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Artificial intelligence is changing the way we execute our everyday operations. AI assistants are incredibly intelligent; they can write code, explain complex concepts, and answer any question you throw at them. However, they can't execute actions on their own. If you ask your AI assistant to “create a backup of my database,” it may provide you with clear instructions, run the CLI commands directly or in some cases, even trigger actions through connected agent workflows.

The AI landscape today feels a lot like the early days of the cloud: exciting, fast-moving, and completely fragmented. Every week, engineering teams are experimenting with dozens of large language models (LLMs) from providers like OpenAI, Anthropic, Google, Mistral, Meta, and beyond. They’re tweaking prompts, testing model performance, swapping context windows, and even running multiple models in parallel to figure out which one works best for each unique use case.

Happy Holidays, and happy almost new year from us at CloudZero! November is always a busy time! In case you missed the headlines, here’s what happened last month in relation to cloud and AI costs: Get the details below!

Bullshit and nonsense. But let’s take it from the beginning. The industry’s story goes something like this: Then, in the same breath: You see the contradiction already, right? The same industry that tells you “collect less, simplify, trust the experts” is also the industry where: This isn’t an observability strategy. It’s observability by hindsight. Right. Good. Now we’re having fun.