Performance Roadmap
Nine levels from measuring before you touch anything, through reading numbers honestly and finding where time goes, to the physics of loaded systems, the data layer, capacity, SLOs and incident method.
Level 1 · Measure before you touch anything
The discipline that separates diagnosis from guessing: a symptom, a signal that confirms it, and a hypothesis written down before you look. Learn what each signal type can and cannot tell you, and the four numbers that describe any service.
Level 2 · Read the numbers honestly
Averages hide outages and a user id in a label can take down the metrics backend. Counters, gauges and histograms as different questions, percentiles as the only honest summary of latency, and logs structured well enough to reconstruct a failure.
Level 3 · Find where the time goes
Tracing locates time across services; profiling locates cost inside a process. Read a waterfall, find the critical path, spot N+1 by its shape, and know which of the two tools answers the question in front of you.
Level 4 · Understand why loaded systems get slow
The physics. Queueing makes systems slow long before they fail, tail latency dominates user experience at scale, and Little's Law sizes every pool you will ever configure. This is the level that changes how you read every dashboard.
Level 5 · Identify the constrained resource
CPU, memory, disk and network, each with the signal that identifies it as the constraint — and the difference between a memory leak and a cache nobody bounded.
Level 6 · Diagnose the data layer
Databases, caches and queues are where most production latency actually lives. Slow-query workflow, lock waits with idle CPU, pool saturation, hit rates that lie, stampedes, hot keys, backlogs and retry storms.
Level 7 · Know your runtime and your users
Garbage collection, event loops, interpreters and JIT warm-up — labelled per runtime because none of it generalizes. Then the user's half of the budget: the browser waterfall, bundle cost and the vitals that measure experience.
Level 8 · Produce numbers that mean something
Load-test shapes that answer different questions, coordinated omission, benchmark hygiene, and telling a real regression from noise. Then capacity: headroom, autoscaling that arrives in time, and what a request actually costs.
Level 9 · Run it in production, at scale
SLOs that describe user experience, alerts worth waking up for, error budgets as a decision tool — then distributed tail amplification, cross-region physics, incident method, and the trade-offs that make a system faster but worse.