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Basic Concepts

Updated on 2024-09-06 GMT+08:00

This section describes the basic concepts about Prometheus monitoring.

Table 1 Basic concepts

Concept

Description

Exporter

Collects monitoring data and regulates the data provided for external systems using the Prometheus monitoring function. Hundreds of official or third-party exporters are available. For details, see Exporters.

Target

Target to be captured by a Prometheus probe. A target either exposes its own operation and service metrics or serves as a proxy to expose the operation and service metrics of a monitored object.

Job

Configuration set for a group of targets. Jobs specify the capture interval, access limit, and other behavior for a group of targets.

Prometheus monitoring

Fully interconnects with the open-source Prometheus ecosystem. It monitors various components, and provides multiple out-of-the-box dashboards and fully hosted Prometheus services.

Prometheus instances

Logical units used to manage Prometheus data collection, storage, and analysis.

Prometheus probes

Deployed in the Kubernetes clusters on the user or cloud product side. Prometheus probes automatically discover targets, collect metrics, and remotely write data to databases.

PromQL

Prometheus query language. Supports both query based on specified time spans and instantaneous query, and provides multiple built-in functions and operators. Raw data can be aggregated, sliced, predicted, and combined.

Sample

Value corresponding to a time point in a timeline. For Prometheus monitoring, each sample consists of a value of the float64 data type and a timestamp with millisecond precision.

Alarm rule

Alarm configuration for Prometheus monitoring. An alarm rule can be specified using PromQL.

Tag

A key-value pair that describes a metric.

Metric management

Automatically discovers collection targets without static configuration. Supports multiple metric management modes (such as Kubernetes SD, Consul, and Eureka) and exposes collection targets through ServiceMonitor or PodMonitor.

Recording rules

With recording rules, raw data can be processed into new metrics using PromQL to improve query efficiency.

Time series

Consist of metric names and tags. Time series are streams of timestamped values belonging to the same metric and the same set of tagged dimensions.

Remote storage

Self-developed time series data storage component. It supports the remote write protocol related to Prometheus monitoring and is fully hosted by cloud products.

Cloud product monitoring

Seamlessly integrates monitoring data of multiple cloud products. To monitor cloud products, connect them first.

Metrics

Labeled data exposed by targets, which can fully reflect the operation or service status of monitored objects. Prometheus monitoring uses the standard data format of OpenMetrics to describe metrics.

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