Telegraf
timescale-analytics
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Telegraf | timescale-analytics | |
---|---|---|
111 | 8 | |
13,753 | 336 | |
1.0% | 4.5% | |
9.9 | 6.0 | |
4 days ago | 7 days ago | |
Go | Rust | |
MIT License | GNU General Public License v3.0 or later |
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.
Telegraf
- 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.
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open source network monitoring tool
Do you mean Telegraf?
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Help with reading modbus using telegraf
I have two devices; both are connected to a Raspberry Pi using a USB converter as Slave 1 and 2. I want to get some readings using Telegraf software https://github.com/influxdata/telegraf/tree/release-1.26/plugins/inputs/modbus (happy to try any other linux software), but I'm having trouble (I'm seriously confused to be honest) with byte_order, data_type, and input register addresses.
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Telegraf processor plugin.
Yeah i think you can use the grok processor, docs found here: https://github.com/influxdata/telegraf/tree/master/plugins/parsers/grok
timescale-analytics
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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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Function pipelines: Building functional programming into PostgreSQL
(NB: Post author here)
This is in the TimescaleDB Toolkit extension [1] which is licensed under our community license for now and it's not available on DO. It is available on our cloud service fully managed. You can also install it and run it for free yourself.
[1]: https://github.com/timescale/timescaledb-toolkit
- How percentile approximation works (and why it's more useful than averages)
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How PostgreSQL aggregation works and how it inspired our hyperfunctions’ design
Absolutely! We're actually developing a lot of that: https://github.com/timescale/timescaledb-toolkit/tree/main/d...
A number of the things you're looking for we've done experimentally and we'll be stabilizing over the next few releases. So we'd love some feedback while we're still able to futz with the API without making breaking changes.
But the two you're asking about are, I think, going to be covered by hyperloglog (we just reimplemented the internals with HLL++) and stats_agg family of functions, which have both 1D (which will give you avg, stddev, variance, etc) and 2D (co-variance, slope, intercept, x-intercept etc as well as all the 1D functions).
Would also love issues if you think we're missing other stuff, going to be generalizing this and want to make it useful for folks.
(NB: Post author here.)
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Postgres downsampling performance
If you know that you're going to be doing downsampling at the hourly level then a continuous aggregate on the hour is probably a good idea. We're also building some functions to make some of the continuous aggregate stuff for these sorts of cases easier/more accurate in more cases, especially if you need things like exact averages when you don't have the same number of points in an hour and want to re-aggregate on top of the continuous agg. See: https://github.com/timescale/timescale-analytics/pull/141/files
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TimescaleDB Raises $40M
Fair point about adaptive chunking. You sound like a long-term user!
There is always a trade-off between getting features to users quickly to experiment and incrementally improve, versus doing it always very conservatively.
When we launched adaptive chunking (introduced in 0.11, deprecated in 1.2), we explicitly marked it as beta and default off, to hopefully reflect that. [1]
The approach we are now taking with Timescale Analytics [2] is to have an explicit distinction between experimental features (which will be part of a distinct"experimental" schema in the database, and must be expressly turned on with appropriate warnings) and stable features. Hopefully this can help find a good balance between stability and velocity, but feedback welcome!
[1] https://github.com/timescale/timescaledb/releases/tag/0.11.0
[2] https://github.com/timescale/timescale-analytics/tree/main/e...
What are some alternatives?
prometheus - The Prometheus monitoring system and time series database.
orioledb - OrioleDB – building a modern cloud-native storage engine (... and solving some PostgreSQL wicked problems)  🇺🇦
VictoriaMetrics - VictoriaMetrics: fast, cost-effective monitoring solution and time series database
TimescaleDB - An open-source time-series SQL database optimized for fast ingest and complex queries. Packaged as a PostgreSQL extension.
Collectd - The system statistics collection daemon. Please send Pull Requests here!
promscale - [DEPRECATED] Promscale is a unified metric and trace observability backend for Prometheus, Jaeger and OpenTelemetry built on PostgreSQL and TimescaleDB.
pfSense-Dashboard - A functional and useful dashboard for pfSense that utilizes influxdb, grafana and telegraf
pgx - Build Postgres Extensions with Rust! [Moved to: https://github.com/tcdi/pgrx]
OPNsense-Dashboard - A functional and useful dashboard for OPNsense that utilizes InfluxDB, Grafana, Graylog, and Telegraf.
t-digest - A new data structure for accurate on-line accumulation of rank-based statistics such as quantiles and trimmed means
tcollector - Data collection framework for OpenTSDB
tsbs - Time Series Benchmark Suite, a tool for comparing and evaluating databases for time series data