What’s the point: Databricks, Docker, AWS Chatbot, Azure, and GitLab

What's the point

The second release of the Databricks Runtime with Conda (Beta) is out. Version 5.5 comes with a variety of upgraded packages as well as some UX improvements. The latter include support for YAML files when using Databricks Library Utilities to customise Python environments, better isolation among environments scoped to notebook sessions, and an easier installation process. On top of that running commands right after starting is supposed to be much faster now.

Docker starts Technology Partner Program

To strengthen the bonds to its partners and give customers an easier way of recognising the formal partnerships Docker has, the company has started a three-leveled Docker Technology Partner Program. It distinguishes between verified, professional, and premier partners, with premier signifying the “deepest level of integration with Docker Enterprise”. 

To achieve this, certified tech has to undergo a “category specific technology review”, while those happy with the professional label will only have to run through the regular certification process for Docker Enterprise with their products. Partners sporting the verified status “have engaged with Docker directly” (bit vague, hm?) and release under a verified publisher account on Docker Hub.

AWS becomes communicative with Chatbot service

AWS has introduced an AWS Chatbots beta into its service offering, enabling teams to receive notifications from other portfolio products and execute commands in Slack and Amazon Chime.

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The preview can get notifications from Amazon CloudWatch and GuardDuty, as well as AWS Health, Budgets, Security Hub, and CloudFormation. An example walkthrough on how to set the whole thing up can be found in the introductory blog post.

Azure tries to speed up pipeline work with new previews

Users of Azure Pipelines can now have a look at the public previews of pipeline caching and pipeline artifacts. The new additions are meant to “accelerate the transfer of artifacts between jobs and stages, and by caching the results of common operations”. While the speedup with caching is pretty self-explanatory, pipeline artifacts help by utilising a deduplication strategy which leads to only uploading “net-new content” to the server.

New GitLab bugfix release available

After some users of self-managed instances reported receiving invalid CI quota violation notifications when upgrading to 12.1, GitLab has released version 12.1.1 to fix the issue. Upgrading should be straight-forward and not require any downtime.

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