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.

In today’s fast-paced cloud environment, understanding the pricing model of some of the best cloud monitoring tools like Datadog is essential in optimizing costs. With several features and adaptable pricing, clarifying Datadog costs and aligning them with your organization’s operational needs is vital for fully harnessing this robust monitoring tool. This guide simplifies Datadog pricing, offering a clear overview of its cost structure.

Many articles that you may find on the web discuss the importance of reducing Azure costs by identifying and removing unused resources. Still, they often fall short of providing practical methods to achieve this. However, Turbo360 has introduced a new feature that simplifies identifying idle or unattached Azure VM disks, eliminating the need for complex queries or PowerShell scripts.

The 2024 State of the Database Landscape survey showed that 79% of businesses are now using two or more database platforms (vs 62% in 2020). Businesses revealed that this growth was largely due to the differing use cases across each platform, as well as the need to increase flexibility. Despite these recognized benefits, increasing the diversity of your database platforms can bring its own set of challenges, including skillset requirements, data integration complexities, security, and monitoring.

No, I'm not talking about 'OpenAI', though you certainly can use it to assist in your API designs. I'm talking about the OpenAPI standard, a modern spec for defining REST APIs. If you're reading this, I probably don't need to tell you that REST APIs are ubiquitous in tech. Practically every company has at least one, whether it be an internal or customer facing API. While other types of APIs have been gaining traction the last few years (GraphQL, gRPC, etc), REST is here to stay.

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.