There have been significant improvements in Tracealyzer over the last years. If you haven’t tried it in a while—or if you’re just getting started—here are some tips and tricks that can be handy when analyzing your FreeRTOS applications. As you may know, the TraceRecorder library automatically records task scheduling and FreeRTOS API calls using the standard trace hooks in the FreeRTOS kernel.

SLA vs SLO vs SLI, what’s the difference anyway? Workplace success relies on clear expectations to help leaders and employees thrive together. As such, the partnership between customer and provider requires the same clarity to maintain service satisfaction. This is why Service Level Agreements (SLAs), Service Level Objectives (SLOs), and Service Level Indicators (SLIs) exist in the first place.

Microsoft Teams is deeply embedded in many organizations’ workflows, acting as a hub to both communicate and collect information about issues and ongoing projects. However, as with most communication platforms, it can be challenging to context-switch between conversations, tickets, and monitoring data when troubleshooting collaboratively.

To ensure that your organization’s cloud spend is efficient, you need detailed and granular visibility to understand what comprises your costs, what causes them to change, and how the cloud services and resources you use are enabling your business goals. Extending your visibility and more closely monitoring your cloud costs can position you to successfully adopt FinOps, which provides a framework that can help you maximize the value you get from your cloud spend.

It’s a story many network administrators dread: leaving the office on a Friday afternoon with everything running smoothly, only to return Monday morning to a nightmare of system-wide failure. If you’re a network administrator, you know the quiet comfort in logging off on Friday, satisfied that all servers are operational, backups are complete and the network is running efficiently. It’s the moment when you finally let out a sigh of relief, looking forward to a stress-free weekend.

For today’s network operations teams, change is a constant. Applications, app delivery chains, software-defined and physical infrastructures, cloud services, and more are in continuous flux. Further, as organizations continue to pursue ever more strategic digital transformation efforts, the pace of this change only accelerates. These days, about the only constant is the demand being placed on network operations teams.

Outages are unexpected events that can suddenly stop an organization's operations. Whether it's a network issue, a key application going down, or a system crash, these problems can cause confusion and disrupt work. Teams scramble to identify the problem, while employees are left in the dark, uncertain about the impact or duration of the issue. A lack of real-time communication can lead to frustrated employees, delayed responses, and prolonged recovery times.

In the first post, we introduced system tables and how to use them to inspect your cluster. In this follow up, we’ll explain some techniques to improve the speed of system table queries.

Keeping a Kafka cluster optimized can feel like a balancing act. Every piece—brokers, partitions, producers, and consumers—has to work in harmony, or you’ll start running into bottlenecks. To get Kafka to run smoothly and handle growing traffic loads, balancing load across the system is key. Let’s go over practical load-balancing techniques that can improve Kafka performance, keep everything running efficiently, and prevent data slowdowns from building up.

You’ve found some Long Animation Frames (LoAFs) impacting your site, now you need to fix them! LoAFs can make animations feel sluggish, delay user interactions, and generally reduce your site’s responsiveness, all of which contribute to a frustrating experience for users. Fortunately, by analyzing LoAF data and addressing common performance bottlenecks, you can dramatically improve how smoothly your site runs.