promscale
Telegraf
promscale | Telegraf | |
---|---|---|
18 | 114 | |
1,330 | 15,741 | |
- | 0.8% | |
0.0 | 9.9 | |
over 1 year ago | 3 days ago | |
Go | Go | |
Apache License 2.0 | MIT License |
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.
promscale
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Promscale Deprecation
Now that Promscale has been deprecated, what are the other ideal means of self-hosted long term Prometheus storage?
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What do you use when you have to store high cardinality metrics?
Oh wow, I browsed the project just a few weeks ago, didn't see it then. I see the deprecation is recent (https://github.com/timescale/promscale/issues/1836)
- Promscale Has Been Discontinued
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Show HN: SigNoz – open-source alternative to DataDog, NewRelic
They say:
> if you want to have a seamless experience between metrics and traces, then current experience of stitching together Prometheus & Jaeger is not great.
But I wonder if using Promscale https://github.com/timescale/promscale would make Prometheus & Jaeger not such a big problem as SigNoz imply.
Promscale readme:
> Promscale is a unified metric and trace observability backend for Prometheus, Jaeger and OpenTelemetry built on PostgreSQL and TimescaleDB.
Either way, SigNoz seems interesting indeed. And am glad to see that SigNoz supports OpenTelemetry.
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Timescale raises $110M Series C
Hi! So the team is over 100 at this point, but engineering effort is spread across multiple products at this point.
The core timescaledb repo [0] has 10-15 primary engineers (although we are aggressively hiring for database internal engineers), with a few others working on DB hyperfunctions and our function pipelining [1] in a separate extension [2]. I think generally the set of folks who contribute to low-level database internals in C is just smaller than other type of projects.
We also have our promscale product [3], which is our observability backend powered by SQL & TimescaleDB.
And then there is Timescale Cloud, which is obviously a large engineering effort (most of which does not happen in public repos).
And we are hiring. Fully remote & global.
https://www.timescale.com/careers
[0] https://github.com/timescale/timescaledb
[1] https://www.timescale.com/blog/function-pipelines-building-f...
[2] https://github.com/timescale/timescaledb-toolkit
[3] https://github.com/timescale/promscale ; https://github.com/timescale/tobs
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Tools for Querying Logs with SQL
Promscale is a connector for Prometheus, one of the leading open-source monitoring solutions. Promscale is developed by Timescale, a time series database with full compatibility to Postgres. Since logs are time series events, Timescale developed Promscale to ingest events from Prometheus and make them available in SQL. You can install Promscale in numerous ways.
- New release Promscale
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Can Apache Druid replace Thanos? Can they complement themself?
In case it helps, Promscale (from Timescale) offers long-term storage for Prometheus data and supports both PromQL and SQL queries. Here's the project page: https://www.timescale.com/promscale/ and the repo is here https://github.com/timescale/promscale It also support OpenTelemetry tracing if that's of interest.
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Benchmarking: TimescaleDB vs. ClickHouse
At first, let's give the definition of `time series`. This is a series of (timestamp, value) pairs ordered by timestamp. The `value` may contain arbitrary data - a floating-point value, a text, a json, a data structure with many columns, etc. Each time series is uniquely identified by its name plus an optional set of {label="value"} labels. For example, temperature{city="London",country="UK"} or log_stream{host="foobar",datacenter="abc",app="nginx"}.
ClickHouse is perfectly optimized for storing and querying of such time series, including metrics. That's true that ClickHouse isn't optimized for handling millions of tiny inserts per second. It prefers infrequent batches with big number of rows per each batch. But this isn't the real problem in practice, because:
1) ClickHouse provides Buffer table engine for frequent inserts.
2) It is easy to create a special proxy app or library for data buffering before sending it to ClickHouse.
TimescaleDB provides Promscale [1] - a service, which allows using TimescaleDB as a storage backend for Prometheus. Unfortunately, it doesn't show outstanding performance comparing to Prometheus itself and to other remote storage solutions for Prometheus. Promscale requires more disk space, disk IO, CPU and RAM according to production tests [2], [3].
[1] https://github.com/timescale/promscale
[2] https://abiosgaming.com/press/high-cardinality-aggregations/
[3] https://valyala.medium.com/promscale-vs-victoriametrics-reso...
Full disclosure: I'm CTO at VictoriaMetrics - competing solution for TimescaleDB. VictoriaMetrics is built on top of architecture ideas from ClickHouse.
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Zabbix anything I should know?
Promscale + TimescaleDB
Telegraf
- Show HN: MavLink Input Plugin for Telegraf
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Rust Dependencies Scare Me
Wow, that's massive. I guess it's inevitable that a popular piece of open-source software for end-users will be compelled to accrue dependencies due to popular demand for features that require them.
I feel Telegraf made a good compromise: out of the box, it comes with a _ton_ of stuff[1] to monitor everything, but they make it possible to build only with pieces that you need via build tags, and even provide a tool to extract said tags from your telegraf config[2]. But lots of supply-chain security stuff assume everything in go.mod is used, so that can results in a lot of noise.
[1] https://github.com/influxdata/telegraf/blob/master/go.mod
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Hardware Metrics Collection with IOT Devices
Telegraf is a highly customizable metrics agent and aggregator.
- How I would automate monitoring DNS queries in basic Prometheus
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Current network throughput from total byte value?
The Telegraf (v1.27.3) Net Input Plugin only reports total numbers - i.e., total bytes received by an interface.
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Filestat working but need help with output
I need some help with Filestat - https://github.com/influxdata/telegraf/tree/master/plugins/inputs/filestat
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Telegraf Deployment Strategies with Docker Compose
Telegraf’s Secretstores Plugin implementation on GitHub
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Right way to link containers on host vs custom network.
That's the thing, I do need network_mode: host on telegraf in order to get host network statistics. See here or here
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Telegraf Inputs.SMART
After screwing around with it for a while, I was able to get inputs.smart working... but I'm not thrilled with the answer. According to this in order for you to get the SMART data inside a container you need to edit the sudoers file inside the container.
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Learnings from integrating JMX based metrics from Java applications into time series databases
I’ve been using the Jolokia agent with telegraf to push JVM metrics into InfluxDB (among other things). I think it can be used with Prometheus too.
What are some alternatives?
TimescaleDB - A time-series database for high-performance real-time analytics packaged as a Postgres extension
Collectd - The system statistics collection daemon. Please send Pull Requests here!
kube-thanos - Kubernetes specific configuration for deploying Thanos.
prometheus - The Prometheus monitoring system and time series database.
pmacct - pmacct is a small set of multi-purpose passive network monitoring tools [NetFlow IPFIX sFlow libpcap BGP BMP RPKI IGP Streaming Telemetry].
node_exporter - Exporter for machine metrics