Operations | Monitoring | ITSM | DevOps | Cloud

Microsoft Windows Internet Information Services (IIS) log files hold a wealth of data on web application activity and performance. But, locating and managing these logs can be challenging for busy sites with constant traffic and complex infrastructures. IT operations teams rely on IIS logs to troubleshoot web applications, track server requests, identify users, and address other user traffic concerns for optimal security.

Docker containers continuously generate logs during operation, and without proper management, these logs can consume significant disk space, impact system performance, and create operational issues. Logrotate offers an effective solution for managing these logs in containerized environments. This guide covers the implementation of logrotate in Docker containers – from initial setup through advanced configurations that ensure stable, maintainable container deployments.

Instead of deploying a patchwork of proprietary agents for every platform, a telemetry pipeline lets you route your data through a single, consistent layer—and send it to any backend you choose. Flexibility, achieved. But there’s a catch. If your pipeline is proprietary, you’ve only shifted the lock-in left. Sure, you can now add or swap destinations freely—but you’re still deeply dependent on a vendor in the middle of your data flow.

Can you ever get too much data? With modern architectures getting increasingly more complex with hundreds of microservices and containers, data volume grows at an exponential rate, and there’s no pause in sight. In this era of ever-expanding volume of telemetry, it’s nearly impossible to separate valuable data from noise, making things like root cause analysis or alerting needlessly more complicated, while putting pressure on the performance of your stack, your scalability and budget.

Cloudflare is a content delivery network (CDN) that helps businesses accelerate, protect, and optimize their websites, applications, and APIs. It acts as a reverse proxy, sitting between users and a website’s origin server to provide DDoS protection, web application firewall (WAF), CDN caching, and load balancing.

There’s nothing like debugging a broken system at 2 AM, running on caffeine and frustration. When everything’s on fire, logs are your lifeline. That’s where trace-level logging comes in. Unlike standard logs, it captures the step-by-step execution of your code—think of it as the difference between a crime report and full CCTV footage. But more logs don’t always mean better debugging. Too much detail, and you’re drowning; too little, and you’re guessing.

Understanding Sumo Logic pricing can be challenging, with complex tiers and varying costs. This guide provides a clear, straightforward breakdown to help you navigate Sumo Logic’s pricing structure effectively.

Everyone has a story about that one road trip where traffic got backed up, making people late to the event. When you have network connectivity problems, your information highway gets clogged up, making it difficult for users to access resources efficiently. While network troubleshooting strategies may seem simple, a lot of nuance and complexity lies in the activities when you dig into your data.

You've deployed a new feature into production. You've done your unit testing, fixed lots of bugs, your code is awesome. Now it's time for hundreds/thousands/millions of users to break...err...use your feature. You're diligent about tracking usage in real-time, and getting customer feedback when something goes wrong. You track the performance and response time impacts on the server. All is good...except...that feature isn't quite working for a specific group of users. Now what?