Writing

Notes on monitoring, alerts, investigation, and keeping production healthy for small teams.

What is a good response time? p95 and p99 latency explained

There is no single good response time, but there are reference points and one rule that beats any number: measure the right percentile and watch it against each route's baseline.

Monitoring & APM2026-07-2110 min read

What to actually monitor when you launch your first app

You do not need a full observability stack to launch. The three signals that catch real problems, the golden signals kept small, and what you can safely skip at first.

Monitoring & APM2026-07-2110 min read

Why does my app work locally but break in production?

Why an app works locally and breaks in production: real data volume, concurrency, config, and external services. What differs, the config trap, and how to catch prod-only breaks.

Monitoring & APM2026-07-2110 min read

Why is my app slow? How to actually find out

Where app slowness hides, why averages lie, and how to trace a slow request to the exact cause instead of guessing. A practical guide for small teams and builders.

Monitoring & APM2026-07-1311 min read

6 things that break when your vibe-coded app gets its first real users

A vibe-coded app that works in development breaks in predictable ways once real users arrive: slow queries, N+1, silent failures, rate limits, auth, and no visibility. What breaks and how to catch it.

Monitoring & APM2026-07-1311 min read

Why is my database query slow?

A database query is slow for a short list of reasons: a missing index, N+1, too much data, or lock contention. How to tell which using the query plan and production traces, and how to fix each.

Monitoring & APM2026-07-1311 min read

LLM observability and cost: where your token spend actually goes

What LLM observability is, why token cost is hard to attribute, what to track by model and feature, and how to do it without a separate tool alongside your monitoring.

LLM observability2026-07-0310 min read

AI agent monitoring: how to watch agents in production

What AI agent monitoring is, why agents are hard to monitor, what to track across a multi-step run, and how to monitor agents without running a separate stack.

LLM observability2026-07-0310 min read

Find out why your vibe-coded app keeps breaking

Error tracking catches thrown exceptions, but vibe-coded apps fail without throwing. The difference between error tracking and monitoring, and what a vibe-coded backend needs.

Monitoring & APM2026-07-0310 min read

Centralized logging: how to get all your logs in one place

What centralized logging is, why you need it once you run more than one service, how the collect-ship-store-search pipeline works, the tools and tradeoffs, and how to do it without running the stack yourself.

Log analysis & investigation2026-07-0110 min read

What can you actually do with your logs?

Your logs are not just for debugging after something breaks. Analytics vs monitoring, what you can watch and alert on from your backend, and how to do it without an enterprise setup.

Monitoring & APM2026-06-2910 min read

How to connect Claude Code to your logs

How to connect Claude Code to your production logs over MCP, so you can query them in plain language from your editor instead of opening a dashboard.

MCP & Claude Code2026-06-256 min read

Log analysis: how to investigate production issues from your logs

What log analysis is, the difference between log management and log analysis, how to investigate production issues from logs step by step, and the tools that help. Grounded in syslog, OpenTelemetry, and trace context.

Log analysis & investigation2026-06-2511 min read

Monitoring errors in production: how to catch them before your customers do

What counts as a production error, why errors slip past you, what to measure, and how to catch them before customers complain. Grounded in HTTP semantics, the SRE golden signals, and OpenTelemetry.

Monitoring & APM2026-06-2510 min read

Application performance monitoring (APM) for small teams: what it is and how to do it

What APM is, the four golden signals it measures, how to instrument with OpenTelemetry, and which APM tools fit a team of two to fifty. Grounded in the SRE golden signals, RED, USE, and the Dapper paper.

Monitoring & APM2026-06-2513 min read

Datadog for startups: how to get the credits (and what happens when they run out)

How to get Datadog for Startups credits step by step, who is eligible, how long they last, what Datadog costs once they run out, and the cheaper alternatives to line up first.

Small-team economics2026-06-2211 min read

What is automated alert investigation

Automated alert investigation is when a system investigates production alerts for you before paging an engineer. It pulls logs, checks deployments, assesses impact, and delivers conclusions.

Log analysis & investigation2026-06-087 min read

The AI on-call engineer: what it is and how it works

An AI on-call engineer handles the investigation side of on-call duty. It monitors production, investigates alerts, and escalates only what needs human judgment.

Log analysis & investigation2026-06-087 min read

What is production engineering in software

Production engineering in software is the discipline of keeping production systems running reliably. It covers monitoring, incident response, reliability, and everything between deploying code and users having a good experience.

Monitoring & APM2026-06-086 min read

Observability without dashboards

What if your observability tool investigated problems instead of showing you graphs? Observability without dashboards means getting answers, not data.

Monitoring & APM2026-06-086 min read

Alert fatigue is killing your engineering team

Most alerts are noise. When everything pages, nothing gets investigated properly. Here is what alert fatigue actually costs and how to fix it.

Monitoring & APM2026-06-058 min read

How to reduce on-call burden without hiring more engineers

On-call does not scale with headcount. Small teams need a different approach to production incidents that does not burn out the people building the product.

Log analysis & investigation2026-06-057 min read

What is AI native observability

AI native observability means your monitoring system investigates problems for you instead of just showing dashboards. Here is how it works and why it matters.

Monitoring & APM2026-06-056 min read