portable_get_random VS VictoriaMetrics

To get cryptographically grade randomness you can use one of these C functions:

BSD, newer macOS, and GNU libc: int getentropy(void buffer, size_t length);

Linux 3.19+: ssize_t getrandom(void buf, size_t buflen, unsigned int flags);

iOS and macOS 10.7+: int SecRandomCopyBytes(SecRandomRef, size_t, uint8_t );

Fuchsia: void zx_cprng_draw(void* buffer, size_t buffer_size);

Any *nix: Read from "/dev/random" (or "/dev/urandom" under the assumption that your system has already enough entropy).

Windows: There are different functions/libraries depending on the Windows version and some of them are a complicated multi-step mess.

Some time ago I wrote a C library that abstracts that away just for fun: https://github.com/panzi/portable_get_random

VictoriaMetrics CTO here.

The referred library is the official OpenTelemetry package for reading metrics in Go language [1] - more details are available at [2].

Note that we at VictoriaMetrics like the idea of unified observability standard like OpenTelemetry. The issue is in the current otel implementation. It is too bloated and very inefficient. This contradicts to our experience with observability cases, which need very optimized format for metrics' transfer in order to reduce costs on CPU and network traffic needed to transfer and process these metrics.

VictoriaMetrics continues investing in OpenTelemetry by providing integration docs [3] and improving the existing functionality for otel metrics' ingestion [4].

[1] https://github.com/open-telemetry/opentelemetry-proto-go

[2] https://github.com/VictoriaMetrics/VictoriaMetrics/pull/2570...

[3] https://docs.victoriametrics.com/guides/getting-started-with...

[4] https://github.com/VictoriaMetrics/VictoriaMetrics/issues/60...

Victoria Metrics

VictoriaMetrics is primarily a time-series database designed for efficiently storing and querying time-series data. It is often used as a back-end data store for time-series data generated by monitoring systems like Prometheus. VictoriaMetrics excels at handling large volumes of time-series data, offering efficient storage and query capabilities.

Not sure I follow since there are very competitive tools written in Go such as https://victoriametrics.com for an example in this space.

Did you try VictoriaMetrics [1] and vmagent [2]? It is a single self-contained binary without external dependencies. It requires relatively low amounts of CPU, RAM, disk space and disk IO, and it runs on ARM.

[1] https://github.com/VictoriaMetrics/VictoriaMetrics/

[2] https://docs.victoriametrics.com/vmagent.html

https://github.com/VictoriaMetrics/VictoriaMetrics#cardinali...

If I understanding correctly, it deal with high cardinality by dropping data, the operators need to monitor for this and adjust their data to lower the cardinality.

VictoriaMetrics

You shouldn't unless you want to use the new open source standard for telemetry. You won't benefit from simplicity or performance improvements. It would be quite the opposite. You can check what is the actual cost of open telemetry adoption here [0]

But if you ever decide to go this path - VictoriaMetrics supports OpenTelemetry protocol for metrics [1]

[0] https://github.com/VictoriaMetrics/VictoriaMetrics/pull/2570

[1] https://docs.victoriametrics.com/Single-server-VictoriaMetri...