is how we capture flame graphs in PHP, Node.js and Python, how to read them, and how to measure the win.
A practical crash triage workflow for iOS and Android teams: get readable stack traces with dSYMs and R8 mapping files, group crashes sensibly, reproduce with context, fix with a test and confirm the fix per release with staged rollouts.
A practical guide to blameless postmortems: how to build a timeline, measure impact, find contributing factors instead of a culprit, write action items that get done, and run the review meeting so people tell the truth.
A practical guide to time handling that survives DST switches: when to store UTC instants, when to keep local time plus an IANA zone, how gaps and overlaps behave, which database types to use, and how to test with fixed clocks.
A good bug report lets someone who has never seen your screen reproduce the problem in minutes. The anatomy we use: environment, exact steps, expected versus actual, evidence, a minimal reproduction, and severity kept separate from priority.
Debugging is faster as a method than as inspiration. The six steps we use on every hard bug, from a reliable reproduction to a regression test, walked through on a real slowdown we isolated among 143 commits with an automated git bisect run.