This page introduces the GitLab product vision, where we're headed over the next few years, and our plan to deliver over the next year.
Our vision is to replace disparate DevOps toolchains with a single application that is pre-configured to work by default across the entire DevOps lifecycle.
We aim to make it faster and easier for groups of contributors to deliver value to their users, and we achieve this by enabling:
You can read more about the principles that guide our prioritization process in our product handbook. You can also read our GitLab as a Product section which describes the principles that are used to guide GitLab itself forward.
We are investing in the following manner across each stage:
Possible future stages that are being considered can be found on our Product stages, groups, and categories page
Product uses a few key concepts to talk about how we work:
We aim for product leadership in almost every area we compete in. We're already there with:
The next three we'll build up to best-in-class, lovable features are:
Depth is about taking everything that's already
viable and getting it through to
complete, and eventualy to
We wouldn't be true to our ambition if we stopped with our current product
categories. For breadth, we’re taking all the brand new,
planned categories, as well as the existing, but
minimal categories, and making them all
Personas are the people we design for. We’ve started down the path of having developers, security professionals, and operations professionals as first-class citizens; letting each person have a unique experience tailored to their needs. We want GitLab to be the main interface for all of these people. Show up at work, start your day, and load up GitLab. And that’s already happening.
But there are a ton of people involved with the development and delivery of software. That is the ultimate GitLab goal - where everyone involved with software development and delivery uses a single application so they are on the same page with the rest of their team. We’ve recently launched the first features for Designers and soon we’ll have more for Product Managers. We’ll be expanding to the business side, with Executives visibility and reporting. Maybe even Legal gets involved in license review. While we’re still calling it DevOps, we’re really expanding the definition of DevOps, and delivering it all as a single application.
The last prong is application types. There’s a bunch of things we’re great for, like cloud native web apps. And our customers have projects today that we could support better, like mobile apps. And then there’s a ton of stuff in the future to consider, like data science and ML.
Application types represent both different application types (web applications, mobile apps) and architectures (monorepos, microservices). Gitlab continues to deliver and replace the disparate DevOps toolchain for both static sites and traditional web applications. These are two examples of application types. We're actively investing in more robust support for new application types such as cloud native and mobile apps, but we aren't done there. GitLab will expand to enable collaboration on new application types. See the handbook for more details or the current maturity levels.
Current Application Types:
Future application types:
Continuing apace in 2019 after Microsoft's 2018 acquisition of GitHub, the trend to consolidate DevOps companies seems here to stay. In January 2019, Travis CI was acquired by Idera, and in February 2019 we saw Shippable acquired by JFrog. Atlassian and GitHub now both bundle CI/CD with SCM, alongside their ever-growing related suite of products. In January 2020, CollabNet acquired XebiaLabs to build out their version of a comprehensive DevOps solution.
It's natural for technology markets go through stages as they mature: when a young technology is first becoming popular, there is an explosion of tools to support it. New technologies have rough edges that make them difficult to use, and early tools tend to center around adoption of the new paradigm. Once the technology matures, consolidation is a natural part of the life cycle. GitLab is in a fantastic position to be ahead of the curve on consolidation, but it's a position we need to actively defend as competitors start to bring more legitimately integrated products to market.
For 2020, we have 5 key product themes we are focused on:
As we add new categories and stages to GitLab, some areas of the product will be deeper and more mature than others. We publish a list of the categories, what we think their maturity levels are, and our plans to improve on our maturity page.
We try to prevent maintaining functionality that is language or platform specific because they slow down our ability to get results. Examples of how we handle it instead are:
Outside our scope are Kubernetes and everything it depends on:
During a presentation of Kubernetes Brendan Burns talks about the 4 Ops layers at the 2:00 mark:
GitLab helps you mainly with application ops. And where needed we also allow you to monitor clusters and link them to application environments. But we intend to use vanilla Kubernetes instead of something specific to GitLab.
Also outside our scope are products that are not specific to developing, securing, or operating applications and digital products.
In scope are things that are not mainly for SaaS applications:
To make sure our goals are clearly defined and aligned throughout the organization, we make use of OKR's (Objectives and Key Results). Our quarterly Objectives and Key Results are publicly viewable.
GitLab's direction is determined by GitLab the company, and the code that is sent by our contributors. We continually merge code to be released in the next version. Contributing is the best way to get a feature you want included.
On our issue tracker for CE and EE, many requests are made for features and changes to GitLab. Issues with the Accepting Merge Requests label are pre-approved as something we're willing to add to GitLab. Of course, before any code is merged it still has to meet our contribution acceptance criteria.
At GitLab, we strive to be ambitious, maintain a strong sense of urgency, and set aspirational targets with every release. The direction items we highlight in our kickoff are a reflection of this ambitious planning. When it comes to execution we aim for velocity over predictability. This way we optimize our planning time to focus on the top of the queue and deliver things fast. We schedule 100% of what we can accomplish based on past throughput and availability factors (vacation, contribute, etc.).
On our releases page you can find an overview of the most important features of recent releases and links to the blog posts for each release.
Note that we often move things around, do things that are not listed, and cancel things that are listed.
Deployments should never be fire and forget. GitLab will give you immediate feedback on every deployment on any scale. This means that GitLab can tell you whether performance has improved on the application level, but also whether business metrics have changed.
Concretely, we can split up monitoring and feedback efforts within GitLab in three distinct areas: execution (cycle analytics), business and system feedback.
With the power of monitoring and an integrated approach, we have the ability to do amazing things within GitLab. GitLab will be able to automatically test commits and versions through feature flags and A/B testing.
Business feedback exists on different levels:
Long term: how do larger efforts relate to changes in conversations, engagement, revenue
Your application should perform well after changes are made. GitLab will be able to see whether a change is causing errors or performance issues on application level. Think about:
We can now go beyond CI and CD. GitLab will able to tell you whether a change improved performance or stability. Because it will have access to both historical data on performance and code, it can show you the impact of any particular change at any time.
System feedback happens over different time windows:
Medium-Long term: did a particular effort influence system status
GitLab is able to speed up cycle time for any project. To provide feedback on cycle time GitLab will continue to expand cycle analytics so that it not only shows you what is slow, it’ll help you speed up with concrete, clickable suggestions.
Machine learning (ML) through neural networks is a really great tool to solve hard to define, dynamic problems. Right now, GitLab doesn't use any machine learning technologies, but we expect to use them in the near future for several types of problems.
Signal detection is very hard in a noisy environment. GitLab intends to use ML to warn users of any signals that stand out against the background noise in several features:
Automatically categorizing and labelling is risky. Modern models tend to overfit, e.g. resulting in issues with too many labels. However, similar models can be used very well in combination with human interaction in the form of recommendation engines.
Because of their great ability to recognize patterns, neural networks are an excellent tool to help with scaling, and anticipating needs. In GitLab, we can imagine:
Similar to DeepScan.
Similar to Sourcegraph.
Identifying anomalous activity within audit events systems can be both challenging and valuable. This identification is difficult because audit events are raw, objective data points and must be interpreted against an organization's company policies. Knowing about anomalous behavior is valuable because it can allow GitLab administrators and group owners to proactively manage undesireable events.
This a difficult problem to solve, but can help to drastically reduce the overhead of managing risk within a GitLab environment.