Prometheus
Prometheus is an open-source monitoring system that collects metrics from configured targets at given intervals, evaluates rule expressions, displays the results, and can trigger alerts if some condition is observed to be true. It features a multi-dimensional data model with time series data identified by metric name and key/value pairs, a flexible query language (PromQL), and no reliance on distributed storage.
Core Information
#core_informationName, description, vendor website, logo, technology type and tags.
Overview & Role
Prometheus is an open-source monitoring system that collects metrics from configured targets at given intervals, evaluates rule expressions, displays the results, and can trigger alerts if some condition is observed to be true. It features a multi-dimensional data model with time series data identified by metric name and key/value pairs, a flexible query language (PromQL), and no reliance on distributed storage.
Domain Classification & Tags
Performance Profile
#performance_profileTypical read and write throughput, payload size and processing latency.
Read Performance Profile
Throughput: Tens of thousands to hundreds of thousands of queries per second (QPS) depending on query complexity and data volume
Payload Size: Varies widely, from single data points (bytes) to large time series chunks (MBs)
Processing Latency: Typically 10-100 ms for simple queries, can be seconds for complex analytical queries over large datasets
Write Performance Profile
Throughput: Hundreds of thousands to millions of samples per second per Prometheus server
Payload Size: Typically small, individual samples are a few bytes to tens of bytes
Processing Latency: Sub-millisecond to a few milliseconds for ingestion
Architecture Diagram
#architecture_diagramReference diagram of the technology's internal architecture.
Features
#featuresCatalogued product capabilities and what each one does.
Empirical data for features is currently being compiled in the global catalog.
Typical Use Cases
#typical_use_casesScenarios the technology is commonly chosen for.
Empirical data for typical use cases is currently being compiled in the global catalog.
Known Customers
#known_customersPublicly referenced organisations using the technology.
Empirical data for known customers is currently being compiled in the global catalog.
Known Integrations
#known_integrationsOther products and services it is documented to work with.
Empirical data for known integrations is currently being compiled in the global catalog.
Connectors
#connectorsDirectional data connections to other technologies, with direction and maturity.
Empirical data for connectors is currently being compiled in the global catalog.
Reference Architectures
#reference_architecturesPublished architectures where the technology is used or mentioned.
No published reference architecture blueprints currently link to Prometheus.
Security Features
#security_featuresBuilt-in security and access-control capabilities.
Empirical data for security features is currently being compiled in the global catalog.
Known Issues
#known_issuesDocumented limitations, defects and operational pitfalls.
Empirical data for known issues is currently being compiled in the global catalog.
Guidelines
#guidelinesRecommended practices for adopting and operating the technology.
Empirical data for guidelines is currently being compiled in the global catalog.
Standards & Compliance
#standards_and_complianceStandards, certifications and control requirements it maps to.
Empirical data for standards & compliance is currently being compiled in the global catalog.
Sources
#sourcesDocumentation and research references behind the recorded information.
Empirical data for sources is currently being compiled in the global catalog.
Expert Validation
#expert_validationWhether domain experts reviewed and confirmed the content.
Empirical data for expert validation is currently being compiled in the global catalog.