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The latest News and Information on DevOps, CI/CD, Automation and related technologies.

The pendulum swings back: colocation as a cost control strategy

The evolution of public cloud over the past few years has been remarkable. Digital transformation, remote work, and AI have created breakneck growth. Back in 2018, before anyone uttered the words COVID or ChatGPT, there were already big drivers for public cloud. The global digital transformation market size was valued at $320 billion, and set for 18% annual growth, to reach a projected $695 billion by 2025.

CPU vs GPU: What's the Difference?

If you've ever delved into the intricacies of PC building or taken your first steps in an introductory Computer Science class, chances are you've encountered the ubiquitous term – GPU. For many gaming enthusiasts, myself included, GPUs are the magic component that gives you more frames in your favorite FPS game, while CPUs are the component where our code finds its execution space.

AIOps as a Service for MSPs: What to Look For

AIOps is a game changer for MSPs. But how do you implement AIOps to ensure you get those game-changing benefits? Chances are, you’re not interested in spending the resources and time required to build it yourself with all of the development, testing, maintenance, etc. that entails. Instead, AIOps as a service provides you with the capabilities to better manage the IT infrastructure and operations of multiple clients.

What do quality engineers do?

Quality engineering (QE), or software quality engineering (SQE), is a discipline within software development focused on ensuring the quality, reliability, and performance of software products. With an increase in development environment complexity in recent years, the focus has shifted back from detecting defects in later stages, as QA has typically done, to proactively ensuring quality throughout the entire development lifecycle.

Secure your AI workloads with confidential VMs

AI models run on large amounts of good quality data, and when it comes to sensitive tasks like medical diagnosis or financial risk assessments, you need access to private data during both training and inference. When performing machine learning tasks in the cloud, enterprises are understandably concerned about data privacy as well as their model’s intellectual property. Additionally, stringent industry regulations often prohibit the sharing of such data.

What Is AWS Compute Optimizer? A Newbie-Friendly Guide

Amazon Web Services (AWS) offers the convenience of choosing specific virtual machine combinations to meet your compute needs. Unlike traditional data centers, you can also scale your cloud resources automatically to meet fluctuating workload needs. The best part is that you can rightsize your workload requirements to specific instance types (VM types) offered by AWS. By hand, this takes a lot of time and is prone to errors. This is where AWS Compute Optimizer comes into play.