Machine learning is more accessible than ever, with datasets available online and Jupyter notebooks providing an easy way to explore and train models. In building a model, we often forget that it will be incorporated into an application that will provide value to the user. Therefore, we wanted to demonstrate how we can "use" the models we build in an application.
Ballerina is an open source programming language for the cloud that makes it easier to use, combine and create network services. In addition to the powerful language features, it comes with a rich standard library, which covers network data, messaging and communication protocols.
Apache Kafka is an open-source distributed event streaming platform used by thousands of companies for high-performance data pipelines, streaming analytics, data integration, and mission-critical applications. Administrators, developers, and data engineers who use Kafka clusters struggle to understand what is happening in their Kafka implementations.
In an episode of our Mobile DevOps is a thing! podcast, we talked to Swift developer John Sundell about Mobile DevOps and his consultancy services, among other things.
What are the best practices of the mobile team behind one of the world’s leading buy-and-sell platforms for improving productivity and the developer experience? Read on for the five main learnings from our recent customer story.
Businesses today adapt to change with breathtaking speed. Lines of business now follow their products out the door digitally and continue tracking usage throughout the lifecycle. This gives companies valuable insights into how customers use and interact with their products, enabling them to analyze and evolve solutions while nurturing customer relationships.
With the rise of drone usage, it’s easier to take aerial footage than ever before. The resulting data can trigger quick, effective action; removing guesswork and increasing aerial awareness, which can have profound implications on growing profits and trimming expenses. And as drone use rises, so does the usage of AI, to navigate, detect, identify, and track meaningful artifacts and objects.
All your app-level settings are available on one page to simplify handling test devices, notifications, and more.
Monorepos are extremely helpful when working with larger codebases. But they also come with additional management costs. In this article, we will go through the process of managing a monorepo with a tool like Melos and set up our repository for CI/CD with Codemagic.
Now in beta: break your Workflows into Stages, build and test in parallel, shard your tests, and get faster PR feedback.
