Stage 2 · Lesson 2 of 6
The Prometheus data model
stores : a metric name, a set of labels and timestamped values. It (fetches) metrics over HTTP from each target on an interval. There are three you use daily.
A counter only goes up, such as requests served; you almost always wrap it in rate(). A gauge goes up and down, such as queue length. A histogram counts observations into buckets, such as request durations, so can be computed later across many pods.
Labels such as service, route and status code let you slice the data. You met Prometheus in the DevOps roadmap; here the goal is to know why each type exists.
Common trapusing a summary for latency and then averaging its percentiles across pods, which gives a number that means nothing.
A question to check yourself, an AI practice session and 1 cheat sheet entry come with the full roadmap. Unlock
Resources for this stage
Start with· follow one of these
- GuideFreePrometheus Documentation
Prometheus · Intermediate
Free: the first steps guide, then the querying basics, functions and histograms pages
- CoursePaidPrometheus Certified Associate (PCA) Prep Course
KodeKloud · Intermediate · Subscription
Paid, hands-on labs for PromQL, recording rules, Alertmanager and Kubernetes monitoring
Practise
Keep handy
Also worth your time
The chapter that defines the four golden signals and what makes monitoring worth paging on