rust-prometheus VS droxporter

I used the prometheus library because it was the most popular and easiest to find. Some unusual and unexpected aspects were that, to delete metrics, all labels must be specified at once, and to record metrics, I always needed the full list of labels that were used during creation. However, these issues were manageable.

[dependencies] prometheus = { git = "https://github.com/tikv/rust-prometheus", rev = "ac86a264223c8d918a43e739ca3c48bb4aaedb90", features = ["process"] }

Metrics exposition is implemented with prometheus crate.

The new Elasticsearch exporter is written in the Rust programming language and is open-sourced on GitHub: github.com/vinted/elasticsearch-exporter-rs. The exporter uses asynchronous Tokio runtime, Rust Prometheus instrumentation library and the official Elasticsearch client library. Metrics collection is decoupled from the serving /metrics endpoint. In addition, Elasticsearch time-based metrics in milliseconds are converted into seconds to comply with Prometheus best practices (metrics ending in “millis” are replaced by “seconds”, “_bytes” and “_seconds” and postfixes are added where appropriate).

Rust has a popular binding: https://github.com/tikv/rust-prometheus

The DigitalOcean rate limits were another challenge. To avoid hitting them, I had to ensure long enough intervals for reading metrics and provide the ability to use multiple keys. I also created my own rate limiter, which you can find here.