Operations | Monitoring | ITSM | DevOps | Cloud

Software deployment, a critical process in software development, refers to all the activities that make a software system available for use. It’s the stage where all the hard work of creating software culminates into something tangible that users can interact with. But before we delve into its complexities, let’s first understand the basics of software deployment.

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.

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.

Reliability metrics in software development are metrics that help teams quantify how dependable and consistent their software systems are over time. By converting a wide range of technical properties into hard data, these provide quantifiable information to understand the probability of software running failure-free in a given environment over time. These metrics are a subset of developer-focused key performance indicators (KPIs), data that is gathered to emphasize developers' output.