Operations | Monitoring | ITSM | DevOps | Cloud

The latest News and Information on Application Performance Monitoring and related technologies.

Azure Data Factory Monitoring Integration

Microsoft Azure Data Factory is a cloud-based data integration service provided by Microsoft Azure. It enables you to create, manage, and automate data workflows that move and transform data from different sources to various destinations. Essentially, ADF allows you to design, orchestrate, and manage data pipelines, making it easier to work with large volumes of data across on-premises and cloud environments.

kubectl logs: How to View & Tail Kubernetes Pod Logs

When debugging containerized applications in Kubernetes, kubectl logs serves as your primary command-line tool for accessing container logs directly. Understanding how to effectively retrieve, filter, and analyze logs becomes essential for maintaining application health and resolving issues quickly, especially in multi-container environments where correlation across services can make or break your troubleshooting efforts.

How to Reduce Errors and Improve Reliability in High-Traffic Node.js Applications with APM?

Node.js has become the go-to runtime for building modern, high-performance applications. Its event-driven, non-blocking I/O model makes it particularly well-suited for apps that demand speed and scalability, such as real-time chats, gaming backends, streaming platforms, fintech dashboards, and e-commerce systems. It’s no surprise that some of the world’s largest companies like Netflix, PayPal, LinkedIn, Walmart rely on Node.js to deliver services at scale.

A Practical Guide to Python Application Performance Monitoring (APM)

When your Python app starts slowing down, maybe queries are taking longer, memory keeps creeping up, or API calls are lagging—basic server metrics won’t tell you why. You need to see what’s happening inside the application itself. That’s the role of Application Performance Monitoring (APM). It gives you a breakdown of database queries, external API calls, memory usage, error rates, and more, so you can connect the dots between code and performance.

Data Sovereignty vs Data Residency vs Data Localization

Awareness of data sovereignty is increasing within organizations. Geo-political situations and recent news stories are causing many to formally evaluate their data management strategies and policies. This means that organizations are also looking at the tools and platforms they use to run and maintain key IT infrastructure and undertake tasks such as monitoring and management. SaaS and cloud first/only tooling can often present data sovereignty challenges and complications.

Reduce cloud waste with Datadog Cost Recommendations

Struggling to optimize your cloud spend across AWS, Azure, and Google Cloud? Datadog Cloud Cost Management highlights underutilized or legacy resources and lets engineers take immediate action using Datadog Workflows. Eliminate waste and drive savings with recommendations that your teams can trust.

Optimize Kubernetes and Container Costs with Datadog Cloud Cost Management

Struggling to understand the true cost of your Kubernetes workloads? With Datadog Cloud Cost Management, you can automatically allocate container costs by team, product, and service down to the pod. Instantly identify idle resources, surface optimization opportunities, and act with confidence. All in one unified platform.

How to surface misconfigured resources by defining policies | Datadog Tips & Tricks

Misconfigured infrastructure resources can be easy to miss, especially in multi-account or multi-cloud environments. From EKS clusters running on deprecated versions to RDS engines on extended support, these issues can disrupt services or drive up costs if left unchecked. In this video, we show you how to: By centralizing policies, you’ll gain a clear view of where to focus your remediation efforts.