The growing influence of containers, microservices, and cloud-native computing is changing the way developers think about building and deploying applications. As a result, the need for a more flexible and dynamic approach to DevOps is increasing. This is where the role of languages comes into play.

In the past, DevOps teams were largely reliant on a limited set of languages, such as Bash and Python. However, as the complexity of applications has increased, so has the need for a wider range of languages. Today, DevOps teams are using a variety of languages, including Go, Rust, and Node.js, to build and manage their applications.

This change is being driven by several factors, including the need for higher performance, the need for greater flexibility, and the need for a more collaborative environment. Go, for example, is a high-performance language that is well-suited for building microservices. Rust is a memory-safe language that is becoming increasingly popular for writing systems software. And Node.js is a JavaScript runtime that is widely used for building web applications.

The use of a wider range of languages is also leading to a more collaborative environment. In the past, DevOps teams were often siloed, with developers working in one language and operations teams working in another. However, as the use of multiple languages has become more common, teams are finding that they need to work together more closely. This is leading to a more collaborative and productive environment.

The changing landscape of languages in DevOps is having a number of benefits. First, it is leading to the development of more innovative and scalable applications. Second, it is making it easier for teams to collaborate and work together. And third, it is leading to a more efficient and productive development process.

As the use of containers, microservices, and cloud-native computing continues to grow, it is likely that the role of languages in DevOps will continue to evolve. In the future, we can expect to see even more languages being used in a wider range of ways. This will continue to drive innovation and improve the way that applications are built and deployed.

Collaboration and productivity software firm Atlassian on Wednesday announced a bevy of new capabilities within its Jira and Confluence platforms that the company says reflect the its ongoing investment in machine learning. Using ML, Atlassian said it has built predictive, intelligent services into its products that will make teams more productive.

More specifically, Atlassian is announcing smart search in Confluence Cloud and Jira Cloud and a predictive pull request experience in Bitbucket. Another feature rolling out soon will enable IT teams to cluster similar tickets in Jira Service Desk for improved efficiencies.

Atlassian has also added intelligent filter controls to the search experience in Jira Software and Confluence. The controls can predict what filters are likely to be used in order to narrow down the search scope.

Meanwhile, a new predictive user pickers in Jira and Confluence will suggest relevant coworkers to collaborate with in different scenarios across Atlassian products. The predictive pickers feature builds on a similar predictive user mentions feature that compiles a list of recommended people to bring into a project based on the specifics of the work.

For IT teams, Atlassian is planning to roll out a feature that will allow admins to cluster tickets in Jira Service Desk that have common overlap. The feature uses predictive, natural language technology that will also be used in Jira software to group together similar bug reports or features requests, linking incidents to tickets in Jira Service Desk and displaying related knowledge base articles in Confluence, Atlassian said.

“This is just the start of Atlassian’s work to incorporate smarts into our products and platform,” said Shihab Hamid, head of product for the Atlassian Teamwork Platform. “We’re always looking for more ways to alleviate repetitive work so that teams can focus on their core mission. We’re building the smartest work collaboration platform on the market – because we’ve learned from how the best teams work.”