Operations | Monitoring | ITSM | DevOps | Cloud

It’s never easy when layoffs hit your organization. In addition to the personal impact of losing friends and coworkers from your team, those who remain are left trying to achieve the same business goals with less people and resources. Unfortunately, layoffs and restructuring have become a common part of business. But you’re not alone. Your partners (including Gremlin) are here to help you navigate your new reality.

Earlier this year, Mark Boost and Dinesh Majrekar had the chance to sit down with Solomon Hykes at Navigate North America 2024 to speak about his thoughts on the future of tech. Solomon is best known as the Founder, former Chief Technology Officer, and Chief Architect of Docker, and is currently the founder of Dagger, a programmable CI/CD engine that runs pipelines in containers, allowing development in various programming languages and execution across diverse environments.

Look, we've all been there: there's a term, you've heard it one hundred times. You've nodded as others said it in meetings. And now, you've started to say it. The only tiny insignificant problem is that you're not 100% sure what it actually means or how it's different from another similar term. I feel you. So I wrote this DevOps glossary with my highly opinionated definitions of common DevOps industry terms.

Serverless architectures have revolutionized how businesses deploy applications, offering scalability and cost efficiency by abstracting infrastructure management. This model, charging only for resources consumed, poses unique budgeting and cost optimization challenges due to its variable pricing structure. Navigating cloud costs in a serverless environment requires a nuanced understanding of leveraging this technology’s benefit while effectively managing expenses.

In the digital era, where data reigns supreme, the ability to extract meaningful insights from vast datasets has become indispensable. Though we have many data sources and data processing languages, SQL (Structured Query Language) stands as a cornerstone in this realm, empowering analysts, and data scientists to navigate through intricate databases with ease.

Data centers are the backbone of our increasingly interconnected world. They power everything from streaming services to AI, handling vast amounts of data every second. However, this technological advancement comes at a cost, with energy consumption being a significant concern. In fact, data center energy consumption is forecasted to double by 2026. As we venture further into 2024, it is important to review some of the key trends around energy consumption in data centers.