It’s 10:00 p.m. on a Sunday when my 9th grader bursts into my room in tears. She says she doesn’t understand anything about algebra and is doomed to fail. I jump into supermom mode only to discover I don’t remember anything about high school math. So, I do what any supermom does in 2024 and head to ChatGPT for help. These generative AI chatbots are amazing. I quickly get a detailed explanation of how to solve all her problems.

Most engineers will tell you this: Troubleshooting today feels like trying to find your way out of a wild jungle, in the middle of a storm, at night, while a countdown clock is running. In other words, it’s ambiguous, nerve-racking, and plain difficult. But should this be the norm?

Mattermost is excited to announce the release of v10.0, bringing with it a groundbreaking enhancement to our Mattermost Copilot plugin: support for multiple large language models (multi-LLM). This feature, designed to empower mission-critical enterprises, adds a new layer of flexibility, privacy, and control to your AI-driven workflows.

Komodor, the company that automates Kubernetes management, today announced Klaudia, the first Generative AI (GenAI) agent for troubleshooting and remediating operational issues, as well as optimizing Kubernetes environments. Integrated within the Komodor Kubernetes Management Platform, Klaudia simplifies and accelerates root-cause analysis, empowering both platform and application teams with precise diagnostics to resolve issues with unprecedented speed and precision.

Migrating applications from a Platform as a Service (PaaS) to a cloud platform is often a complex, time-consuming, and expensive process. Companies using PaaS platforms like Heroku, Render, Fly.io, Railway, Vercel, Netlify, and many others frequently delay this migration despite needing enhanced security, compliance, technical capabilities, and greater control over their infrastructure.

Large language models are algorithms designed to understand, generate, and manipulate human language. State-of-the-art large language models include OpenAI’s GPT-4o, Anthropic Claude Sonnet 3.5, and Meta LLaMA 3.1. They are built using neural networks with billions or even trillions of parameters. They are trained on vast datasets that can include text from the internet, books, code, and other information sources.