Operations | Monitoring | ITSM | DevOps | Cloud

Here’s your go-to kubectl commands cheat sheet! Jump into Kubernetes management with these handy commands and make your life easier.

A common pattern when building Grafana dashboards is to represent data for many items at once, such as simultaneously monitoring hundreds of servers. But what if there’s a problem with one of those servers? You’d want the ability to quickly identify that single server, and drill into the details without noise from all the other systems. In Grafana, dashboard variables are a great way to filter data and focus on the information that’s most important to you.

Keeping Kafka running at peak efficiency takes more than just a smooth setup. Fine-tuning Kafka producers and consumers is key to making sure every message is processed quickly and accurately. A little tweaking here and there can help you avoid bottlenecks, increase throughput, and keep your whole data pipeline running smoothly. In this guide, we’ll dive into practical tips for configuring producers and consumers for maximum efficiency.

A friend of mine once had an annual appraisal where his manager blithely declared to him that his target for the next year was "to exceed his targets". Rather than spend the next year screaming silently whilst trapped inside an MC Esher-esque cycle of infinite recursion, my friend politely demurred and requested a more achievable goal, such as building a time machine out of jellybeans.

In the first part of this series, we explored how AppSignal can significantly enhance the robustness of Open edX platforms. We saw the challenges that Open edX faces as it scales and how AppSignal's features — including real-time performance monitoring and automated error tracking — provide essential tools for DevOps teams. Our walkthrough covered the initial setup and integration of AppSignal with Open edX, highlighting the immediate benefits of this powerful observability framework.

In Rails, we're more likely to use SQL databases than other frameworks. Unlike NoSQL databases, which can be scaled horizontally with relative ease, SQL databases like PostgreSQL or MySQL are much less amenable to easy scaling. As a result, our database usually becomes the primary bottleneck as our business grows. Although SQL databases are very efficient, as our growing customer base puts an increasing load on our servers, we begin scaling our instance counts, workers, etc.

As the world moves towards sustainability, IT operations and digital workspaces are becoming critical in achieving corporate sustainability goals. The digital transformation of businesses—especially in light of hybrid and remote working models—has increased the demand for IT infrastructure, which in turn raises concerns about energy consumption, carbon emissions, and environmental impact.

Modern observability platforms are transforming how organizations handle application performance monitoring and troubleshooting.

‍ While Scout provides powerful monitoring tools (try it now!) mastering logging is an awesome complement to these skills. In this post, we’ll see how to create readable, actionable logs for both humans and machines. You’ll improve your logging strategy, drastically reduce troubleshooting time, and put yourself in the best possible position for maximum observability. As a starting example, let’s take this error log.