openobserve VS opentelemetry-proto

Lot of interesting OSS observability products coming out in recent years. One of the more impressive(and curious for many reasons) IMHO is OpenObserve: https://github.com/openobserve/openobserve .

As opposed to just a stack, they are implementing just about the whole backend shebang from scratch.

in case it matters to others, https://github.com/openobserve/openobserve/tree/v0.7.0 is the last Apache2 licensed copy before they went AGPL with 0.7.1

https://github.com/openobserve/openobserve/blob/v0.7.0/.env.... is some "onoz" for me, but just recently someone submitted https://github.com/aenix-io/etcd-operator to the CNCF sandbox so maybe things have gotten better around keeping that PoS alive

eCharts is awesome. We moved from plotly after using it for several months to echarts at https://github.com/openobserve/openobserve and are super happy.

Wouldn't make more sense to have the same observability stack on production and development? For instance, open-observe is also a single binary that provides UI for logs, metrics and traces, although every log producer would have to be properly configured and routing to it.

Another idea: maybe chrome dev-tools could be repurposed to display server logs instead of client logs, somehow [2].

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1: https://github.com/openobserve/openobserve

2: https://chromedevtools.github.io/devtools-protocol/

It doesn't read from files unfortunately, but https://openobserve.ai/ is very easy to set up locally (single binary) and send otel logs/metrics/traces to.

Here's how I run it locally for my little shovel project - https://github.com/bbkane/shovel#run-the-webapp-locally-with... .

Also linked from that README is an Ansible playbook to start OpenObserve as a systems service on a Linux VM.

Alternatively, see the shovel codebase I linked above for a "stdout" TracerProvider. You could do something like that to save to a file, and then use a tool to prettify the JSON. I have a small script to format json logs at https://github.com/bbkane/dotfiles/blob/2df9af5a9bbb40f2e101...

Implement a monitoring stack, or openobserve for an all-in-one package.

I would recommend you take a look at OpenObserve (https://github.com/openobserve/openobserve ). It's free and open source and can do all you asked and more with far lower resource utilization. It's the easiest to run of any log system that you can find. Can capture windows and linux logs. Also compresses them heavily (30-60x, YMMV). 100 GB ingested logs can be 3 GB stored.

I have used https://github.com/openobserve/openobserve in several hobby projects and liked it. It's an all-in-one solution. It's likely less featureful than many others but a single binary and everything in one place pulled me in and worked for me so far.

Not affiliated, I just like the tool.

A good one. A lot is being built on top of clickhouse. I can count at least 3 if not more (hyperdx, signoz and highlight) built on top of clickhouse now.

We at OpenObserve are solving the same problem but a bit differently. A much simpler solution that anyone can run using a single binary on their own laptop or in a cluster of hundreds of nodes backed by s3. Covers logs, metrics, traces, Session replay, RUM and error tracking are being released by end of the month) - https://github.com/openobserve/openobserve

Maybe, you are asking yourself: "But I already had instrumented my applications with vendor-specific libraries and I'm using their agents and monitoring tools, why should I change to OpenTelemetry?". The answer is: maybe you're right and I don't want to encourage you to update the way how you are doing observability in your applications, that's a hard and complex task. But, if you are starting from scratch or you are not happy with your current observability infrastructure, OpenTelemetry is the best choice, independently of the backend telemetry tool that you are using. I would like to invite you to take a look at the number of exporters available in the collector contrib section, if your backend tracing tool is not there, probably it's already using the Open Telemetry Protocol (OTLP) and you will be able to use the core collector. Otherwise, you should consider changing your backend telemetry tool or contributing to the project creating a new exporter.

Here's the example payloads for OTLP over JSON and example of how to ingest them: https://github.com/open-telemetry/opentelemetry-proto/tree/m...

An OTLP receiver can receive data via gRPC or HTTP using the OTLP format. There are advanced configurations that you can enable via the YAML file.

Cerbos fully transitioned from OpenCensus to OpenTelemetry, a move that significantly boosts our metrics and tracing capabilities. This shift allows for more efficient integration with a variety of observability products supporting the OpenTelemetry protocol (OTLP) but also offers the flexibility to use push metrics and fine-tune trace sampling. With this update, configuration through the tracing block in Cerbos files is deprecated in favor of using OpenTelemetry environment variables.

Networking is Easy (Really!) Since you install the agent directly into the environment where you are running your application, there is no complex networking. When developing in localMode, the agent listens on the common OpenTelemetry Line Protocol (OTLP) on ports 4317 & 4318 automatically.

Oh nice, thank you (and also solumos) for the links! It looks like oteps/pull/171 (merged June 2023) expanded and superseded the opentelemetry-proto/pull/346 PR (closed Jul 2022) [0]. The former resulted in merging OpenTelemetry Enhancement Proposal 156 [1], with some interesting results especially for 'Phase 2' where they implemented columnar storage end-to-end (see the Validation section [2]):

* For univariate time series, OTel Arrow is 2 to 2.5 better in terms of bandwidth reduction ... and the end-to-end speed is 3.1 to 11.2 times faster

* For multivariate time series, OTel Arrow is 3 to 7 times better in terms of bandwidth reduction ... Phase 2 has [not yet] been .. estimated but similar results are expected.

* For logs, OTel Arrow is 1.6 to 2 times better in terms of bandwidth reduction ... and the end-to-end speed is 2.3 to 4.86 times faster

* For traces, OTel Arrow is 1.7 to 2.8 times better in terms of bandwidth reduction ... and the end-to-end speed is 3.37 to 6.16 times faster

[0]: https://github.com/open-telemetry/opentelemetry-proto/pull/3...

[1]: https://github.com/open-telemetry/oteps/blob/main/text/0156-...

[2]: https://github.com/open-telemetry/oteps/blob/main/text/0156-...

We then modified the benchmark to encode our example data which is an opentelemetry trace data.