[Section] Metrics

[andrewhowdencom]

Objectives

After this course, learners should be able to:

1. Understand the strengths and weaknesses of time-series data
2. Understand the types of problems that time-series data can solve
3. Understand how this data fits into the greater observability journey (e.g. vs. logs, distributed tracing).
4. Understand the general architecture of time-series
5. Understand how to view some basic time-series data via Prometheus (e.g. CPU, memory, disk)
6. Understand the specific data types provided by OpenTelemetry
7. Understand how to instrument the system with: a. Counter (e.g. requests/sec) b. Gauge (e.g. memory) c. Histogram (e.g. latency of requests)
8. Understand how to break the data down into sections through attributes, as well as limits on this approach.
9. Be able to use common libraries for this data
10. Understand common models of data (latency, error rates and throughput)
11. Understand how to query the data back (counter, gauge, histogram and so on)
12. Understand how to graph the data via Grafana (e.g. counter & gauge → single stat, histogram → Multi-line graph and heatmap).

Subject Matter Expert

@andrewhowdencom

Validation

No response

Deliverables

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• [ ] Quiz (Partially completed; needs research)