The Ops Section comprises the Verify, Package, Release, Configure and Monitor stages of the DevOps lifecycle. Market analysts (internal - i) often describe these stages as automated software quality (ASQ, partially analogous to Verify, Package and Release) IT automation and configuration management (ITACM, analogous to Configure) and IT operations management (ITOM, partially analogous to Monitor).
In some contexts, "ops" refers to operators. Operators were the counterparts to Developers represented in the original coining of the term DevOps. That definition highlighted the rift between the two groups and a need for collaboration. At GitLab, we use "ops" to mean operations - any component of the software delivery value stream after a developer commits code. Our developer first perspective means our use of the word ops is focused on enabling developers to configure tools and perform operations tasks first. We have ambitious plans to support operators in the future.
The total addressable market (TAM) for DevOps tools targeting these stages was $3.2B in 2018 and is expected to grow to $7.6B by 2022 (18.8% CAGR) (i). This is a deep value pool and represents a significant portion of GitLab's expanding addressable market as organizations further adopt DevOps and developer focused ops tools account for a larger share of a market which traditionally targets Architects, System Admin and Operator personas.
The market is well established (i) but the participants are evolving rapidly. Existing leaders in single stages of the DevOps lifecycle are expanding towards a complete DevOps delivery platform via acquisition and product development. These existing leaders run the gamut from GitHub with their strong position in the Create stage, to Splunk with their strong position in Monitor. All are pivoting to pursue a single DevOps platform strategy.
Expanded market players such as GitHub are taking market share from traditional participants like CloudBees in the Verify stage. In the Package stage, JFrog is expanding their leadership position in artifact repositories into other stages of the DevOps lifecycle. In the Release stage Spinnaker is a new open-source, fast growing entrant enabling collaborative CI/CD workflows and taking market share from traditional Application Release Orchestration vendors. Splunk, New Relic and Datadog are dominating market share in the Monitor stage and fiercely competing to be a central monitoring platform. IBM (+RedHat), Hashicorp, Puppet and Chef split a large chunk of the fragmented market in the Configure stage.
Despite many strong players, GitLab's market share in the Ops section is growing, especially in the Verify and Release stages. For the Configure, Package, and Monitor stages, our unique perspective as a single and complete DevOps application positions us for growth. Our customers utilize many Ops Section stages today. Primarily they:
Our current R&D investment in Ops Section stages is large. The maturity of each stage and category can be found in our maturity page. Our investment in the Ops section is critical to both enabling enterprise users to continue on their DevOps maturity journey. Driving adoption across multiple Ops stages enables early adopters to recognize the benefit of a single application.
GitLab is competing in a new market of value stream delivery platforms (i - Gartner). We were an early entrant in this market before it was defined but there are many, and will be more, fast followers. Key players include large established tech firms (Microsoft) as well as newly consolidated platforms from aquisition (JFrog, CollabNet/VersionOne/XebiaLabs).
Beyond the key players, there is also rapid innovation in new technologies making for a market where there is both proliferation of new technology, and consolidation of the winning technologies into comprehensive platform players. Ease of deployment for CI/CD and operational tools has aided this expansion. Developers and operations teams can easily instrument and utilize new technologies alongside their existing software development pipelines with less risk, and in quicker time frames than under previous models where it required diligent planning and months of installation and configuration.
Competing tools are marketed as stand-alone point solutions while GitLab's capabilities will shine when customers use other stages of GitLab. This can create a narrow funnel for adoption with potential users coming only from the segment of the market already using, or willing to use, other stages of GitLab rather than broad-based market fit. Without developing more landing spots for new users of GitLab, this smaller adoption funnel will affect our rate of learning.
Few companies have been able to successfully bridge between Developer and Operator personas. Building tools that satisfy both sets of jobs-to-be-done is difficult. Without deeply understanding new personas and tasks, market entrants end up with a checklist of modules that don't represent a cohesive and improved experience for users.
In recent years we've seen the emergence of large public cloud infrastructure providers moving from a focus on infrastructure services for operators towards developer tools. These providers could challenge current notions of multi-cloud by creating great, integrated experiences in their tools for developers to create, verify, and deploy applications to the providers' infrastructure. There is a possibility that these provider-centric ecosystems present organizations with a choice of investing in a best-of-breed platform with a small subset of projects or a just sufficient enough platform used by all.
