Prometheus does not inherently cache probe results in a traditional database. Instead, Prometheus collects and stores time-series data directly in its storage system. The core architecture of Prometheus is designed to scrape metrics from targets at regular intervals, storing them in a time-series database. These metrics are then available for querying and analysis.
However, Prometheus itself is not a general-purpose caching system for arbitrary data or for caching probe results beyond its normal operation. The primary purpose of Prometheus is to collect, store, and query time-series data related to system and application metrics.
If you have specific requirements for caching probe results or other data, you might need to implement a separate caching solution based on your use case. Tools like Redis or Memcached are commonly used for general caching purposes, and you can design a system where the results of probes are cached in such systems if needed.
Remember that Prometheus is more focused on real-time monitoring and alerting based on time-series data rather than serving as a generic caching layer. If you have specific caching requirements, you might need to integrate Prometheus with other tools or build a custom solution to meet your needs.
references:
OpenAI
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