Introducing Open DevOps Automation
You’ll receive a hundred different responses if you ask 100 development teams what tools they use to release software of DevOps automation since each team is different, each project is different, and tools change rapidly.

However, the desire to employ the best tool available—which is typically a competitive advantage—can result in an ever-expanding tool stack that is fragmented, challenging to set up and administer, and creates information silos. Companies have tried to consolidate all of their tools under one vendor or accepted an uncoordinated best-of-breed toolchain as a solution to these problems. As a result, teams end up settling on “good enough” tooling rather than innovative methods of operation as a result.
We think that each software team should select the best resources available without compromising the capacity to work together throughout the organization. Our strategy is open and integrated to allow teams to utilize the tools of their choice while ensuring that cooperation doesn’t slow down development.
Today, we’re introducing Open DevOps Automation, a Jira-based development experience that unites a varied toolchain into one seamless experience. Continue reading to find out how we’re giving software teams the freedom to choose the tools they want and work however they like while maintaining coordination.
A “You Build it, You Operate it” Team-Specific Toolchain – DevOps Automation
We’ve prepared the framework for teams creating and running their own services by combining Atlassian products and partner offers into a pre-configured Jira project dubbed “Open DevOps Automation,” which will help them begin shipping and operating software.
Jira Software, Confluence, Bitbucket, and Opsgenie are the foundational components of the standard DevOps project. Teams can quickly switch to the tools they desire, such as GitLab or GitHub, with just one click.
“GitLab and Atlassian have a strong commitment to serving our users’ requirements. We’re pleased with the work we did to integrate GitLab with Jira. Without compromising visibility or the capacity for collaboration, our joint customers get the freedom to stay in the context and with the tool of their choice.
Open DevOps Automation’ Default Features.
Jira will serve as the foundation for all of our DevOps Automation solutions. Your developers enjoy writing code, but since the company must be involved in the development process, everyone is usually forced to use Jira by default.
That’s not the situation anymore. Developers and the company may concentrate on their work rather than manually updating Jira or frequently changing contexts.
Code in Jira: Bitbucket, GitLab, and GitHub Git repositories have been natively linked into Jira Software. When you submit a modification or merge a branch, just remember to include the Jira issue keys, and Jira will automatically update. To help all your stakeholders understand what your team is presently working on, Jira will automatically display repos on the Code page in order of the most recent change. When you incorporate the Jira issue key into your development activity, the Deployments tab will automatically fill with your deployments, making it apparent when and what value was delivered to consumers. This is compatible with all major CI/CD providers, including Bitbucket Pipelines, GitLab, Jenkins, Azure DevOps, Circle CI, and J Frog.
Jira’s on-call: schedule makes it simple to page the appropriate person via Opsgenie in case something goes wrong and someone has to be notified. This eliminates the need to find out who is on call.
Jira pages In DevOps, culture is equally as important as tools. Teams have access to tried-and-true templates for best practices like change management, runbooks, and post-incident reviews thanks to Confluence’s integration with Open DevOps Automation
Cycle time trends: Since each task in Open DevOps is associated with a Jira issue, Jira can offer information on bottlenecks that enhance team productivity. Jira Service Management and Open DevOps can be combined with ease by teams who require more comprehensive service operations and support capabilities.
Develop and Adapt Open DevOps with our collaborators
There is no one DevOps toolchain that works for all teams since there is no one way to perform DevOps Automation. Our 2020 DevOps Automation Trends Survey revealed that respondents utilized an average of 10 tools to transfer an idea from development to production. We at Atlassian can vouch for this because we use a ton of products ourselves!
In Jira for Open DevOps, we already have connectors with top testing, security, feature flagging, and observability suppliers. Future milestones will include one-click connections to third-party applications, further simplifying the process of getting started with them.
Now that Atlassian Open DevOps has been released, it is not a compromise. While we take care of the complexities of integrating the tools teams want and making sure that workflows are optimized, teams can concentrate on providing value to their customers.
We’re interested in seeing how Open DevOps will be used, customized, and expanded by our clients. However, what excites us the most is what our customers will create using it.
About Enteros
Enteros offers a patented database performance management SaaS platform. It proactively identifies root causes of complex business-impacting database scalability and performance issues across a growing number of RDBMS, NoSQL, and machine learning database platforms.
The views expressed on this blog are those of the author and do not necessarily reflect the opinions of Enteros Inc. This blog may contain links to the content of third-party sites. By providing such links, Enteros Inc. does not adopt, guarantee, approve, or endorse the information, views, or products available on such sites.
Are you interested in writing for Enteros’ Blog? Please send us a pitch!
RELATED POSTS
How to Improve Retail Profitability with Enteros Cost Attribution, Database Analytics, and Software Management
- 21 June 2026
- Software Engineering
Introduction The retail industry is evolving at an unprecedented pace. Driven by ecommerce growth, omnichannel experiences, customer personalization, and digital transformation initiatives, retailers are investing heavily in technology to remain competitive. Modern retail organizations rely on: Ecommerce platforms Point-of-sale (POS) systems Inventory management applications Customer engagement platforms Supply chain systems Retail analytics environments AI-powered recommendation … Continue reading “How to Improve Retail Profitability with Enteros Cost Attribution, Database Analytics, and Software Management”
How to Drive Education Platform Growth with Enteros Database Performance Analytics and RevOps Efficiency
Introduction The education sector is experiencing a profound digital transformation. Universities, colleges, online learning providers, K-12 institutions, and corporate learning platforms are increasingly relying on technology to deliver engaging learning experiences, manage academic operations, and support student success. Modern education ecosystems now support: Learning Management Systems (LMS) Student Information Systems (SIS) Online learning platforms Virtual … Continue reading “How to Drive Education Platform Growth with Enteros Database Performance Analytics and RevOps Efficiency”
Why Intelligent Database Workload Management Is Essential for High-Growth SaaS Platforms
- 19 June 2026
- Database Performance Management
Introduction Telecommunications providers are operating in one of the most competitive and technology-intensive industries in the world. While demand for connectivity, mobile services, broadband access, and digital experiences continues to grow, profit margins are increasingly challenged by rising infrastructure costs, complex network operations, and expanding customer expectations. Modern telecom organizations must support: 5G networks Cloud-native … Continue reading “Why Intelligent Database Workload Management Is Essential for High-Growth SaaS Platforms”
Reducing Operational Complexity with AI-Driven Database Observability and AIOps
Modern enterprises operate in increasingly complex digital environments. Applications now span hybrid cloud infrastructures, multi-cloud deployments, containerized platforms, microservices architectures, and globally distributed data systems. While this transformation enables greater scalability, agility, and innovation, it also creates significant operational challenges for IT and engineering teams. At the heart of these complex environments lies the database … Continue reading “Reducing Operational Complexity with AI-Driven Database Observability and AIOps”