We have some exciting news! The Analytics Dashboards are being upgraded to our latest Kibiter release based on Kibana 6.1.0. This new version will allow our customers to enjoy new visualizations, new metrics and a new security layer. Everything 100% open source software.
Nowadays, more and more companies such as PayPal, Bosch or Autodesk are internally implementing inner source programs. Inner source differs from classic open source development process by remaining within the view and control of a single organization and offers many advantages in terms of efficiency and effectiveness.
In previous posts, we talked about Inner source characteristics and advantages such as InnerSourcing: the development model of the future.
Once again, Bitergia will be at OSCON, held this time in Portland, at Oregon convention center. OSCON, one of the biggest open source conventions in USA, has been ground zero of the open source movement and nowadays continues to be the catalyst for innovation among companies.
Open source projects issues deal with community health and activity: how to get people to contribute or how to keep people engaged are common activities for community managers. Thus, key Performance Indicators (KPIs) should be set for each community based on those goals.
Nowadays, is a matter of fact that software development is eating up the labor market. Netflix is not a film company, Amazon is not an online ebook company, Spotify is not a music company, Pixar is far from being an animation studio, and Groupon is not just a marketplace. We are living in the digital transformation. To attract and to retain the best development talent is becoming more and more important for any company.
Mentoring is one of those activities key in any open source communities as well as in any other environment such as internally at companies. The new edition of the OpenStack gender report [to be published], produced by Intel and Bitergia, has focused specifically on those programs that help newcomers and filling the existing knowledge gap.
How have we ended with more than 30 different data sources supported in our Bitergia Analytics product? During the last couple of years I’ve been so focused on improving the support and operating areas here in Bitergia that I forgot to stop and look back to see how far we have “walked” in terms of development.
Last week I was invited to participate in the Open Source Weekends meetup, so I set up a quick GrimoireLab demo for them. It was a surprise, part of my talk about the history of Bitergia. You can see the slides online:
The adoption of Python notebooks to perform data analysis has considerably increased, becoming a de-facto standard within data scientists communities. But, which Python libraries are used on them?