Outside of market challenges we have some internal ones as well. In general, we are not dogfooding the Release, Monitor and Configure stage features sufficiently. This has the effect of slowing our rate of learning, and putting us in the position of not having immediate real-world validation of our product initiatives.
Given these challenges, here are some key opportunities we must take advantage of:
GitLab's Ops strategy follows that of GitLab's company strategy. Just like our company mission, we will enable everyone to contribute not just via application code, but via other digital artifacts that increasingly define the performance, reliability, and resilience of the world's software. We will pursue that mission and capitalize on the opportunities (developer buyer power, IT skills gaps, a move towards Kubernetes, and our roots in source-control and CI) listed above by utilizing a dual-flywheel approach. This approach starts with attracting developers performing DevOps tooling and operations tasks to our Core (FOSS). As we build best of breed tools for them we will utilize their feedback to drive community and product improvements. This will in turn generate revenue for higher product tiers and additional investment for supporting the platform and ops teams which support modern development teams.
We'll do this by enabling easy-to-discover workflows that support doing powerful, complex actions with a minimum of manual configuration. We want to take advantage of our single application so that, while each team may have their own views or dashboards in the product that support their day to day, the information about what is deployed where is available everywhere and to everyone, embedded naturally into the product where it's relevant. For example, a person thinking about upcoming releases may interact mostly with an environment-based overview that helps them see upcoming changes and alerts as they flow through environments, but that same information exists everywhere it is relevant:
The end result is that even complex delivery flows become part of everyone's primary way of working. There isn't a context shift (or even worse, a switch into a different tool) needed to start thinking about delivery or operations - that information is there, in context, from your first commit. The centerpiece of this strategy is our Get Things Done Easily theme.
In three years the Ops market will:
As a result, in three years, the Ops stages in GitLab will:
Our direction for Ops is to enable today's modern best practices in operations without the burden of specialized teams, multiple tools, and heavy workflows that are the largest barriers to adoption in these stages of the DevOps lifecycle.
Our goal is to empower DevOps teams to own their code's path to production as well as the performance of their production application itself. We also want to ensure they have the tools to contribute to feature development and the complete end-user experience of their application.
Our themes are directly aligned to our overall Product Principles especially:
In addition to our broad product themes there are some specific call-outs relevant for the Ops Section stages.
GitLab CI/CD was built from the ground up with speed and scalability in mind. This is reflected both in the product design as well as product vision (automated testing, testing all the things). To enable our users to go from monthly shipping releases to truly enabling continuous delivery, everything that we do must be concerned with the scalability and speed of continuous integration and testing. Not that sword fighting on office chairs isn't fun, but we do want people to be able to contribute at the speed of development. We will achieve this through automated tuning where possible, and faster feedback on potential issues where not.
Wall clock time for a pipeline is an important measure here. You feel this many times every day - when you make a commit and a pipeline starts, but you need to go have lunch before you see the result, that's not fun for anyone. Issues like our auto-determining the test parallelization factor and running tests likely to fail first represent how we want GitLab CI/CD to automatically find and solve these problems for you. We are building more speed into the workflow itself with features like the dependency proxy to help speed up the tax you pay on every job invocation setting up the environment, fetching dependencies, and so on.
There have been three major trends impacting operations; they are all three essential to enabling Developer style workflows for operational tasks by defining those activities as code (or data). They are Compliance as Code, Infrastructure as Code (IAC) and Observability as Code (OAC). At GitLab, our roots in SCM make us especially well suited for supporting these trends.
Compliance as Code is the idea that requirements for auditing and compliance teams can be collected with zero additional cognitive load from developers and other team members participating in software delivery. Because GitLab has an end-to-end view of the artifacts that are associated with releases (issues, merge requests, feature flags, and so on) we are uniquely positioned to provide a comprehensive view of compliance-related activity, collected on an ongoing basis throughout the build, test, and release process. Our vision here can be found in our strategy page for Release Evidence.
IAC provides DevOps teams with a method to maintain consistency with the infrastructure their applications run on. The best practices defined in IAC prevent configuration drift, and allow teams to maintain consistent performance and security characteristics without the need for ongoing manual intervention.
IAC was made possible by the availability of rapidly deployed cloud infrastructure (IaaS platforms), and the corresponding buildup of tools to enable generic usage and consistent deployment to that infrastructure (Container Management Platforms).
