Operations | Monitoring | ITSM | DevOps | Cloud

The Biden-Harris administration released the National Cybersecurity Strategy on March 2, 2023. The national cyber strategy document establishes expectations and offers guidance on how the United States government intends to protect the country’s digital assets and critical infrastructure from the threat of cyberattacks.

Automation has been a bit of a buzzword in the IT community in the last few years. Companies around the world are looking for ways to scale and automate routine tasks so they can focus on more strategic initiatives. But “automation” is a word that can cover a lot of workflows and can mean something different to every team. What do we mean when we talk about automation here at LogicMonitor?

We have to come clean. During KubeCon, we experienced an incident that we weren’t ready to discuss until now. This incident caused quite a disruption and, had it been left unresolved, would have had a massive snowball effect. At the time, we didn’t want to raise any alarms, so we kept it quiet while our team rallied to resolve it. And to be honest, most folks probably didn’t even realize that it happened since we moved so quickly.

In SaaS companies, engineers are the biggest influencers to cloud costs. They choose the infrastructure, build the products, and produce the code. Unfortunately, having this power means engineering managers are often asked to predict cloud spend months or even years into the future. An executive or a head of finance might approach the engineering head and ask how much the company will spend on cloud costs next year, thinking he or she should naturally have the answer.

Virtualization has become an essential component of modern IT infrastructure, enabling organizations to optimize their resources, improve efficiency, and reduce costs. Microsoft Hyper-V, a popular virtualization technology, allows for the creation and management of virtual machines (VMs) on a physical server. It enables multiple operating systems to run simultaneously on the same hardware, providing both flexibility and scalability.

There is rapid adoption of artificial intelligence (AI) and machine learning (ML) in the finance sector. AI in banking is reshaping client experiences, including communication with financial service providers (for example, chat bots). Banks are exploring ways to use AI/ML to handle the high volume of loan applications and to improve their underwriting process.

The goal of capacity planning is to match resources with demand. There are essentially three outcomes from this analysis. You can underestimate the resources you need (underprovision), which can hurt performance. You can overestimate (overprovision), which adds unnecessary costs. Or you can get it just right (rightsized). And, of course, you want to be rightsized at the lowest possible cost. Because many factors go into cloud capacity planning, it can feel like more of an art than a science.

If you’re part of a software engineering team in digital health, medtech, medical devices, Software as a Medical Device (SaMD), etc. you have to comply with regulatory standards. And one of the biggest challenges engineering leads have in this sector is figuring out what they have to do to achieve software delivery compliance.