Meltano Graduates to Version 1.0

Today we’re happy to announce Meltano’s version incrementation to 1.0, signifying a point of product maturity that offers a solid end-to-end user experience to extract data and turn it into dashboards.

If you haven’t used Meltano yet you can get started in 60 seconds or less by installing Meltano’s 1-Click App in the DigitalOcean Marketplace and then walk through the Getting Started Guide. When you use our link and create a new DigitalOcean account, you will receive $50 of credit over the first 30 days.

We all encourage all existing Meltano users to upgrade to version 1.0

Meltano began as an internal skunkworks project at GitLab ~18 months ago, and over the past 6 months the core team and contributor community have worked together to reach this milestone. We are grateful for all these contributions, and appreciate our colleagues inside GitLab for their warm support for our unconventional “internal startup” approach (more on this in a future post!).

What It Means to Make It To “V1”

Unlike GitLab, which began with a focus on version control and gradually made the transition to managing the entire DevOps lifecycle, the vision for Meltano has been about simplifying the DataOps workflow from day one. With this big vision, we have grappled with the complexity that comes from making choices on behalf of users and needing to satisfy a range of technical know-how levels from experienced data engineer and scientist to freshly minted analyst.

At the beginning of July, we established key criteria for reaching v1.0 to address these challenges and deliver a working product:

  • UI-based product that is fully usable with the mouse, no command line or coding required (DigitalOcean 1-Click App)
  • End-to-end experience that takes a user from first data extraction to dashboard visualization in minutes (YouTube speedruns)
  • Stable release we can guarantee backward compatibility to and reliable support for (logging, upgrade from the UI, extensively dogfooded and documented with all major bug resolved)
  • Do not invest much more in proprietary Meltano tech for Meltano Model and Meltano Analyze, we should find open source solutions for these phases and integrate them instead

While this might sound like a simple list on its face, the surface area of Meltano as a data pipeline management tool is already large enough that the work required to ensure an end-to-end experience was the bulk of the heavy lifting.

We put the focus on these areas above all else because our core KPI to measure whether Meltano is working is our ability to consistently grow MAUI. With the release of Meltano v1.0 we now offer a product experience worth coming back for and we can’t wait to see what you’ll create!


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Published by Danielle Morrill

General Manager of Meltano at GitLab