The term High Performance Computing, HPC, evokes a lot of powerful emotions whenever mentioned. Even people who do not necessarily have vocational knowledge of hardware and software will have an inkling of understanding of what it’s all about; HPC solves problems at speed and scale that cannot be achieved with standard, traditional compute resources. But the speed and the scale introduce a range of problems of their own.

As we’ve seen throughout this series, a design pattern is a general solution that has been proven to solve a repeatedly occurring problem when designing software. In my previous blog posts, we examined the basics of the software operator design pattern, the forces impacting it, and the advantages and disadvantages of using it. But how does the software operator pattern actually work?

2023 was an epic year for artificial intelligence. In a year when industry raced faster than academia in machine learning (source), the state of the art for AI evolved to include increasingly larger amounts of data, and bringing to bear sufficient computing resources to support new use cases remained a challenge for many organisations. With the rise of AI, concerns were not far behind.

Whenever it comes to a small-scale private cloud infrastructure project roll-out, organisations usually face a serious dilemma. The implementation process often seems complex due to a lack of knowledge, tricky migrations and an immediate need from management to run various extensions, such as Kubernetes, on top.

As the adoption of confidential computing continues to grow, customers expect their confidential workloads to be strongly separated from their underlying cloud providers. To better align with these user requirements, Canonical is excited to announce ephemeral OS disks for Ubuntu confidential VMs (CVMs) on Microsoft Azure – a new solution that enables you to store disks on your VM’s OS cache disk or temp/resource disk, without needing to save to any remote Azure Storage.