Systems | Development | Analytics | API | Testing

Xray is one of the most popular Jira apps for testing and QA. It enables test management natively within Jira so that software teams can seamlessly integrate quality management into their everyday workflows. You can easily link requirements to Xray test cases within Jira to keep tabs on all tests, know where tests went right/wrong, and bring focus to quality at scale. Together Katalon and Xray streamline test automation and test management efforts for agile teams and their CI/CD pipelines.

Cloudera has been providing enterprise support for Apache NiFi since 2015, helping hundreds of organizations take control of their data movement pipelines on premises and in the public cloud. Working with these organizations has taught us a lot about the needs of developers and administrators when it comes to developing new dataflows and supporting them in mission-critical production environments.

Joint customers can move faster with more visibility across their entire data stack, helping data teams collaborate better with increased trust in their data.

At a macro level, software testing is an activity that seeks to find bugs or problems in software products. An essential subset of software testing is functional software testing, defined as a type of black-box testing method that focuses on the functionality of a software product. It’s a technique for ensuring that an application meets its requirements and specifications by executing test cases from the user’s perspective.

As we all know, APIs are absolutely everywhere. APIs power almost every aspect of a modern tech business and even non-tech businesses. You may have an internal API that is used by developers to power internal systems and external APIs which expose functionality more publicly. As with any functionality, APIs can also be used to drive revenue by selling them to users in need. Whether you’re selling a REST API, GraphQL API, or other API, learning how to sell your API has become a popular ask.

The growth of big data has scattered data sources throughout the enterprise, tucking them away in silos and making them hard to find. But there is more to data than just storing information in an operational data store or running analytics from a data warehouse. For example, regulated industries have requirements needing tighter control over the data.

The world is full of different types of goals. Consider football. The goal in football is at the end of the field. A runner either crosses the goal or they don't, when trying to make a touchdown. Or, consider basketball. In basketball, when a player shoots the ball, the player’s shot either goes through the net or it doesn’t. Alternatively, consider ice hockey. When a hockey player shoots the puck, it either goes into the net — or it doesn’t.