Viewing profile — ankitnayan

and here query builder helps by making it earier to do cross-signal joins and subqueries. I see that is upcoming in SigNoz https://signoz.io/blog/query-builder-v5/#what-we-couldnt-…

You might also like the interactive dashboard feauture that was released in the recent launch week https://www.youtube.com/watch?v=YQTQXq0F5Iw&ab_channel=SigNo...

I think all of us agree that OpenTelemetry's end-goal of making Observability vendor neutral is futuristic and inevitable. We can complain about it being hard to get started, bloat…

you can add https://github.com/open-telemetry/opentelemetry-collector-co... at signoz's otel-collector which will scrape your service's endpoint periodically. If your service is do…

Interesting post. How do you apply restrictions on your queries? Otherwise a few concurrent queries scanning huge data or being slow due to groupby, etc can slowdown the system. Al…

However the CPU and memory resources used are very minimalist. On no load conditions, it takes around 0.3-0.5 CPUs and 1.5-2GB RAM

I have seen it ingest 500K events/s. How did you conclude the poor perf?

When handling surges of the order of 10x, it's much more difficult to scale the different components of loki than to write them to Kafka/Redpanda first and consume at a consistent …

it's very hard to think s3 work as a buffer. Every datastore can work for almost all storage usecases buffer/queue/db when the scale is low but the latter were designed to work at …

https://www.confluent.io/blog/exactly-once-semantics-are-pos...

Caching is to improve read performance whereas Kafka is used to handle ingest volume. I couldn't correlate the Grafana articles shared

Hi Prabhat, I am one of the maintainers at SigNoz. Nice to see OpenObserve's belief that the future of Observability should be OpenSource. We chose clickhouse rather than building …

An OpenSource alternative to DataDog built on ClickHouse database which is also native to OpenTelemetry https://github.com/SigNoz/signoz

https://github.com/SigNoz/signoz/blob/main/LICENSE

Yes...we are avoiding join altogether. Currently we used join in timeseries but we are probably moving away from that due to perf. Single table is amazingly fast

Basically, the choice of DB is different, relational vs analytical DB. IMO clickhouse should be better at ingestion rate and aggregation queries.

What does your schema for metrics look like? Using materialised views? I am particularly interested in storing metrics with labels(key/val pairs) Eg, Prometheus metrics. You can't …

I would love to see some benchmarks when making such a heavy claim. I would be interested in knowing performance of ingestion rate, query timings and resource usage.

We have recently been talking to a few companies in HealthCare and Fintech, and it seems they have strong needs for data to remain on-premise. One of such verticals in the company …

hmm..got your point. We shall definitely look into other queuing system to be integrated as interface. Trying to understand better, what's a super simple dev setup like (to get the…

Thanks, feel free to reachout to us if you have any concerns or want to discuss in general. We are always eager to learn and help.

really liked the way you put things to clarity. Thanks for these inputs and suggestions, will definitely think harder on this.

Nothing wrong there. If enough users want, we can add clickhouse also