Sam Altman, the key visionary behind the popular adaption of Gen AI and essentially the father of ChatGPT, deemed it “unthinkable” to have products and services without AI integration in the future. I’m sure that among other beliefs that inspired him to make such claims, the need for intelligence beyond efficiency in the modern digital ecosystem was a key one. It only makes sense to rethink IT management in this context and replace our traditional methods with the benefits of AIOps.

Alright, I’m back. Time for part 2. In the first part, I covered how we handle bad data in batch processing. In particular, cutting out the bad data, replacing it, and running it again. But this strategy doesn’t work for immutable event streams as they are, well, immutable. You can’t cut out and replace bad data like you would in batch processed data sets.

We at Loadero regularly plan, implement and execute performance tests for clients which has led to us acquiring plenty of first-hand experience on the topic. Within this article we want to share with readers exactly what performance testing is, why it is valuable, as well as cover several factors that should be taken into consideration when deciding on the tests' implementation.

IFrames were used, and are still used, in many embed frameworks. After much experimentation, including many unsuccessful platforms, iframes have proven themselves to be a simple and powerful way to let partners customize your experience. However, their limitations are also known: Consequently, platform teams have tested and continue to test alternatives. Certain platforms now exclude iframes entirely, while others combine iframes with non-iframe alternatives.

Over one billion people worldwide live with some form of disability. Accessibility testing ensures that digital platforms are usable for everyone, including people with disabilities.

Retrieval Augmented Generation (RAG) is an intelligent assistant that helps you find exactly what you’re looking for in a pile of medical records. Like an X-ray shows you hidden details inside the body, RAG helps you quickly extract precise information from complex data. RAG provides instant, accurate answers—often visualized in charts or summaries that require analysts to produce manually. RAG combines two AI capabilities—retrieval systems and generative models.

BigQuery external datasets for Spanner let you browse, explore and query Spanner tables as if they were native BigQuery tables.

Many organizations struggle with fragmented testing approaches covering only individual components or features, leading to gaps in the system’s reliability and user experience.

The dynamic landscape of product development continuously increases the scope of what is demanded from quality engineering (QE) professionals. So, it is not surprising that workplace learning and upskilling are critical to the organizational success, as highlighted by Workplace Learning Report: Without a doubt, the more technical side of the skill spectrum - e.g.