Time-series database
A time-series database is a database optimized for storing, organizing, and querying observations or measurements indexed by time.
Machine Learning Platform Engineering
A time-series database stores measurements indexed by time so that temporal queries and retrieval are efficient.
- How it is used
- Supports Kubernetes application monitoring by storing scraped metrics for temporal queries, dashboards, and alerts.
- How deep it goes
- Defines time indexing and traces scraping, querying, visualization, and alerting, but does not detail storage internals.
- Examples
- Uses FastAPI /metrics output, request counters, Prometheus queries, Grafana charts, and response-code aggregation.
- What you can do after
- Operate Prometheus and Grafana to collect, query, visualize, and alert on application metrics.
Read how Machine Learning Platform Engineering explains time-series database →
Effective Platform Engineering
A time-series database is a database optimized for storing and retrieving timestamped measurements and other time-indexed data.
- How it is used
- Stores observability metrics for dashboards, historical analysis, trend identification, and troubleshooting.
- How deep it goes
- Explains storage placement, ingestion routing, querying, and persistence, but does not detail database internals or data modeling.
- Examples
- Uses Prometheus for high-resolution metrics, Grafana for visualization, and Persistent Volume Claims for durable storage.
- What you can do after
- Operate/configure an observability pipeline that stores metrics and exposes them through dashboards and alerts.
Read how Effective Platform Engineering explains time-series database →
Cloud Observability in Action
A time series database is a database optimized for storing and querying values indexed by time.
- How it is used
- Stores and queries low-level system and application metrics as time-indexed signals.
- How deep it goes
- Defines time buckets, series dimensions, counters, data points, and instant or range queries.
- Examples
- Uses container memory, service invocations, and an HTTP 400 request counter with status-code dimensions.
- What you can do after
- Evaluate/understand metric behavior by retrieving values or aggregates for selected series and time ranges.
Read how Cloud Observability in Action explains time-series database →
Related concepts
- Prometheusincludes · Prometheus is an open-source monitoring and alerting system that collects, stores, and queries time-series metrics.
- performanceuses · Performance is the measurable effectiveness or operational behavior of a system under specified conditions, assessed through relevant qualities such as task results, speed, responsiveness, throughput, or resource use.
These guides are generated from the text of Manning books by Manning's knowledge graph and link to the sections they draw on. The full books are available on liveBook and at manning.com.