We are all used to open source projects. Concepts such as community, code review process, continuous integration, geographically distributed contributions, community managers, and a whole myriad of terms and collaborative way of working are usual for all of us. And enterprises are learning from this open process. Those are changing the direction of their development models to a more open one within the organization. Initiatives such as the Inner Source Commons where companies such as PayPal or Bloomberg are publicly exposing their case, help others to deal with the usual problems they face.
“The idea is beginning to take root in even the most secretive corporate cultures… Its power lies in the inherent social nature of the creative process. When developers are able to access, use and build upon what their colleagues are creating, innovation can really take hold.”
Phil Granof in Wired
As we detailed in the previous post, adopting Inner Source practices creates great benefits for companies such as saving cost, faster time to market and enabling innovation.
There’s no doubt that Inner source needs a different approach to project management but “hands on!” What’s the best project to start Inner Sourcing?
Software is becoming the core of most business, even the traditional ones. However it doesn’t mean that companies should build all the software they need, most of it can be easily bought or outsourced with low cost, in order to focus their efforts on their core business. Thus, Inner Source should help to add value to organizations running away from commodity.
This was the case for Philips Healthcare. Klaas-Jan Stol and Brian Fitzgerald in their article Inner Source—Adopting Open Source Development Practices in Organizations recommended to start with a seed project. That means, not starting from scratch but choosing an existing initial implementation of a software product or component.
Frank Van Der Linden, CTO at Phillips was responsible for and pioneered the setting up Inner Source within the company. He decided to start with a component suite of DICOM (Digital Imaging and Communication in Medicine) standard, used in many medical imaging tools such as x-ray and MRI (Magnetic Resonance Imaging) scanners. Philips Healthcare has a product line for diagnostic techniques in Hospitals, so they chose a core business software product for Inner Sourcing.
Van Der Linden reports enormous business benefits using Inner Sourcing as a process for developing:
- Three times more product groups served.
- Substantially improved product quality (Improved feedback from product groups)
- Product groups find defects earlier.
- Significant time to market gains.
- Growing an active Inner Source community – Over 60% of the PH software community involved.
Philips and other companies running Inner Sourcing learned from Open Source projects, they understood how to align and coordinate efforts. In the next post, we will talk about essential tools to enable Inner Sourcing.
One of the first tasks done by a developer during the day is to choose where to go and what to fix. Backlogs are quite useful for this purpose, either using Kanban and directly having a look at the open issues waiting lists project by project as in the case of GitHub, or using any other manual or automated method.
For this engineering focus we have started to produce some panels whose main purpose is to help developers to make decisions. As this is still in its first stages there is room for improvement, but this hopefully shows how powerful this could be. The displayed panel is part of the open analytics panel produced for the CoreOS community.
This panel aims at providing information at three main levels:
The EclipseCon starts today in France. And for this special occasion we are landing a new version of the open analytics platform for Eclipse today. This is intended to be used for community purposes, but also for engineering teams and for those curious about how this community performs over time and nowadays. Luis Cañas will talk about this during the Conference, do not miss his talk!
The entry point for the dashboard is the Overview page. There a summary of each of the available data sources is displayed together with some filters that help to understand the evolution and current state of the activity and the community of Eclipse.
Public quarterly reports are used for understanding the performance of companies. And so, quarterly reports done by Bitergia fill the gap of understanding the performance of open source communities. This type of analysis focuses on those that are still interested in metrics, but do not have the time to play with the dashboards. This indeed provides a full overview of the current quarter, but adds a comparison with the previous quarters. This allows to have some extra context about where the community is heading.
In Bitergia we have a list of happy customers using the Metrics Grimoire toolset (fork them at GitHub!) to produce metrics about their communities. Tracking tech communities is not that simple and this needs of some infrastructure. And one of the main issues usually consists of aggregating all of the information.
- How to have aggregated information for a given project from several data sources?
- How to aggregate information from a specific developer from several data sources?
- How to aggregate information for a given company from several data sources?
- How to manage the several identities (IRC nickname, Jira user name, …) across data sources of a developer?
- And what about managing the several affiliations of a developer?
And even more, is there a place where I can easily have a glimpse and check how my community is going?
The following is an example of the OPNFV community where the Git repositories, Gerrit projects, tickets from Jira, mailing lists, IRC channels and the Askbot instance is summarized in the entry page of the OPNFV dashboard.
The Bitergia toolset covers all of these issues with the retrieval of raw information, cleaning and massaging of the data and visualization. Indeed any of these steps are fully independent, what helps you to add any of your favourite tools in any of the several steps.
Let’s imagine that you’re interested in using your favourite visualization tool to play with the data. You can have direct access to the databases or to the post-processed data. It’s your data and Bitergia worries about providing a trustable service where all of the tools and data are open source.
[This post is based on the executive summary of the 2015-Q5 OpenStack Community Activity Report, sponsored by the OpenStack Foundation]
The October-Devember 2015 penStack Community Activity Report shows a stable growth of the OpenStack Community. As new repositories and teams keep being added, the number of projects keeps growing. On the other hand it is worth mentioning the decrease in activity during the latest quarters in project teams such as Nova, or stabilization of some others, such as Horizon or Cinder. This is a clear signal of the maturity reached by the some of the project teams in the OpenStack Foundation.
Active Core Reviewers reach a new peak
Although Git activity (changesets merged in the code base) does not show a large increase of activity, if compared to Gerrit, the development effort in the project keeps increasing. This last quarter of 2015 the number of Active Core Reviewers reached a new record of 449 different developers.
Time to merge keeps decreasing
During the third quarter of 2015, a small increase in time to merge seemed to signal a change in trend. However, this last quarter of 2015 keeps the previous decreasing trend. During this period the median time to merge a changeset into master decreased from 2.91 days down to 2.38 days.
Efficiency closing tickets decreases
It is noticeable the decrease of the relative number of tickets closed in OpenStack projects (also known as the efficiency of the ticket closing process). Previous quarters topped at about 60% of closed tickets (with respect to tickets opened during the same period), while this quarter shows a much lower 44%. This could be seen as a poor performance indicator of the project teams.
However, the efficiency closing changesets in the review system (number of changesets merged or abandoned with respect to number of new changesets being proposed for review) remains stable at around 80%.