Operations | Monitoring | ITSM | DevOps | Cloud

AIOps, which stands for Artificial Intelligence for IT Operations, is here to stay. The truth is that leveraging artificial intelligence (AI) for ITOps offers a range of benefits that can significantly improve the efficiency, reliability, and performance of IT operations. So keep on reading as we explore AIOps software potential. From automating routine tasks to predicting future issues and enhancing decision-making, as well as practical scenarios as strategies for its implementation.

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Today, we are pleased to announce the general availability of Elastic 8.13.

Like humans, machines need to continually learn from non-stationary information streams. While this is a natural skill for humans, it’s challenging for neural networks-based AI machines. One inherent problem in artificial neural networks is the phenomenon of catastrophic forgetting. Deep learning researchers are working extensively to solve this problem in their pursuit of AI agents that can continually learn like humans.

In the ever-evolving landscape of the digital era, the backbone of our interconnected world is woven together by an intricate web of networks. Behind the scenes, ensuring the seamless operation of these networks are the unsung heroes known as network technicians. These skilled professionals wield their network toolkits to maintain, troubleshoot, and optimize the complex systems that keep our data flowing and communications thriving.

In today's world, networks are crucial for businesses to communicate and share data smoothly. But keeping networks running well and staying ahead of performance issues can be tricky. That's where network visibility tools come in handy. These tools give a complete view of a network, helping IT pros see everything that's happening and fix any issues quickly.

Microservice mediator APIs provide a flexible, scalable, and decentralized approach to microservices communication, enabling organizations to build robust, modular, and maintainable applications. They shield microservices from the details of the other implementations and promote loose coupling, helping to ensure autonomy, scalability, and independence among microservices.

In one of our latest posts, StackState Co-Founder Mark Bakker described how eBPF revolutionizes observability and how StackState’s agents rely heavily on eBPF to capture and analyze the data moving through your cluster. Today, we’re looking at an example where our eBPF code failed and — by diving deep into the intricacies of eBPF implementation in the Linux kernel — share the tale of how we fixed it using even more eBPF.