veneur VS community

This was the idea behind Stripe's Veneur project - spans, logs, and metrics all in the same format, "automatically" rolling up cardinality as needed - which I thought was cool but also that it would be very hard to get non-SRE developers on board with when I saw a talk about it a few years ago.

https://github.com/stripe/veneur

One pain point with Prometheus is that is has relatively weak support for quantiles, histograms, and sets[1]:

- Histograms require manually specifying the distribution of your data, which is time-consuming, lossy, and can introduce significant error bands around your quantile estimates.

- Quantiles calculated via the Prometheus "summary" feature are specific to a given host, and not aggregatable, which is almost never what you want (you normally want to see e.g. the 95th percentile value of request latency for all servers of a given type, or all servers within a region). Quantiles can be calculated from histograms instead, but that requires a well-specified histogram and can be expensive at query time.

- As far as I know, Prometheus doesn't have any explicit support for unique sets. You can compute this at query time, but persisting and then querying high-cardinality data in this way is expensive.

Understanding the distribution of your data (rather than just averages) is arguably the most important feature you want from a monitoring dashboard, so the weak support for quantiles is very limiting.

Veneur[2] addresses these use-cases for applications that use DogStatsD[3] by using clever data structures for approximate histograms[4] and approximate sets[5], but I believe its integration with Prometheus is limited and currently only one-way - there is a CLI app to poll Prometheus metrics and push them into Veneur, but there's no output sink for Veneur to write to Prometheus (or expose metrics for a Prometheus instance to poll).

It would be extremely useful to have something similar for Prometheus, either by integrating with Veneur or implementing those data structures as an extension to Prometheus.

[1] https://prometheus.io/docs/practices/histograms/

[2] https://github.com/stripe/veneur

[3] https://docs.datadoghq.com/developers/dogstatsd/

[4] https://github.com/stripe/veneur#approximate-histograms

[5] https://github.com/stripe/veneur#approximate-sets

otel is working on their events spec https://github.com/open-telemetry/community/issues/1688

1. Agreed. It's the sink and the house attached to it, and the docs are thin and confusing as a result.

2. I had a similar experience to you. I wanted to implement a simple heartbeat in our app to get an idea of usage numbers. This is surprisingly not possible, which greatly confuses me given the name of the project. The low engagement on my question put me off and I abandoned my OpenTelemetry planning completely. [1][2]

[1] https://github.com/open-telemetry/community/discussions/1598

One of the OpenTelemetry Project's many Special Interest Groups (SIG) is the OpenTelemetry Community Demo SIG which gives support to a set of instrumented backend microservices and a web frontend app that are primarily used to showcase how to instrument a distributed system using OpenTelemetry. The application's main focus is to demonstrate the implementation process to instrument an application no matter what programming language, platform, or operating system your team is using, as well as providing different approaching techniques (automatic and manual instrumentation, metrics, baggage). All of this while following the standards and conventions defined by the official OpenTelemetry Documentation. More about the specific requirements can be found here. At Tracetest, we have always focused on becoming part of and embracing the OpenTelemetry community. One of our goals this summer was to get more involved with a core OpenTelemetry project where we could provide a meaningful contribution. The OTel demo became the best match for achieving that goal as it would not only help the community, but we at Tracetest needed a good example to test and showcase what can be done with our tool. During the version 0.7 project cycle, we created two specific tickets to get us closer to the community and start looking for things to pick up: