Monitoring AWS billing costs with AWS tags
Today, I’ll be covering how AWS tags can help you keep track of and monitor your AWS billing costs with the granularity and depth needed to reduce and optimize your AWS costs.
Operations | Monitoring | ITSM | DevOps | Cloud
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The latest News and Information on Application Performance Monitoring and related technologies.
Comparing The Top 9 Datadog Alternatives and Competitors in 2025
The rising costs and complexities of monitoring cloud infrastructure are pushing many organizations to explore alternatives to Datadog. With monthly bills sometimes reaching thousands of dollars and feature sets that can be overwhelming, teams are looking for practical, cost-effective solutions that better fit their needs.
Application Performance Monitoring (APM) Use Cases Every DevOps Team Should Know
Modern applications are built using distributed architectures, microservices, and cloud-native technologies. As these systems grow in complexity, it becomes harder for DevOps teams to maintain performance, track issues, and ensure a consistent user experience across all environments. Application Performance Monitoring (APM) helps solve these challenges by providing real-time visibility into how applications behave, from user interactions to backend services and infrastructure.
APM best practices: Dos and don'ts guide for practitioners
Application performance management (APM) is the practice of regularly tracking, measuring, and analyzing the performance and availability of software applications. APM helps you get visibility into complex microservices environments, which can overwhelm site reliability engineering (SRE) teams. The generated insights create an optimal user experience and achieve desired business outcomes.
Choosing the Right APM Software: 5 Key Factors to Consider
When applications slow down, users leave, and engineering teams scramble. Whether you're troubleshooting a spike in response times or chasing down intermittent backend failures, Application Performance Monitoring (APM) provides the visibility you need to detect, diagnose, and resolve performance issues before they impact your users or business goals. For engineers, APM isn’t just a convenience - it’s essential. But not all APM tools are created equal.
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Introducing Raygun CLI: Level-up your error tracking workflow
Raygun CLI is a powerful command-line interface tool designed to enhance the developer experience when working with Raygun's error tracking and performance monitoring platform. With this tool, we bring Raygun's features directly to your terminal, making it easier to integrate some important elements of Raygun Crash Reporting and error tracking into your development and CI/CD workflow. We are excited to announce the release of version 1.0.0 of Raygun CLI.
The Complete Guide to APM Best Practices for Developers, DevOps & SREs
Application Performance Monitoring (APM) is no longer optional, it is essential for delivering fast, reliable, and seamless digital experiences. But simply installing an APM tool isn’t enough. To truly know its potential, IT teams need to follow APM best practices. Best practices for APM refer to the most effective ways to monitor, analyze, and optimize your application’s performance using APM tools.
MCP Observability with OpenTelemetry
2025 has truly been the year of Agentic AI, with MCP (Model Context Protocol) emerging as one of its flashy and most talked-about innovations. While many products have seamlessly integrated MCP servers into their systems, these servers are increasingly being labelled as black boxes, opaque components that handle critical tasks but offer little visibility into what's happening under the hood. We prompt an agent, a tool gets invoked, and a response is generated. But what really happens in between?
Instrument NextJS with OpenTelemetry in 100 seconds
What if setting up observability in your Next.js app was as easy as running a few commands? In this quick guide, we show you how to instrument your Next.js application using OpenTelemetry and visualize with SigNoz — without all the headaches.
Perform Distributed Tracing for your MCP system with OpenTelemetry
2025 has truly been the year of Agentic AI, with MCP (Model Context Protocol) emerging as one of its flashy and most talked-about innovations. While many products have seamlessly integrated MCP servers into their systems, these servers are increasingly being labelled as black boxes, opaque components that handle critical tasks but offer little visibility into what’s happening under the hood. We prompt an agent, a tool gets invoked, and a response is generated. But what really happens in between? And when something breaks, how do we trace the failure and debug it effectively?