grouparoo VS Grafana

Reverse ETL is on AirByte's roadmap under the "Future / Not prioritized" section. I wanted to use Grouparoo as a short term solution, but the repo was archived and I think they stopped taking new cloud customers (unknown if this is wrong/outdated).

There are other tools that we will have to adopt in the future but haven’t yet due to lack of necessity. Specifically, one category that is popular in modern data stacks is Reverse ETL (Hightouch, Census, or Grouparoo). We currently don’t have a usecase for piping data back into 3rd party tools but it will definitely come up in the future.

Reverse ETL: Grouparoo, Castled

Grouparoo, the open source Reverse ETL tool we are building, does all of these things. https://www.grouparoo.com

Ingestion / ETL: Airbyte, Singer, Jitsu Transformation: dbt Orchestration: Airflow, Dagster Testing: GreatExpectations Observability: Monosi Reverse ETL: Grouparoo, Castled Visualization: Lightdash, Superset

Grouparoo | Remote (US) | Remote-OK | https://www.grouparoo.com

Grouparoo is a venture-backed software company building open source data tools that make data reliable, accessible, and actionable. We’re empowering teams to make great customer experiences, driven by data. While engineering teams have gotten good at storing and generating data about their customers, it’s rare that this data is used to its full potential in external applications. Grouparoo makes these integrations easy by providing a framework for defining your customer data and reliably syncing it to external tools.

To learn more about who we are, our engineering culture, and whether this is the right place for you, read our Key Values profile: https://www.keyvalues.com/grouparoo

Here are our open roles:

- Senior Backend / Lead Engineer: https://jobs.lever.co/grouparoo/6ba485d1-a5a4-41f0-9fa5-920a...

- Developer Advocate: https://jobs.lever.co/grouparoo/5e1531b4-7ec8-4c10-8e52-fc23...

Tech Stack: TypeScript / Javascript / Node.js, ActionHero, React + Next.js, Postgres & Redis, and whole lot of third-party APIs!

Congrats on the launch! Hightouch looks great and this need is real. Things seem to be going well, so I don't think I'm taking too much away by mentioning that we have been been working on Grouparoo, an open source alternative that solves similar pain points.

A few differences: git developer workflow focused (branches, CI, PRs, etc), ability to self host, segmentation in destinations (tagging people in mailchimp based on rules, for example)

https://www.grouparoo.com

We are building Grouparoo. Obviously, it's a biased sample but we are seeing a few trends at play.

Has anyone heard or used of reverse etl or Hightouch or open sourced Grouparoo?

Monitoring application logs is a crucial aspect of the software development and deployment lifecycle. In this post, we'll delve into the process of observing logs generated by Docker container applications operating within HashiCorp Nomad. With the aid of Grafana, Vector, and Loki, we'll explore effective strategies for log analysis and visualization, enhancing visibility and troubleshooting capabilities within your Nomad environment.

To help us visualize these scenarios, we'll build a Grafana Dashboard so we can follow along.

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.

Prometheus: Open-source monitoring system. Often used together with Grafana.

Grafana

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.

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:

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:

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.