Prometheus Historical Data & Trends

To display historical data and trend analysis in Prometheus, you can achieve this using the query language PromQL provided by Prometheus. Here are some steps that can help you showcase historical data and trend analysis.

1. Utilize PromQL to query historical data: With PromQL query language, you can retrieve historical data. For instance, you can use sum(rate(http_requests_total[5m])) to query the number of HTTP requests from the past 5 minutes. By adjusting the time range in the query, you can retrieve historical data from different time periods.
2. Create charts to display trend analysis: You can use monitoring visualization tools like Grafana to connect to Prometheus and create charts for trend analysis. In Grafana, you can select Prometheus as the data source, then choose the metrics and time range to display in the chart configuration, showing historical data and trend analysis.
3. By utilizing built-in features in Prometheus, such as the rate() and predict_linear() functions, you can conduct trend analysis. The rate() function can be used to calculate the rate of change in a time series, while the predict_linear() function can be used to make linear predictions on the time series.

With the methods mentioned above, you can display historical data and trend analysis in Prometheus, helping you better understand system performance and identify potential issues.