patroni
Grafana
Our great sponsors
patroni | Grafana | |
---|---|---|
19 | 378 | |
6,195 | 60,196 | |
1.9% | 1.3% | |
9.2 | 10.0 | |
10 days ago | 6 days ago | |
Python | TypeScript | |
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.
patroni
-
Citus is not ACID but Eventually Consistent
Citus doesn't provide fault tolerance. Each shard is a monolithic PostgreSQL. To reduce downtime on failures, you can protect each shard with a standby database. As this is a complex configuration, Patroni can help. For this lab I'll use the Citus+Patroni docker-compose-citus.yml from https://github.com/zalando/patroni.git:
-
How to create postgres cluster in docker swarm?
We have been using stolon + consul for years without issue in our swarm environments. It may also be possible with patroni.
-
Why PostgreSQL High Availability Matters and How to Achieve It
one of the solutions which made it pretty simple for us to run postgresql in a ha environment (mostly in k8s, but works standalone as well) is zalandos patroni: https://github.com/zalando/patroni it's really solid and worked for us for a few years already.
or for k8s their operator: https://github.com/zalando/postgres-operator (docker image: https://github.com/zalando/spilo) we've also tried other operators which were easier to get started, but they failed miserably (crunchyrolls operator is basically based on the zalando one)
-
Docker: Patroni + HAProxy + Etcd + PgBouncer
Hello. I am currently using this docker-compose model from Zalando repository. It does not include PgBouncer in its architecture by default. I've been trying to find a containerized implementation involving Patroni, HAProxy, Etcd and PgBouncer. I didn't find anything solid so far.
-
Can someone share experience configuring Highly Available PgSQL?
General purpose: Patroni - Set up your own etcd + HAProxy + Patroni + Postgres components and it'll generally manage itself after that.
- Patroni Version 3.0.0 Released
- Any self hostable postgres clustering, replication and fail over system?
-
Postgresql HA using repmgr and Keepalived
I don't have a great answer for you except that it sounds like you are trying to create your own version of patroni. Is there a good reason to not just use patroni?
-
Testing Patroni strict synchronous mode 👉🏻 you must handle invisible commit and read split brain
git clone https://github.com/zalando/patroni.git cd patroni docker build -t patroni . docker-compose up -d
-
Any recommandation Postgres Operator ?
I actually used Patroni on Openshift in my company. To be update with the latest version we created our helm chart.
Grafana
-
Golang: out-of-box backpressure handling with gRPC, proven by a Grafana dashboard
To help us visualize these scenarios, we'll build a Grafana Dashboard so we can follow along.
-
Monitoring, Observability, and Telemetry Explained
Visualization and Analysis: Choose a tool with intuitive and customizable dashboards, charts, and visualizations. A question to ask is, "Are the visualization features of this tool user-friendly and adaptable to our team's specific needs?" Tools like Grafana and Kibana provide powerful visualization capabilities.
-
4 facets of API monitoring you should implement
Prometheus: Open-source monitoring system. Often used together with Grafana.
- Grafana: Open and composable observability and data visualization platform
-
The Mechanics of Silicon Valley Pump and Dump Schemes
Grafana
-
Reverse engineering the Grafana API to get the data from a dashboard
Yes I'm aware that Grafana is open source but the method I used to find the API endpoints is far quicker than digging through hundreds of files in a codebase I'm not familiar with.
-
Building an Observability Stack with Docker
So, you will add one last container to allow us to visualize this data: Grafana, an open-source analytics and visualization platform that allows us to see traces and metrics simply. You can set Grafana to read data from both Tempo and Prometheus by setting them as datastores with the following grafana.datasource.yaml config file:
-
How to collect metrics from node.js applications in PM2 with exporting to Prometheus
In example above, we use 2 additional parameters: code (HTTP response code) and page (page identifier), which provide detailed statistics. For example, you can build such graphs in Grafana:
-
Root Cause Chronicles: Quivering Queue
Robin switched to the Grafana dashboard tab, and sure enough, the 5xx volume on web service was rising. It had not hit the critical alert thresholds yet, but customers had already started noticing.
-
Teach Yourself Programming in Ten Years (1998)
I completely agree but do feel it needs qualifying. The problems beginners run into aren't usually the same as the problems experienced devs run into when adopting a language new to them, but where I see the two overlap I know something is a serious hazard in a language.
Java as a first language: won't like the boilerplate but won't have any point of comparison anyway, will get a few NPEs, might use threads and get data races but won't experience memory unsafety.
Go as a first language: much less boilerplate, but will still get nil panics, will be encouraged to use goroutines because every tutorial shows off how "easy" they are, will get data races with full blown memory unsafety immediately.
Rust as a first language: `None` // no examples found
I think Go as a beginner language would be better if people were discouraged from using goroutines instead of actively encouraged (the myth of "CSP solves everything"), otherwise I think it needs much better tooling to save people from walking off a cliff with their goroutines. And no, -race clearly isn't it, especially not for a beginner.
And in one respect I've found Go more of a hazard for experienced devs than beginners: the function signature of append() gives you the intuition of a functional programming append that never modifies the original slice. This has literally resulted in CVEs[1] even by experienced devs, especially combined with goroutines. Beginners won't have an intuition for this and will hopefully check the documentation instead of assuming.
[1] https://github.com/grafana/grafana/security/advisories/GHSA-...
What are some alternatives?
pg_auto_failover - Postgres extension and service for automated failover and high-availability
Thingsboard - Open-source IoT Platform - Device management, data collection, processing and visualization.
stolon - PostgreSQL cloud native High Availability and more.
Apache Superset - Apache Superset is a Data Visualization and Data Exploration Platform [Moved to: https://github.com/apache/superset]
postgresql_cluster - PostgreSQL High-Availability Cluster (based on "Patroni" and DCS "etcd" or "consul"). Automating with Ansible.
Heimdall - An Application dashboard and launcher
stolon-chart - Kubernetes Helm chart to deploy HA Postgresql cluster based on Stolon
Wazuh - Wazuh - The Open Source Security Platform. Unified XDR and SIEM protection for endpoints and cloud workloads.
crunchy-proxy - PostgreSQL Connection Proxy by Crunchy Data (beta)
Thingspeak - ThingSpeak is an open source “Internet of Things” application and API to store and retrieve data from things using HTTP over the Internet or via a Local Area Network. With ThingSpeak, you can create sensor logging applications, location tracking applications, and a social network of things with status updates.
pgvector - Open-source vector similarity search for Postgres
uptime-kuma - A fancy self-hosted monitoring tool