The Future of DevOps is Here – Say Hello to Atlassian AI

The Future of DevOps is Here – Say Hello to Atlassian AI

Reading Time: 4 minutes
DevOps & Atlassian AI

Manual overload and the time spent uncovering insights from data scattered across systems and departments are two of the most pressing issues facing DevOps teams today.

According to a Gartner survey, 47% of digital workers struggle to find the information or data needed to perform their jobs effectively. Well, with Atlassian AI, this is all set to change.

Understanding Current DevOps Challenges

DevOps teams face several challenges in turning their product vision into reality. Here’s looking at the top 5:

  1. Complex projects: Today’s software projects are becoming increasingly complex. With multiple technologies, tools, and people involved, managing and optimizing them has become a Herculean task. Balancing quality with cost is also a challenging endeavor, bogging down DevOps teams.
  2. Global teams: DevOps teams are scattered across the world. Working on the same project from different time zones and using different tools negatively impacts communication and project management. It is challenging to have teams on the same page while providing them with a common platform to discuss progress and identify and act on issues.
  3. Multiple tools: Today’s DevOps teams use several tools to develop and deploy cutting-edge applications. This application sprawl leads to several issues, including difficulty finding the correct information at the right time, which can lead to incorrect or delayed decisions.
  4. Manual overload: Despite multiple tools, most DevOps teams are overburdened with manual tasks. Whether reading through thousands of lines of code to identify a bug or defect or finding the right solution, the time and effort wasted on these mundane tasks impact overall productivity and efficiency.
  5. Time to market: Resource constraints, increasing pressure on quality, and shrunken budgets directly affect time to market. Effectively and consistently managing stakeholder expectations and responding to new trends and changes with agility further delays development and deployment time.

Evaluating the Capabilities of Atlassian AI

At the Team’24 Event, Atlassian made several significant announcements.  One of the most important ones was around new capabilities and innovations in Atlassian AI.

Atlassian AI opens doors to a wide array of intelligent features aimed at transforming how products are developed and delivered.

Using the power of human-AI collaboration, DevOps resources can transform teamwork, derive instant insights from scattered data, and take action quickly and efficiently. They can communicate more effectively, summarize at scale, and promptly solve every issue using intelligent suggestions.

That said, here’s looking at the top capabilities of Atlassian AI:

  • AI coding tools

o   Coding assistants like Tabine offer quick and relevant in-line code suggestions, enabling developers to accelerate development. Trained on permissive open-source repositories, Tabine allows developers to leverage full-function code blocks or generate custom code blocks using natural language prompts.

o   AI-powered tool kits such as Codeium can generate autocomplete suggestions, clarify unfamiliar codebases, and modify and refactor code based on prompts. Developers can also use Codeium to translate code from one language to another while receiving necessary coding assistance using natural language-based search functionality.

o   Automated summaries enable DevOps teams to get a bird ‘ s-eye view of critical project data – with a simple button click. They can use Atlassian AI capabilities to summarize comments, meeting notes, project updates, and more – minimizing time for decision-making.

  • Natural language searches: DevOps teams can use Atlassian AI’s natural language search functionality to find the data they need when they need it quickly. They can provide simple prompts to search across data, tools, and platforms and get their hands on contextual and relevant results within their Atlassian experience. Using natural language searches, DevOps teams can save up to 77% of time and drive more focus and efforts on strategic priorities.
  • Automated support interactions: Atlassian AI enables service teams to automate Tier 1 support issues while allowing users 24/7 self-service support. The built-in AI engine in Jira Service Management leverages powerful Natural Language Processing and generative AI to ensure fast, conversational support. Virtual agents in JSM can deflect repetitive requests or route tickets to the right teams with pre-gathered context, allowing agents to focus on more important work.
  • Intelligent workflows: With Atlassian AI, DevOps teams can use several intelligent workflows to enhance productivity. For instance, they can automate tasks such as creating a flowchart design for new requests, reviewing documentation, cleaning Jira backlogs, or scanning code to unearth issues.
  • Virtual agents: Powered by Atlassian AI, Atlassian Rovo empowers DevOps teams to unlock knowledge and make better decisions. These out-of-the-box virtual agents range from workflow management agents to knowledge management agents, team culture agents, maintenance agents, and custom agents. These agents help teams uncover data that’s most relevant to them, learn as they go, and act faster.

Understanding the Benefits

As AI finds a permanent spot in the development lifecycle, DevOps teams can transform their development and delivery efforts to meet customers’ evolving needs. Atlassian AI delivers several compelling benefits, including:

  • Improved productivity by automating mundane and cumbersome tasks across coding, information searching, and data summarizing.
  • Better code quality by leveraging several coding tools and assistants that quicken the development timeline.
  • Faster decision-making by assimilating data across apps and processes and turning them into actionable insights.
  • Accelerated time-to-market by improving coding speed, communication, and issue identification and resolution.

Conclusion

Atlassian AI offers the ideal solution for DevOps teams facing challenges while developing and deploying cutting-edge products. Intelligent workflows, natural language search, coding assistance… There’s a lot Atlassian AI brings to the DevOps table. Exploit the various capabilities of Atlassian Intelligence today!

Learn how enreap can help you make the most of Atlassian AI as a specialized Atlassian partner!

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