Operations | Monitoring | ITSM | DevOps | Cloud

In a previous blog, we talked about patterns to run a database in a highly available manner. In this blog, we present our recipe for MySQL high availability. We will also explain how our solution interacts with K8s objects to provide some of its features.

On 16 July the world celebrates International Artificial Appreciation Day. In the previous century, science fiction often covered topics and inventions that are now closer to science fact, such as humanoid robots. In the 50s, artificial intelligence met both great successes, including algorithm development, and big failures, caused by compute power constraints.

Automotive as an industry is constantly looking for ways to improve its processes and efficiency. The one common tool that is at the intersection of all software development activities is the operating system (OS). From advanced simulation tools to new vehicle designs, the OS has to be reliable and provide the best platforms for a maximum number of purposes.

Large language models (LLMs) are machine-learning models specialised in understanding natural language. They became famous once ChatGPT was widely adopted around the world, but they have applications beyond chatbots. LLMs are suitable to generate translations or content summaries. This blog will explain large language models (LLMs), including their benefits, challenges, famous projects and what the future holds.

Kubernetes 1.28 is currently planned to be released on the 15th of August 2023. Canonical Kubernetes 1.28 is scheduled to release swiftly afterwards, with MicroK8s 1.28 expected to be generally available within 24 hours of upstream, and Charmed Kubernetes expected to follow within days. We consistently follow the upstream release cadence to provide our users and customers with the latest improvements and fixes, together with security maintenance and enterprise support for Kubernetes on Ubuntu.

In the traditional computing threat model, privileged system software like the hypervisor, host OS, firmware, and DMA-capable devices were all granted access to the data and code of your workloads. This was widely accepted because it seemed necessary for the system managing VM resources (memory, execution, and hardware access) to also have access to the workload’s data. How else could it manage it after all?

Smart homes are changing. A modern smart home typically isn’t a self-contained, set-it-and-forget-it, custom installation. It’s a hyper-connected set of devices that work together to automate and enhance the users’ living space. Today’s smart homes contain devices from many manufacturers, running dozens of protocols, interfacing with multiple cloud backends.

In the constantly evolving world of software development and IT management, choosing the right operating system for your enterprise developers is a strategic choice. Ubuntu vs macOS, which is right for you? Our latest whitepaper helps you answer this question and make an informed decision. This blog post provides a sneak peek into our findings covering both the developer landscape, and the key considerations for IT administrators. Considering macOS or Linux for your organisation?

Note: This post is co-authored by Simon Aronsson, Senior Engineering Manager for Canonical Observability Stack. AI/ML is moving beyond the experimentation phase. This involves a shift in the way of operating because productising AI involves many sophisticated processes. Machine learning operations (MLOps) is a new practice that ensures ML workflow automation in a scalable and efficient manner. But how do you make MLOps observable?

The Canonical Data Fabric team is pleased to announce the first beta release of Charmed Spark, our solution for Apache Spark. Apache Spark is a free, open source software framework for developing distributed, parallel processing jobs. It’s popular with data engineers and data scientists alike when building data pipelines for both batch and continuous data processing at scale.