Operations | Monitoring | ITSM | DevOps | Cloud

Today, we’re releasing InfluxDB 3.4 for Core and Enterprise, as well as our 1.2 update for the Explorer UI. This release focuses on developer efficiency, operational automation, and targeted security enhancements, giving teams faster setup, smoother workflows, and stronger guardrails for production use. InfluxDB 3 Core is free and open source, optimized for recent data, and licensed under MIT and Apache 2.

The hype around generative AI has led many IT teams to experiment with plugging generic GPT models into their workflows. On paper, this is the beginning of true AI networking, featuring conversational interfaces, instant summaries, and faster troubleshooting. However, as we discussed in the previous post, “Why Your IT Copilot Needs Context, Not Just Data,” copilots are only as effective as the intelligence behind them.

As organizations increasingly adopt multi-cloud strategies, identifying areas to reduce cloud spend has become highly complex and time consuming. While there are many reasons that organizations choose to run their infrastructure in a multi-cloud environment, many do so to comply with regional data requirements, take advantage of best-of-breed offerings, or avoid vendor lock-in.

It starts like this. You wake up groggily and stumble into the kitchen. The coffee machine is already brewing your favourite blend. But that’s not the surprise. It's the message on your phone: "Coffee beans restocked. $10 paid. Delivery by noon." You didn’t place an order. You didn't lift a finger. Your machine did it for you. Welcome to 2025, where your devices aren't just smart, they're economically independent. These are machine customers (custobots). They negotiate. They pay.

Your Mac’s GPU is a massively parallel processor that handles anything from animating the UI to heavy lifting in video editors, 3D tools, games, and on-device machine learning models. Think Final Cut Pro exports, Blender renders, Stable Diffusion, WebGPU demos, or shader builds in Xcode - which are all tasks that require heavy GPU.

A couple months ago, we sent out a survey to all our users asking what they like about Oh Dear, how they use it, and how we could improve our service. One of the things that was asked a lot was ping and TCP port monitoring. The past few months we worked hard to add this kind of monitoring to our service. And while building it, we touched upon other parts of our service and improved lots of little things. And I'm proud to share that we now have shipped it all! Let's go through it!

When developing software, the longer you intend to keep a system around, the more important it becomes to prioritize its code quality. But as more organizations move toward microservice architectures and adopt agentic AI and LLMs into their development workflows, many engineering teams have increased their emphasis on accelerating developer velocity, often at the expense of code quality. This can often result in code that fails to meet standards for performance, reliability, and security.

The zettabyte era of data is alive and well. Every tool in your tech stack now has some sort of AI functionality, while middleware sprawl and feature wars between vendors become daily battles.

Are you interested in learning about API monitoring? Then you’ve come to the right article. Below, we explain what APIs are and why they’re valuable, explore the basics of API monitoring, and wrap up with practical advice on how to get comprehensive API monitoring in your organization.