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Today, we are excited to announce our partnership with Pruna AI. Pruna AI is the optimization engine built to simplify and accelerate scalable inference. Koyeb offers a serverless cloud platform for teams to deploy ML and AI models on high-performance GPUs, CPUs, and accelerators - globally. By combining Pruna with Koyeb, you can speed up your model optimizations, achieve 5x faster inference speeds, and run them on scalable, high-performance serverless infrastructure.

When evaluating a DevOps testing service, software teams should ask the following questions — it can mean the difference between quickly shipping high-quality code and bottlenecking releases, or having bugs slip into production: In this article, we review five top DevOps testing services, starting with our own, Rainforest QA. We show how we help teams ship high-quality code without constant bottlenecks dragging down the release pipeline.

BigQuery DataFrames 2.0 brings multimodal data processing and AI into your BigQuery Python workflows, and enables larger Pythonic data science.

The retail industry has been shaped and fundamentally transformed by disruptive technologies in the past decade. From AI assisted customer service experiences to advanced robotics in operations, retailers are pursuing new technologies to address margin strains and rising customer expectations.

Collaboration across IT is increasingly critical to having a smooth and effective software release cadence. As software complexity grows, it becomes more difficult for individual team members to have a thorough understanding of all the different elements that comprise a successful software application.

Two years after Seagate first shared their AI and MLOps success story, the data storage leader is now revealing how far they've come since then. In this blog post, you’ll see how the team manages thousands of AI models in production with only a few team members. This is thanks to their AI factory, whichdoes the heavy lifting of automated processes like monitoring, testing, mocking and more.

At Ably's February fan engagement event, Sam Renouf, CEO of the Professional Triathletes Organisation (PTO), captured the essence of impactful fan engagement with an observation about motorsports: Sam's insight points to a transformation across sports, and fan experiences more generally: that effective engagement now depends on meaningful realtime data storytelling.

QA automation means turning manual test steps into code so they can run faster, more consistently, and at scale. Instead of executing the same test cases over and over, testers write scripts that do the work for them. These scripts validate core functionality, trigger workflows, and report pass/fail status automatically. We'll show you how to do it in this article, in-depth.

Agile and DevOps changed how we build software. Fast feedback, continuous delivery, and constant iteration are the new normal. But the faster you move, the more you risk breaking things—especially if your testing can’t keep up. That’s where test automation comes in. Not as a silver bullet, but as a strategic foundation for scaling quality at speed.

Choosing the right storage format is crucial for optimizing performance, cost, and flexibility when working with cloud data. While file formats like Apache Parquet and Avro have been popular choices for storing data in data lakes, in recent years a new category called table formats has emerged to provide more management capabilities on top of these files. Among these, Apache Iceberg has been gaining significant adoption and momentum. So what exactly is Iceberg and why does it matter? Let’s dive in.