Chapter 2 Introduction to Prometheus
The origin of the Prometheus
Facebook found that 85% of queries were for data within 26 hours. This requires a strong query language and often limited retention periods for monitoring data.
architecture
The metrics collected
Using a pull mode, you need to install your exporter to export metrics to a specific port.
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Endpoint: The source of metris
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Target configuration: How do you connect, what metadata is applied, what authentication is required for the connection, or define how fetching will be performed
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Job: A set of targets
Service discovery
- Based on the file
- Automatically discover
Aggregation and alerts
Query data
Query promQL, graphical interface
The data model
Each time series is uniquely identified by a combination of time series names and labels
- Instrumentation label: add before fetching
- Target label: added after fetching
Metrics starting with _ is for internal use
The name of the metrics
Consists of ASCII characters, digits, underscores (_), and colons ()
The sampling
- A value of type float64
- A millisecond precision timestamp
Define the rules
metrics_name{label1=value1, label2=value2}
Retention time
It keeps 15 days of time series data in its database.
security
- Untrusted users will be able to access the HTTP API of the Prometheus server to access all data in the database. Confused. JPG
- Only trusted users have access to the Prometheus command line, configuration files, rules files, and runtime configurations.
Prometheus and its components do not provide any server-side authentication, authorization, or encryption