Operations | Monitoring | ITSM | DevOps | Cloud

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 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.

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.

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.