Amazon Timestream
Serverless time-series database for IoT, metrics, and operational telemetry
Prometheus
Flexible monitoring system with powerful queries and autonomous servers
Prometheus collects metrics via pull or push, stores them in a multi‑dimensional time series database, offers PromQL for analysis, and supports alerting, federation, and diverse service discovery.
Overview
Who should use Prometheus?
Prometheus is designed for developers, SREs, and operations teams that need a cloud‑native monitoring solution for dynamic environments such as Kubernetes, micro‑service architectures, and virtual machines. It runs as a single‑server process that scrapes metrics from configured targets, stores them locally, and makes them available through the expressive PromQL query language.
Core capabilities and deployment
The system uses a pull‑based HTTP model, with optional push via an intermediary gateway for batch jobs. Service discovery plugins automatically locate targets across cloud providers, container orchestrators, and static configurations. Metrics are stored in a multi‑dimensional time‑series database, enabling powerful aggregation and alerting rules. For larger installations, horizontal federation lets multiple Prometheus servers share data while each node remains autonomous. Deployment options include pre‑compiled binaries, Docker images, or building from source with Go and NodeJS toolchains. The built‑in web UI provides basic graphing, while integrations with Grafana deliver richer dashboards.
Highlights
Multi‑dimensional time‑series data model
PromQL – powerful query language
Autonomous single‑server operation
Built‑in service discovery and federation
Pros
- Open‑source with active CNCF community
- Flexible pull‑based collection reduces target impact
- Rich alerting and rule evaluation
- Extensive integrations and exporters
Considerations
- Scaling beyond a single node requires federation
- Push gateway adds complexity for batch jobs
- Remote write feature is still experimental
- Learning curve for PromQL
Managed products teams compare with
When teams consider Prometheus, these hosted platforms usually appear on the same shortlist.
Looking for a hosted option? These are the services engineering teams benchmark against before choosing open source.
Fit guide
Great for
- Kubernetes clusters and containerized workloads
- Micro‑service architectures needing custom metrics
- Teams requiring programmable alerting
- Organizations preferring self‑hosted monitoring
Not ideal when
- Very high‑cardinality metrics without federation
- Environments that need a fully distributed storage backend
- Users seeking out‑of‑the‑box dashboards without Grafana
- Teams lacking ops expertise to manage configuration
How teams use it
Cluster health monitoring
Continuously scrapes node and pod metrics, alerts on resource exhaustion, and visualizes trends via Grafana.
Service latency alerting
Uses PromQL to define latency thresholds, triggering alerts when SLA limits are breached.
Capacity planning
Analyzes historical time‑series data to forecast resource needs and guide scaling decisions.
Federated multi‑region monitoring
Aggregates metrics from regional Prometheus instances into a central server for unified dashboards.
Tech snapshot
Go86%
TypeScript13%
Yacc1%
Shell1%
CSS1%
SCSS1%
Frequently asked questions
What type of data model does Prometheus use?
It stores metrics as time‑series identified by a metric name and a set of key/value labels, enabling multi‑dimensional queries.
How does Prometheus collect metrics?
Primarily via an HTTP pull model; targets expose /metrics endpoints that Prometheus scrapes at configured intervals. A push gateway can be used for batch jobs.
Can Prometheus scale horizontally?
A single server is autonomous, but large deployments use federation to combine data from multiple servers while keeping each node independent.
What is PromQL?
PromQL is Prometheus’s query language that lets you select and aggregate time‑series data using the metric’s labels and functions.
How is Prometheus typically visualized?
It includes a basic web UI for graphing, and integrates with Grafana for advanced dashboards and alerting.
Project at a glance
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