Operations | Monitoring | ITSM | DevOps | Cloud

A benchmark can be interpreted as a standard of comparison used to assess something. In everyday life, for example, when we want to buy a new cellphone and want to know which one is faster, we can see the speed test (benchmark) by measuring how fast the cellphone opens applications or runs games. From there, we can compare which cellphone is better based on the numbers produced.

Imagine spending weeks grinding through SQL tutorials, practicing syntax, and refining your queries in your spare time. But when the interviewer throws a complex JOIN + subquery at you, your brain suddenly hits a 404. It happens to the best of us. However, most candidates crash and burn—not because they lack knowledge, but because they prepare like students instead of engineers. They memorize syntax, pray for predictable questions, and freeze the moment they’re asked to think, not recite.

Without SQL aggregate functions, databases would be nothing more than glorified spreadsheets. These functions—SUM(), COUNT(), AVG(), MIN(), and MAX() —do the heavy lifting in analytics. They process massive datasets, transforming scattered records into clear, usable insights that drive decision-making. But while aggregation simplifies data, it can also slow things down.

To start securely and efficiently, Linux systems follow a carefully orchestrated sequence of steps to initialize firmware and manage services. Applying security patches to the software responsible for some of these early steps of Linux startup often requires a full system reboot.

New IDC study, co-sponsored by Canonical and Google Cloud, reveals the challenges and opportunities for organizations securing their software supply chains. Today, Canonical and Google Cloud released findings from a joint research project conducted by the International Data Corporation (IDC) that sheds light on the critical challenges organizations face in securing their software supply chains. The report, “The State of Software Supply Chains.

You can assess your company’s financial health using a number of SaaS metrics, depending on the type of business you are in. Among the most useful is the SaaS Magic Number. So, why is it called the SaaS Magic Number, and how do you calculate it? And why is it so important to track your SaaS Magic Number regularly?

Resource exhaustion at a node remains a critical issue. However, the automation of deployment and management of containerized applications is executed relatively efficiently in Kubernetes. When a node is low on resources—as in CPU, memory, or storage—a workload may suffer from failures, degraded performance, and eviction.

Software development is changing fast, and here at GitKraken, we’re excited to be at the forefront. We’re entering a new era—one where AI is helping developers rather than trying to replace them. Our goal is to put that power to work for developers—embedded in your workflows, on your terms. We’ve been listening closely to feedback from our community—developers, team leads, engineering managers, and our enterprise customers.