With our roots as a source code management system, we will build on our existing workflows for code management, and extend our ability to define and manage infrastructure configuration in your project repositories so you can achieve reliability and consistency in your application.
Observability is a measure of your application which defines how well you can understand the state of your production system from its external outputs. The more observable your application is, the more reliably you can operate it, both manually and through automation. Our vision is to allow you to define your observability and operational automation in code, alongside your application code. Whether that is the configuration of dashboards, metrics, alerts, runbooks, automation scripts or incident issues - GitLab will source-control those configurations and ensure they are reliably deployed to your production systems.
Progressive Delivery is a set of emerging CD best practices, oriented around being able to control and monitor deployments incrementally over time, and in an automated and safe way. It takes Continuous Delivery to the next level by providing more options around how and when different users get access to your new features, making software delivery a continuous activity, rather than frequent but punctuated moments in time.
Defining your infrastructure, observability, and operations as code is just the first step. The real magic happens when you rapidly iterate on those definitions. As a single-application for the entire DevOps lifecycle GitLab completes what is commonly a major gap in the DevOps loop - the feedback from ops back into planning.
Our vision is to provide not just an easy ability to identify, suggest, complete, and deploy changes to your production system, but also enable new insights that other tools can't. During incident response, GitLab can quickly identify the last deployed commit, lines of code changed, and author to guide the response to the right place. During deployment, GitLab can quickly tell you if your production system is already out-of-bounds from defined service-level indicator (SLI) metrics and roll back. During post-mortems, GitLab can suggest runbook or alert changes. We are very excited about enabling DevSecOps teams with these smart additions.
Truly integrated DevOps teams are difficult to create. While large organizations have the budget to staff dedicated teams with roles like "Cost Optimization Engineer" and "Site Reliability Engineer" smaller teams require "Jack of All Trades" engineers.
Our vision at GitLab is that everyone can contribute, and that small teams, without specialization, can leverage and adopt the same tools as those in larger organizations. By building on our preference for convention over configuration, we can take the guess work out of operations. We will enable you and your team to quickly build a production application and iterate on it. We'll make it easy for teams to start from modern operations practices where you avoid alert fatigue by detecting real user events and are able to resolve like a pro. Not just on its features, but on the overall experience delivered to your users. Rapidly.
Like our product-wide adoption journey, we've also defined a user adoption journey between the Ops section stages.
The Ops Section North Star Metric is our Total Section Stages Monthly Active Users (Total Section SMAU). Just like our broad-based product metric of SMAU, total Total Section SMAU measures user-based adoption of the various stages at GitLab.
Given that, we are heavily focused on enabling CI usage from existing SCM customers and CD usage from existing CI customers - thus activating users into our section SMAU and enabling them to continue on our user adoption journey to other Ops Section stages.
The majority of our Ops Section product groups are focused on driving adoption first, and then monetization within their category scope. Some groups are well placed to focus on adding tier value for buyer-based personas on top of existing stages which already have heavy usage. Those groups will adopt Stage Monthly Active Paid Users (SMAPU) as their North Star Metric. In the Ops section those groups are:
GitLab will focus on the jobs to be done (JTBD) found in the workflows identified across all of our stages. Today we've identified those critical JTBD in the Package, Release Management, Configure and Monitor stages.
The most critical are:
We identify the personas the Ops section features are built for. In order to be transparent about personas we support today and personas we aim to support in the future we use the following categorization of personas listed in priority order.
To capitalize on the opportunities listed above, the Ops section has features that make it useful to the following personas today.
As we execute our 3-year strategy, our medium term (1-2 year) goal is to provide a single application that enables collaboration between cloud native development and platform teams.
Our plan is quite simple. We see a common progression in all of our GitLab stages and categories. That progression is:
As a result we'll be focused on aquisition and tier value in our Verify stage, awareness in our Package and Release stages and dogfooding and soon awareness in our Configure and Monitor stages.
In doing so, over the next 12 months we will choose NOT to:
GitLab considers acquisitions as a key part of our investment in expanding the breadth of GitLab. The Monitor and Configure stages have a higher appetite for acquisition. Over the next year, GitLab is interested in acquisitions that fill gaps in our current set of new and minimal categories in the Configure and Monitor stages. There are also some other unnamed categories which fulfill our themes above that we would consider acquisitions in. Those include:
Below are some additional resources to learn more about Ops:
The Ops section is composed of five stages, each of which contains several categories. Each stage has an overall strategy statement below, aligned to the themes for Ops. Each category within each stage has a dedicated vision page plus optional documentation, marketing pages, and other materials linked below.
