veneur
loki
veneur | loki | |
---|---|---|
2 | 80 | |
1,714 | 22,213 | |
0.1% | 1.4% | |
3.5 | 9.9 | |
about 1 month ago | 5 days ago | |
Go | Go | |
MIT License | GNU Affero General Public License v3.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
veneur
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OpenTelemetry in 2023
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
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Launch HN: Opstrace (YC S19) – open-source Datadog
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
loki
- Loki 3.0 Released
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List of your reverse proxied services
I also needed to make a small patch to Promtail to make this work: https://github.com/grafana/loki/pull/10256
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About reading logs
We don't pull logs, we forward logs to a centralized logging service.
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loki VS openobserve - a user suggested alternative
2 projects | 30 Aug 2023
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Logs monitoring with Loki, Node.js and Fastify.js
Over the past few months, I've been spending a lot of time creating dashboards on Grafana using Loki for MyUnisoft (the company I work for).
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OpenObserve: Open source Elasticsearch alternative in Rust for logs. 140x lower storage cost
For log systems you generally don't migrate data. Logs lose value over time. What you want to do is to go ahead and start ingesting data into the new system (OpenObserve in this case) and slowly, the data in the old system will become stale and then you can retire it. However if you need to export logs anyhow, there is no straightforward way in loki to do this. You could run a script to query loki and export it to a file. If found this thread with a sample script - https://github.com/grafana/loki/issues/409
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Config files of snaps?
That snap is woefully out of date. The upstream repo was recently updated to 2.8.2, but the snap stable channel has 2.4.1 from 18 months ago. https://github.com/grafana/loki/releases/tag/v2.8.2
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i need to visualize all logs from remote dir
Loki
- Loki Helm charts that use DynamoDB
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I can't recommend serious use of an all-in-one local Grafana Loki setup
I installed promtail a few weeks back and I ran into this bug, that has been outstanding for months: https://github.com/grafana/loki/issues/8663 (e.g. a fix had been written but had not been released):
Due to a buffering issue, Loki would exit in case of configuration error without printing any error message or anything at all
There is definitely something weird about how the project is run.
What are some alternatives?
opstrace - The Open Source Observability Distribution
ClickHouse - ClickHouse® is a free analytics DBMS for big data
cortex - A horizontally scalable, highly available, multi-tenant, long term Prometheus.
fluent-bit - Fast and Lightweight Logs and Metrics processor for Linux, BSD, OSX and Windows
Cortex - Cortex: a Powerful Observable Analysis and Active Response Engine
Zabbix - Real-time monitoring of IT components and services, such as networks, servers, VMs, applications and the cloud.
influxdb-apply - Define InfluxDB users and databases with a yaml file.
VictoriaMetrics - VictoriaMetrics: fast, cost-effective monitoring solution and time series database
b3-propagation - Repository that describes and sometimes implements B3 propagation
ElastiFlow - Network flow analytics (Netflow, sFlow and IPFIX) with the Elastic Stack
skywalking - APM, Application Performance Monitoring System
loki-multi-tenant-proxy - Grafana Loki multi-tenant Proxy. Needed to deploy Grafana Loki in a multi-tenant way