promscale
charts
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promscale | charts | |
---|---|---|
18 | 88 | |
1,330 | 8,297 | |
-0.2% | 2.7% | |
0.0 | 10.0 | |
1 day ago | 3 days ago | |
Go | Smarty | |
Apache License 2.0 | 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.
promscale
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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)
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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.
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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
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A different and (often) better way to downsample your Prometheus metrics
(NB: Promscale team member)
Thanks for the positive feedback!
Is there anything in particular you are missing in Promscale to be used as a backend for multiple Prometheus instances?
We added support for multi-tenancy a couple of months ago (https://blog.timescale.com/blog/simplified-prometheus-monito...)
And thanks to a community contribution by 2nick on github Promscale can be integrated with Thanos :) (https://github.com/timescale/promscale/pull/664)
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Thanos Integration with Prometheus
No. No you can’t store Prometheus metrics in Postgres out of the box AFAIK. You’d need to run a service that provides a remote write endpoint to proxy metrics into Postgres. There’s probably a few open source projects out there similar to: https://github.com/timescale/Promscale
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TimescaleDB Raises $40M
(Timescale engineer here). We believe so and we have customers using us for just that. We haven't created our own product for that yet (as we have for metrics -- Promscale) but it is an idea we are playing with. You may want to look at our Promscale design doc[1] for ideas on table layout.
charts
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Coexistence of containers and Helm charts - OCI based registries
Both of these examples seem pretty obvious and something you wouldn’t mess up, but as your chart grows, so does your values.yaml file. A great example is the Redis chart by Bitnami. I encourage you to scroll through its values file. See you in a minute!
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Master Helm, Chart the Kubernetes Seas 🌊🧭🏴☠️
💡 The full details of helm charts can be referenced in their associated GitHub Repository.
- [Kubernetes] Comment déployez-vous un cluster Postgres sur Kubernetes en 2022?
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Dynamic Volume Provisioning in Kubernetes with AWS and Terraform
The actual reason that our pods are not coming up is found when we review the helm installation that we are trying to run. If you check the dependencies in the GitHub repository (https://github.com/bitnami/charts/blob/main/bitnami/drupal/values.yaml) you find out that persistent storage is enabled by default and set to 8Gi. Also, the helm package uses MariaDB and the database size is specified to a default of 8Gi, thus setting the minimum storage for this installation to be 16Gi.
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Experience setting up Spark and Hudi on Kubernetes
We're using https://github.com/bitnami/charts/tree/main/bitnami/spark, but I have heard good things about https://github.com/GoogleCloudPlatform/spark-on-k8s-operator as well. Hudi should not need any long running deployments as per the docs https://hudi.apache.org/docs/0.5.1/deployment/#deploying
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"helm crearte" command for bitnami charts/common Library?
Bitnami has its own scaffolding published at https://github.com/bitnami/charts/tree/main/template
i love the bitnami charts, now i'm at the point i want to write my own helm chart. (Openshift UI for Kubernetes packaged as a helm chart) I try to use the same structure and stuff as bitnami. I look for an "template" which i can start similar to the helm command 'helm create'. Is there something like this?At the moment i do a lot of copy of paste of other bitnami charts but this is kind of annoying. s. Bitnami Common Library
- How to configure apps that do not support env. vars?
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How to implement a distributed /etc directory using etcd and JuiceFS
To install etcd, you can refer to the official documentation and build a multi-node etcd cluster; you can also use the chart installer provided by Bitnami for etcd .
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Help finding docker base images
bitnami.com perhaps?
What are some alternatives?
thanos - Highly available Prometheus setup with long term storage capabilities. A CNCF Incubating project.
TimescaleDB - An open-source time-series SQL database optimized for fast ingest and complex queries. Packaged as a PostgreSQL extension.
kube-thanos - Kubernetes specific configuration for deploying Thanos.
prometheus - The Prometheus monitoring system and time series database.
helm-charts - A curated set of Helm charts brought to you by codecentric
VictoriaMetrics - VictoriaMetrics: fast, cost-effective monitoring solution and time series database
Telegraf - The plugin-driven server agent for collecting & reporting metrics.
oauth2-proxy - A reverse proxy that provides authentication with Google, Azure, OpenID Connect and many more identity providers.
pmacct - pmacct is a small set of multi-purpose passive network monitoring tools [NetFlow IPFIX sFlow libpcap BGP BMP RPKI IGP Streaming Telemetry].
renovate - Universal dependency automation tool.
kubegres - Kubegres is a Kubernetes operator allowing to deploy one or many clusters of PostgreSql instances and manage databases replication, failover and backup.