The details of how we'll achieve different elements of this can be found in the individual category pages below:
Gain the confidence to ship at blistering speed and immense scale with automated builds, testing, and out-of-the-box security to verify each commit moves you forward. This category is at the "lovable" level of maturity.
GitLab Runner is the execution agent that is used to run your CI jobs and send the results back to GitLab. This category is at the "lovable" level of maturity.
The Jenkins Importer helps unblock teams from migrating to GitLab CI. This category is at the "minimal" level of maturity.
Automatically analyze your source code to surface issues and see if quality is improving or getting worse with the latest commit. This category is at the "minimal" level of maturity.
Code testing and coverage ensure that individual components built within a pipeline perform as expected, and are an important part of a Continuous Integration framework. This category is at the "minimal" level of maturity.
Be confident in the performance of your changes by ensuring that they are validated against real world load scenarios. This category is planned, but not yet available.
Ensure performance of your software in-browser using automated web performance testing. This category is at the "minimal" level of maturity.
Testing to ensure usability flows work and are actually understandable and valuable to your users. This category is at the "minimal" level of maturity.
Beyond being a compliance requirement in many cases, accessibility testing is the right thing to do. This category is at the "viable" level of maturity.
Keeping master green and ensuring the stability of collaboration on branches is vitally important. GitLab has introduced Merge Trains as an important way to accomplish this. This category is at the "viable" level of maturity.
The details of how we'll achieve different elements of this can be found in the individual category pages below:
Every team needs a place to store their packages and dependencies. GitLab aims to provide a comprehensive solution, integrated into our single application, that supports package management for all commonly used languages and binary formats. This category is at the "viable" level of maturity.
A secure and private registry for Docker images built-in to GitLab. Creating, pushing, and retrieving images works out of the box with GitLab CI/CD. This category is at the "viable" level of maturity.
Kubernetes cluster integrations can take advantage of Helm charts to standardize their distribution and install processes. Supporting a built-in helm chart registry allows for better, self-managed container orchestration. This category is at the "minimal" level of maturity.
The GitLab Dependency Proxy can serve as an intermediary between your local developers and automation and the world of packages that need to be fetched from remote repositories. By adding a security and validation layer to a caching proxy, you can ensure reliability, accuracy, and auditability for the packages you depend on. This category is at the "viable" level of maturity.
GitLab ensures that the dependencies stored in your package registries conform to your corporate compliance guidelines. This means you can prevent your organization from using dependencies that are insecure or out of policy. This category is planned, but not yet available.
Jupyter Notebooks are a common type of code used for data-science use cases. With GitLab you can store and version control those notebooks in the same way you store packages and application code. This category is at the "minimal" level of maturity.
Git LFS (Large File Storage) is a Git extension, which reduces the impact of large files in your repository by downloading the relevant versions of them lazily. Specifically, large files are downloaded during the checkout process rather than during cloning or fetching. This category is at the "minimal" level of maturity.
The details of how we'll achieve different elements of this can be found in the individual category pages below:
Deliver your changes to production with zero-touch software delivery; focus on building great software and allow GitLab CD to bring your release through your path to production for you. This category is at the "complete" level of maturity.
Use any static site generator to create websites that are easily managed and deployed by GitLab. This category is at the "complete" level of maturity.
Get a full production like environment for every merge request that updates on each commit. See code running and enable user acceptance testing before you merge. This category is at the "complete" level of maturity.
Mitigate the risk of production deploys by deploying new production code to a small subset of your fleet and then incrementally adding more. This category is at the "viable" level of maturity.
Feature flags enable teams to achieve CD by letting them deploy dark features to production as smaller batches for controlled testing, separating feature delivery from customer launch, and removing risk from delivery. This category is at the "viable" level of maturity.
Management and orchestration of releases-as-code built on intelligent notifications, scheduling of delivery and shared resources, blackout periods, relationships, parallelization, and sequencing, as well as support for integrating manual processes and interventions. This category is at the "viable" level of maturity.
Release Evidence includes features such as deploy-time security controls to ensure only trusted container images are deployed on Kubernetes Engine, and more broadly includes all the assurances and evidence collection that are necessary for you to trust the changes you're delivering. This category is at the "minimal" level of maturity.
