Prometheus is an open-source systems monitoring and alerting toolkit originally built at SoundCloud. It is now a standalone open source project and maintained independently of any company. Prometheus collects and stores its metrics as time series data, i.e., metrics information is stored with the timestamp at which it was recorded, alongside optional key-value pairs called labels.
Prometheus is designed to monitor the performance and health of your applications and infrastructure. It can scrape metrics from instrumented jobs, either directly or via intermediary push gateways for short-lived jobs. It also supports a powerful query language called PromQL to help you analyze and visualize metrics data.
When Prometheus is not scraping due to timeout issues, you may observe that certain metrics are missing from your dashboards or alerts. This can lead to incomplete data analysis and potentially missed alerts for critical systems. In the Prometheus logs, you might see messages indicating scrape timeouts or failures to retrieve metrics from specific targets.
The primary issue here is that Prometheus is unable to complete the scraping of metrics from a target within the configured timeout period. This can happen if the scrape timeout is set too short or if the target's response time is too long. The default scrape timeout in Prometheus is 10 seconds, but this may not be sufficient for all environments or targets, especially if they are under heavy load or have complex queries to process.
For more details on configuring scrape timeouts, refer to the Prometheus Scrape Configuration documentation.
First, check the current scrape timeout settings in your Prometheus configuration file (usually named prometheus.yml). Look for the scrape_timeout parameter within your scrape_configs section.
scrape_configs:
- job_name: 'example'
scrape_interval: 15s
scrape_timeout: 10s
static_configs:
- targets: ['localhost:9090']
If the scrape_timeout is not explicitly set, it defaults to the value of scrape_interval. Consider increasing the timeout value to accommodate slower targets.
If increasing the scrape timeout is not feasible or does not resolve the issue, investigate the target's response time. Ensure that the target application or service is optimized for performance. This might involve reviewing and optimizing database queries, reducing payload sizes, or increasing resource allocations.
For guidance on optimizing Prometheus performance, check out the Prometheus Performance Optimization guide.
After making changes, monitor the Prometheus logs and dashboards to ensure that metrics are being scraped successfully. Use PromQL queries to verify that data is being collected as expected. For example, you can run a query like up{job="example"} to check the status of your targets.
For more information on using PromQL, visit the PromQL Basics documentation.
By adjusting the scrape timeout settings and optimizing target performance, you can resolve timeout issues and ensure that Prometheus continues to scrape metrics effectively. Regularly review your configurations and monitor performance to maintain a robust monitoring setup.
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