This topic describes the terms that are used in Managed Service for Prometheus.
| Term | Description |
|---|---|
| exporter | An application that runs together with the monitored objects. It is used to convert the existing monitoring data of objects into the OpenMetrics format. This ensures that Managed Service for Prometheus can recognize the exposed metric data. More than 100 official or third-party exporters are available. For more information, see Exporters. |
| job | The configuration set for a group of targets. A job defines the capture behaviors that act on a group of targets, such as capture interval and access control. |
| Prometheus Service | A managed monitoring service that is provided by Alibaba Cloud. Managed Service for Prometheus is compatible with the open source Prometheus ecosystem. Managed Service for Prometheus provides out-of-the-box dashboards for you to monitor a wide variety of components. Managed Service for Prometheus allows you to create multiple types of Managed Service for Prometheus. |
| Prometheus instance | A logical unit that is provided by Alibaba Cloud Managed Service for Prometheus to manage data collection, data storage, and data analysis in Managed Service for Prometheus. |
| Prometheus agent | The Prometheus agent is deployed in a Kubernetes cluster on the user side or on the cloud service side. The Prometheus agent automatically discovers collection targets, collects metric data, and writes data to remote databases. |
| PromQL | The query language of Managed Service for Prometheus. Managed Service for Prometheus supports transient query and time span query, and provides a variety of built-in functions and operators. You can use PromQL statements to aggregate, slice, predict, and combine raw data. |
| sample | The value at a specific point in time on a timeline. In Managed Service for Prometheus, each sample consists of a value of the float64 data type and a timestamp that is accurate to milliseconds. |
| target | The collection target to be captured by the Prometheus agent. The collection target exposes its own running and business metrics, or the Prometheus agent exposes the running and business metrics of the monitored objects. |
| alert rule | Alert configurations that follow the Alerting Rule format of Managed Service for Prometheus. Alert rules can be described by using PromQL. |
| tag | A key-value pair that describes a metric. |
| service discovery | A feature that allows Managed Service for Prometheus to automatically discover collection targets without static configurations. Multiple service discovery methods such as Kubernetes service discovery, Consul, and Eureka are supported. You can use ServiceMonitor and PodMonitor to expose collection targets. |
| pre-aggregation | Managed Service for Prometheus supports recording rules. You can use PromQL to pre-aggregate raw data and save the results as new metrics to improve query efficiency. |
| timeline | A timeline consists of a metric name and a tag. The combination of a metric name and a tag identifies a unique timeline in the time series. |
| remote storage | A time series data storage component that is developed by Alibaba Cloud. Remote storage supports the Remote Write protocol of Managed Service for Prometheus and is hosted on cloud services. |
| cloud service monitoring | Managed Service for Prometheus is integrated with the monitoring data of various Alibaba Cloud services. If you need to monitor an Alibaba Cloud service, you can create a Prometheus instance for the service. |
| metric | A series of tagged data that is exposed by the collection target. The metric data can reflect the running status or business status of the monitored objects. Managed Service for Prometheus uses the standard data format of OpenMetrics to describe metrics. |