Use HashiCorp Vault and GitLab to manage your GitLab secrets. This category is at the "minimal" level of maturity.
While the market for the Configure stage has many strong incumbent players, it is splintered across many traditional IT management tools (Ansible, Chef, Puppet). There are emerging trends (i) showing a consolidation on containers (i) and specifically Kubernetes (i) for cloud-native application development. This will have the effect of stymying commercial players from locking in market share based on proprietary tools. So while there are strong players, the current market dynamics means there is upside for us.
The Configure stage is made up of several categories:
Commit your code and GitLab does the rest to build, test, deploy, and monitor automatically. Eliminate the complexities of getting going with automated software delivery by automatically setting up the pipeline and necessary integrations, freeing up your teams to focus on the culture part. This category is at the "viable" level of maturity.
Create and manage Kubernetes clusters with a few clicks. Install applications with a single click. This category is at the "viable" level of maturity.
Tight integrations with Slack and Mattermost make it easy to manage and automate software development and delivery right from your chat app. This category is at the "minimal" level of maturity.
Runbooks are a collection of documented procedures that explain how to carry out a particular process, be it starting, stopping, debugging, or troubleshooting a particular system. Executable runbooks allow operators to execute pre-written code blocks or database queries against a given environment. This category is at the "minimal" level of maturity.
Run cloud-agnostic serverless workloads on Kubernetes, deployed via GitLab CI/CD. This category is at the "minimal" level of maturity.
Manage your infrastructure effectively to create, configure, and manage a complete software development environment. This category is at the "viable" level of maturity.
This category is at the "minimal" level of maturity.
Priority: low • Direction
The market for the Monitor stage is aligned around key players New Relic, Splunk, ServiceNow and Datadog. Datadog, New Relic and Splunk are all headed towards integrated observability platforms based on collecting all available telemetry. ServiceNow (i) is considered a standard for help-desk and Incident Management workflows. Strong existing players with large sustained R&D investment will make it difficult for GitLab to compete head-to-head for Monitor stage market share, especially with traditional Operations and System Administration users.
The Monitor stage is made up of several categories:
GitLab collects and displays performance metrics for deployed apps, leveraging Prometheus. Developers can determine the impact of a merge and keep an eye on their production systems, without leaving GitLab. This category is at the "complete" level of maturity.
Consolidate all of your IT alerts in GitLab. Quickly triage and investigate problems by correlating alerts to relevant metrics, logs, traces, and errors. Elevate the critical ones to incidents for speedy resolution. This category is at the "minimal" level of maturity.
Track incidents within GitLab, providing a consolidated location to understand the who, what, when, and where of the incident. Define service level objectives and error budgets, to achieve the desired balance of velocity and stability. This category is at the "viable" level of maturity.
GitLab makes it easy to view the logs distributed across multiple pods and services using log aggregation with Elastic Stack. Once Elastic Stack is enabled, you can view your aggregated Kubernetes logs across multiple services and infrastructure, go back in time, conduct infinite scroll, and search through your application logs from within the GitLab UI itself. This category is at the "viable" level of maturity.
Tracing provides insight into the performance and health of a deployed application, tracking each function or microservice which handles a given request. This makes it easy to understand the end-to-end flow of a request, regardless of whether you are using a monolithic or distributed system. This category is at the "viable" level of maturity.
Self-managed GitLab instances come out of the box with great observability tools, reducing the time and effort required to maintain a GitLab instance.
Error tracking allows developers to easily discover and view the errors that their application may be generating. By surfacing error information where the code is being developed, efficiency and awareness can be increased. This category is at the "viable" level of maturity.
Digital experience management includes both real user monitoring (passive) and synthetics monitoring (active) to allow developers to detect problems in end-to-end workflows and understand real-world performance as experienced by users. This category is planned, but not yet available.
Priority: medium • Direction
This category is planned, but not yet available.
Priority: medium • Direction
It's important to call out that the below plan can change any moment and should not be taken as a hard commitment, though we do try to keep things generally stable. In general, we follow the same prioritization guidelines as the product team at large. Issues will tend to flow from having no milestone, to being added to the backlog, to being added to this page and/or a specific milestone for delivery.
after_scripteven when the job is cancelled for gracefully interruptible jobs
ci_release_generationfeature flag by default
secrets:in GitLab CI
environment:action:to annotate non-deployment jobs Premium
:releaseyaml as steps via API