Operations | Monitoring | ITSM | DevOps | Cloud

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.

Full-Circle Observability: Using SigNoz to monitor a LangChain agent that queries SigNoz MCP

In Part 1 of this series, we explored how to instrument a LangChain trip planner agent with OpenTelemetry and send telemetry data to SigNoz. By tracing each step of the planning process: LLM reasoning, tool calls for flights, hotels, weather, and activities, and the final itinerary response, we saw how observability turns a black-box agent workflow into a transparent, debuggable system.

LangChain Observability: How to Monitor LLM Apps with OpenTelemetry (With Demo App)

LangChain has become one of the most popular frameworks for building LLM-powered applications, making it easier to create agents that can reason, plan, and take actions. But like any production-grade AI app, LangChain agents can run into performance bottlenecks, hallucinations, or tool call failures. And without proper LangChain observability, it’s hard to know where things break down.

Put Cloud Costs in Front of Engineers with Datadog Cloud Cost Management

Tired of surprises on your cloud bills? With Datadog Cloud Cost Management integrated into the Software Catalog, engineers see cost, performance, and reliability side by side—no context switching required. Give every service owner the visibility they need to make cost-aware decisions.

Track Cloud Unit Economics with Datadog Cloud Cost Management

Do you know the true cost per user, API call, or checkout? Datadog Cloud Cost Management lets you break down spend by combining cost, observability, and custom business metrics—all in one place. Track cost per transaction, alert on changes, and align engineering and finance with real-time unit economics.

APM Logs: How to Get Started for Faster Debugging

When application performance monitoring detects a spike in latency or error rates, the immediate challenge is determining the underlying cause. APM logs address this by correlating performance metrics with the specific log events that occurred at the same time. Instead of switching between monitoring dashboards and manually searching through log files, APM log correlation consolidates both views.

Proactive Observability - Predictive Analytics Models and Algorithms for IT Systems and Metrics

Predictive Analytics Models and Algorithms are an important component of eG Enterprise’s AIOps engine for proactive observability. eG Enterprise collects and analyses metrics, events, logs and traces and the data including real usage data is used to make intelligent predictions to forecast future system behavior and IT resource metric levels.

How our engineers use AI for coding (and where they refuse to)

Okay, picture this: if you drew a Venn diagram of folks in tech right now, it'd probably look something like this: You'll probably find yourself in one of those circles, right? I’m guilty of falling in the intersection! Because let's be real, the 'will AI replace developers by 20xx?' debate is everywhere – Reddit, Hacker News, team Slack and even your local cafe. Well, we decided to go straight to the source.

A Practical Guide for Developers: Preventing PHP Mistakes with Performance Monitoring

Performance is one of the most critical aspects of any PHP application. A few seconds of delay or an unnoticed bottleneck can cause users to leave your site, increase bounce rates, and reduce business conversions. For developers, ensuring top performance is not always easy. Small coding mistakes, inefficient queries can accumulate into major problems over time. Without visibility into what’s happening inside the application, it becomes difficult to identify the root cause of slowdowns or failures.

PHP Performance Monitoring with Atatus PHP APM

PHP is used by millions of websites and applications around the world because it’s easy to work with and very flexible. But like any technology, PHP apps can run into problems like slow performance or errors that affect users and your business. Atatus PHP APM provides developers, DevOps engineers, and SREs with clear insights into what is happening inside PHP applications, helping them find and fix issues faster, improve performance, and keep things running smoothly.

Top 7 Application Performance Monitoring Tools

Your application is under constant pressure to deliver low latency, high reliability, and a smooth user experience isn’t optional. When performance drops, every second matters. Application Performance Monitoring (APM) gives you the visibility to spot issues before your users feel the impact. It also helps you understand what’s happening inside your stack, so you can track resource usage, pinpoint bottlenecks, and keep things running at peak performance.

What is PHP memory leaks? How can you detect and resolve with APM?

According to the 2025 PHP Trends Report, 31% of developers cited performance bottlenecks as a recurring issue and PHP memory leaks were among the top culprits identified by DevOps teams working with high-traffic applications. Imagine you're shipping an app that’s humming along smoothly during QA. But weeks after going live, you start noticing creeping latency and irregular job failures. You dig into the logs, tweak some queries, but the issue persists.

What Makes PHP Application Monitoring Tools Essential for Leading Industries?

PHP is one of the most widely used scripting languages for web development. From e-commerce platforms to government portals, PHP powers a large share of the web. However, as web applications grow in complexity, user expectations also rise. Slow page loads, broken features, or unresponsive sites can lead to lost revenue, lower engagement, and frustrated users.

Observing LlamaIndex Apps with OpenTelemetry + SigNoz

LlamaIndex has become a popular choice for building Retrieval-Augmented Generation (RAG) applications, helping developers seamlessly connect large language models with private or domain-specific data. But RAG workflows can be complex with slow retrieval times, irrelevant or inconsistent responses, and silent failures in the data pipeline can all degrade the user experience. That’s why observability is essential.
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AI realism (part one)

Emotions are running high about AI technologies. In this 2-parter, I do my best to make a rational case on the reality of AI, and how we can respond to it. This is part one; part two next week. We seem to be struggling to have pragmatic discussions about advancements in Artificial Intelligence. It's hard to hear calmer voices over the detractors and breathless enthusiasts. Today, I want to make a reasoned, evidence-based case for the potential of this technology, glance at present and future applications, and offer some practical examples for implementing AI within an organization.

New Feature - Vulnerable System Drivers Monitoring

Vulnerable system drivers continue to be a vector exploited by attackers to compromise systems. In eG Enterprise version 7.5 we added a number of periodic security checks to assist administrators proactively identify weaknesses, including vulnerable system drivers monitoring.This new capability is supported for a Windows OS, when using a VM agent for inside view monitoring and / or when monitoring an Azure Virtual Desktop session host.

The Platform Engineer's Playbook: Mastering OpenTelemetry & Compliance with Mezmo and Dynatrace

The rise of platform engineering has put a new team at the center of the developer experience. These teams are tasked with building the "paved road" for developers, which includes providing a robust, self-service observability stack. However, they face a dual mandate: provide a great developer experience and manage the ever-growing costs and complexity of the tools involved.

How We Think About "Developer Marketing" at SigNoz

“Developers hate marketing.” Do they, really? I often hear this thrown around on podcasts about DevTools marketing, and while it’s true that developers don’t respond to the same old marketing tactics, they do respond to genuine communication. The reason developers are hard to “market” to is that they are also the builders of the stuff you want to sell.