While “America runs on Dunkin”, IT increasingly runs on Linux. Between being open-source and highly customizable, everything from video games to enterprise servers can run on Linux. When cloud services took over the corporate IT environment, they brought Linux with them in the form of virtual servers and containers. Meanwhile, developers increasingly use Linux-based Docker to containerize applications and Kubernetes to manage the deployments.

This is one of a series of blog posts that explain how the Cribl SRE team builds, optimizes, and operates a robust Observability suite using Cribl’s products. If you haven’t, we encourage you to read the previous blog about how the Cribl SRE team uses our own products to achieve scalable observability. We installed Cribl Edge on the machines we manage for our users and use it to gather metrics.

The latest LM Studio 0.3 update has made Elastic’s AI Assistant for Security run with an LM Studio-hosted model easier and faster. In this blog, Elastic and LM Studio teams will show you how to get started in minutes. You no longer need to set up a proxy if you work on the same network or locally on your machine.

As organizations increasingly look to leverage the benefits of both on-premises and cloud environments, hybrid cloud architecture has gained traction. Today, 75% of organizations worldwide have adopted a hybrid cloud strategy. However, hybrid IT isn’t for everyone.

AWS Auto scaling Auto scaling is a powerful feature that allows your cloud infrastructure to dynamically adjust capacity based on demand, optimizing both performance and cost. However, to truly harness the power of Auto Scaling groups in AWS, you need to move beyond basic setup and dive into fine-tuning with advanced monitoring. This blog will guide you through advanced strategies for optimizing your AWS auto scaling using enhanced monitoring functionalities.

The state of industries has come a long way since the Industrial Revolution with new technologies such as smart devices, the internet, and the cloud. The Industrial Internet of Things (IIoT) is a network of industrial components that share and process data to gain insights. But as IIoT involves sensitive data and life-critical operations, this also comes with various IIoT cloud security challenges. Therefore, it is important to strengthen security.

Autoscaling in cloud computing is the ability of a system to adjust its resources in response to changes in demand automatically. This guarantees that applications always have the resources they need to perform optimally, even during periods of high traffic. Autoscaling eliminates manual intervention, allowing your dev team time to focus on your product. All major cloud providers like AWS, Azure, and Google Cloud Platform offer robust autoscaling solutions with many features and capabilities.

If The Notorious BIG – the artist behind the iconic song "Mo Money Mo Problems" – had been an IT operations engineer, he might instead have labeled his hit "Mo Clouds Mo Problems." Why? Because the more clouds you have to manage and monitor, the more problems you're likely to run into.