Operations | Monitoring | ITSM | DevOps | Cloud

The UK government’s recently announced AI Opportunities Action Plan marks an ambitious step forward in harnessing artificial intelligence to drive economic growth and societal progress. As the CEO of Civo, a UK-founded company committed to reimagining the cloud with sustainability, innovation, and sovereignty at its core, I welcome this bold vision.

Traditional programming is built around well-defined inputs and deterministic logic. Developers write functions that take structured inputs, apply a predefined set of operations, and return a structured output. This model works well when the input space is predictable, but it struggles with problems where inputs are ambiguous, unstructured, or constantly evolving.

Jeff Foster, Director of Technology & Innovation at Redgate, explains how Redgate is approaching the AI revolution. As we celebrate Redgate’s 25th anniversary, it’s a great time to reflect on how far we’ve come and where we’re headed. Our longstanding mantra has been “ingeniously simple” software – tools that empower users to accomplish tasks they might not have thought possible.

It’s 3:17 AM. Your phone is buzzing with Slack notifications in the on-call channel. The API error rate has spiked to 60%. You crawl to your laptop, SSH into the prod cluster, and you’re buried under terabytes of logs. The noise is overwhelming.

Generative AI is transforming industries by automating tasks and delivering AI tools, such as AI assistant Sumo Logic Mo Copilot, to enhance operational efficiency. But, these advancements also challenge traditional quality engineering (QE) methodologies. Unlike conventional software testing, AI models produce dynamic, context-sensitive outputs, requiring a new approach to validation and testing. At Sumo Logic, we faced similar challenges while testing Mo Copilot.

In July 2024, a routine network configuration change at Microsoft caused a global outage that left millions without access for 90 minutes. The culprit, however, was a network issue within the Microsoft WAN that disrupted global routes. Unfortunately, this isn’t a one-off network outage but a part of a broader, troubling trend. Modern Network Operation Centers (NOCs) are far too siloed and broken to handle the growing complexity of modern networks.

Cofounder Doreen Jacobi spoke with several of our customers about the revolution AI is bringing to incident management. Artificial Intelligence has seamlessly integrated into our daily lives, often in ways we barely notice. But what does that actually mean for industries facing complex challenges, like incident management? What real benefits does AI bring today, and how might it shape the future?

I attended ElasticON recently where we spent the day with our NYC Elastic community, talking about the combined value of vector databases using retrieval augmented generation (RAG) to feed large language models (LLMs) for next-level generative AI (GenAI) results. Elastic’s CTO and Founder Shay Banon kicked off his keynote with an important message: GenAI is not magic.