Operations | Monitoring | ITSM | DevOps | Cloud

Frameworks evolve, libraries change, and APIs get rewritten. But your ORM decision? That one sticks—it shapes your architecture, guides how your team writes queries, and affects how painful refactors become later on. In.NET, this choice often narrows to Dapper and NHibernate—two trusted tools with fundamentally different approaches. NHibernate offers deep abstraction, rich mappings, and built-in caching, while Dapper gives you raw speed, total SQL control, and zero overhead.

In.NET, data access has evolved, but finding the right tool still comes down to control vs. convenience. You have to decide: do you prefer to write every query or move faster with something easier to maintain? Can you manage the boilerplate, or would you rather work with leaner syntax? For many.NET developers, the answers point to one of two popular tools—ADO.NET or Dapper. ADO.NET gives you complete control but with boilerplate and manual overhead.

When I first started writing Go software a little over a decade ago, one of the features I found particularly intriguing was the ability to build statically-linked binaries for multiple operating systems and architectures without a lot of headache. This build toolchain feature is widely relied upon by nearly all Go developers, especially when needing to build multi-arch container images destined to be run in a Kubernetes cluster consisting of amd64 and/or arm64 nodes.

Monitoring doesn't always need to be complex. In this guide, we'll show you how to turn raw logs into usable metrics using a lightweight open-source setup with no ELK stack and no heavy lifting. We'll use Loki, Python, and Telegraf to convert logs into Graphite metrics you can easily monitor or alert on. This is perfect for system admins, DevOps beginners, or anyone curious about building more innovative monitoring pipelines from scratch.

Microsoft Azure offers over 150 cloud services across IaaS, PaaS, and SaaS. But for many teams, it can be expensive, complex, and hard to tailor to specific needs. If the platform feels like overkill or just isn’t the right fit, this guide covers the best Azure alternatives — and what makes each one worth considering.

Cribl’s powerful data processing engine is designed specifically for IT and Security teams, enabling organizations to take control of their ever-growing data volumes. By simplifying the management, processing, and analysis of telemetry data, such as logs, metrics, and traces, generated across complex digital environments. This empowers organizations with the choice, control, and flexibility to manage and analyze data, allowing them to adapt to evolving needs and strategies.

In the fast-moving world of IT operations, Gartner’s research provides critical insight into where the market is heading, and which vendors are leading the charge. In the past year, Resolve earned three powerful validations of its innovation and impact: These distinctions reflect more than technical capabilities. They reinforce Resolve’s mission to drive a new era of intelligent, autonomous IT orchestration through agentic automation.

GitHub, a platform offering version control and collaboration services for software development, plays a pivotal role in managing code, tracking issues and pull requests, and deploying software. As millions of developers and businesses rely on GitHub's infrastructure, its reliability is crucial. Tracking GitHub's outages and understanding their frequency is essential, particularly for organizations that depend on the platform for critical processes.

Identity management is vitally important in cybersecurity. Every time someone tries to access your networks, systems, or resources, it’s critical that you are verifying that these attempts are valid and legitimate, and that they match a real, authenticated user. The way that this tends to be handled in cyber security is through Identity and Access Management (IAM), most commonly by using third-party Identity Providers (IdPs).

When Java web applications experience slowdowns or crashes, the culprit is often the Tomcat server. For DevOps engineers overseeing critical applications, proactive monitoring is crucial for ensuring optimal performance and reliability. In this guide, we'll explore the essential aspects of monitoring Apache Tomcat servers, focusing on the key metrics to track, setting up robust monitoring systems, and troubleshooting common performance issues that could impact your application’s stability.