- Consider decoupling your collector from whatever is consuming your traces with something like kafka. Traces can be pretty heavy and it can be tricky to scale collectors. If something goes down, it's probably a good idea to continue writing the traces to queue or topic.
- https://www.otelbin.io is a nice little tool to help with collector configuration
My ideal setup would be to just write SQL on telemetry data and plot dashboards / set alerts.
Also, thoughts on Vector vs otel agent?
HyperDX is just a lot better, sure a few papercuts but they got all the important stuff right imo.
Can you share which version of SigNoz did you try or what time frame? We recently made a lot of improvement in how you can host SigNoz including support for Postgres and better docs fro self hosting corretcly - https://signoz.io/docs/collection-agents/get-started/
Don’t use vector or otel-agent. Add a materialized view in clickhouse to transform data and swap HyperDX to load from your view (in the UI.)
IMO, with the current tech, it entirely depends on what data you're talking about.
For metrics and traces, I would use the OTel collector personally. You will have much more flexibility and it's pretty easy to write custom processors in Go. Support for traces is quite mature and metrics isn't far off. We've been running collectors for production scale of metric and trace ingest for the past couple of years, on the order of 1m events/sec (metric datapoints or spans). You mentioned low volume so that's less important, but I just wanted to mention in case others find this comment.
Logs are a bit different. We looked in to this in the past year. Vector has emerging support for OTLP but it's pretty early. Still, I bet it's pretty straightforward if your backend can ingest via OTLP. Our main concern with running the otel-collector as the log ingest agent was around throughput/performance. Vector is battle-tested, otel is still a bit early in this space. I imagine over time the gap will be closed but I would probably still reach for Vector for this use-case for higher scale. That said, YMMV and as with any technical decision, empirical data and benchmarking on your workloads will be the best way to determine the tradeoffs.
For your scale you could probably get away with an OTel collector daemonset and maybe a deployment with the Target Allocator (to allocate Prometheus scrapes) and call it a day :)
It's been solid, but the UI is kind of clunky and a little buggy here and there. Dashboards are tricky to setup too. But it has no dependencies, and was easy to setup, and I couldn't find anything else that handled logs too.
PS: I am one of the maintainers
Also, I wasn't sure if Zookeeper was mandatory even for a single-server SigNoz install?
SigNoz UI certainly looks more polished tho!
ClickStack/HyperDX is a polished OOTB stack that has an all in one image you can deploy to get started, so you don't need to worry about the ClickHouse side until you need to really scale (which is where ClickHouse really shines).
The UI is predictably an annoying mess, but that's the case with EVERY tracing solution I've tried. Very much including SigNoz.
Another issue is the complexity of switching between filtered views. A very useful primitive that you and Uptrace are missing: "show this event within the surrounding context". CloudWatch has it.
The other main overarching issue is ease of navigation and switching between contexts. You are actually somewhat better than Uptrace because I can actually cut&paste URLs on most of the pages and send them to my colleague over Slack.
But you make up for that by having bad search in traces (e.g. I can't just search all the traces with the word "UploadDoc" somewhere in them). Here's how Uptrace works: https://imgur.com/a/UWSdIEt
Your "Trace View" is ridiculous: I can't resize columns, I can't drag them to change the order, I can't even _show_ additional columns even though I can sort by them: https://www.loom.com/share/d5fa401384d94959978c0bb2be9010a5?...
Then you also are freaking annoying with the UI. I don't even care about everything getting extra-bloated. It's just par for the course for the modern UI vibe-based design.
But I get almost physically sick from these ridiculous popups: https://www.loom.com/share/21f5efdae8b84b12ba09c45cd2fa0855?...
Honestly, I think that most observability stacks (very much including SigNoz) are focusing on looking hip with cool dashboards. They totally suck when I need to dig deep into logs to find what happened.
> My first "sniff test" for observability platforms is a tool to quickly jump to a given trace/span by ID.
You should be able to do this in SigNoz https://www.loom.com/share/71a2a95b76584b3983d9eeebb60ac420?...
> "show this event within the surrounding context"
we have this in the context logs. does this solve your use case or you mean something else? https://www.loom.com/share/9039afd5c4bf45e7b357a22c9943bb32?...
>But you make up for that by having bad search in traces
Did you mean for this to search across all attributes in spans or when you know which attribute you want to search in? If later, than you can do this through our query builder even today.
Your feedback on "Trace View" is fair. We are planning some improvements on that
This isn't a lot to go on.
The important thing is what you're trying to instrument - hosts, applications, network, microservices, all of the above? (And then whether you want a few weeks retention, or keeping years worth.)
Grafana in front of Prometheus with node-exporter or telegraf (it can expose in prometheus mode) on the clients -- will tick a lot of boxes and is fast to get going.
Grafana in front of InfluxDB + telegraf is similar, but personally I find PromQL easier than InfluxQL.
> ... write SQL on telemetry data and plot dashboards / set alerts.
Read up about the design of TSDBs and log / tracing datastores - their design & intent heavily influences their query languages.