I love hiking mountains; I always did since I was a child. There is a mix of challenges, enthusiasm, and learnings in walking for long hours through little and tortuous steep trails: it challenges your mind and body and makes you stronger.
One thing that always fascinated me is how the shape of peaks and valleys changes as you go higher and raise your perspective. When finally, exhausted, you reach the mountain peak you have a mix of pleasure and relief. You have achieved your goal, and you can, at last, have the full view on the horizon, understand how mountain chains are linked together, where rivers start and end up in lakes, and you can see far away as never before.
Continuous Delivery is a landscape of rivers, lakes, and mountains
I believe today’s landscape of Software Engineering is very diverse: there are so many powerful tools that generate streams of data continuously, and we need to get on top of them every day to be successful in an ever-evolving market space.
Continuous Delivery is the key methodology that nowadays allows the entire “software production chain” working smoothly. However, it poses challenges which are not always technical but often related to the flow of information across the systems and people.
See the big picture
To succeed, we need to raise our point of view to see the “big picture” and understand how things are connected and where are the improvement points, considering all the data we have about:
collect software and system metrics, logs, test results, build trends
repositories, commits, branches, pull requests, patch sets
- People and Teams
active and passive collaborators, contributors, reviewers, comments and replies
Collecting data is not enough, we need to raise our point of view and hike the Continuous Delivery mountain of problems and reach a point where all those elements make sense because they are:
- all visible from a single perspective
Yet another BigData problem
The problem is too many data sources to manage.
The typical solution to the problem is taking all logs from everywhere and publishing them to a single repository using an ELK (ElasticSearch + Logstash + Kibana) stack and building fancy dashboards. I have used this approach for small-scale projects, and it works quite well, but … when I tried to scale that to a much bigger Continuous Delivery pipeline the complexity, diversity, and granularity of data just killed my ability to see the “bigger picture” and I felt almost helpless in front of my Kibana dashboards.
Back to the source of data
Trying to understand what was missing, I ended up realizing that some of the dimensions were not taken into account and correlated: Code Reviews.
All the tooling were about test results, build, system and application logs but none of them has taken the code into account, which is the source of all the pipeline. You can understand where to go if you realize where you are coming from: the code is the source of all build chains.
When I started collecting data from the code repository and reviews, all made sense again, and I felt the I have reached the peak of my Continuous Delivery hiking effort: all made sense again and I could see the overall perspective.
Continuous Delivery Analytics
Exactly in the same way we Application Analytics are used to collecting data about our production system, split into dimensions and analyzed, we need then to start doing the same with our Continuous Delivery pipeline.
There are already some of the tools out there in the market which integrates some parts of it, but I haven’t seen a single one who can give you the bird’s eye perspective you need to understand the big picture.
That’s why I started writing one, using the only way make sense for me: writing in the open and with the help and cooperation of the OpenSource community of people and companies who share the same problem and have the same perspective.
Gerrit Analytics coming at the User Summit 2016
I presented my ideas at a couple of conferences (Devoxx, JenkinsWorld) and I received a lot of appreciation and feedback: the next one is the Gerrit User Summit in Mountain View – CA.
Large companies like SAP, Qualcomm, Ericsson, Google and Intel are exchanging every year their problems and ideas on how to make their Continuous Delivery Pipelines smoother, better and faster.
The perspective will be, of course, more Gerrit Code Review centric with more data and views that make sense from a review perspective.
Call to action
Come to the Gerrit User Summit 2016 in Mountain View – Google HQ on the 12th and 13th of November, and see the Gerrit and Continuous Delivery Pipeline in Action.
The event is FREE, register now at https://goo.gl/forms/oeEnQweHl2noNSnn1