Operations | Monitoring | ITSM | DevOps | Cloud

Your Node.js app runs fine on your machine. But inside Docker? You start getting weird crashes—ENOSPC: no space left on device. Chrome headless tests fail out of nowhere. PostgreSQL throws shared memory errors under load. The problem? It’s probably /dev/shm, the shared memory volume Docker sets up by default. Most containers get just 64MB of space here.

A Shopware store goes from smooth to sluggish—pages take 10 seconds to load, even longer in some cases. What happened? In this post, we tell the true story of how one overlooked plugin setting nearly collapsed a storefront, and how it was resolved using native tools. If you’re shipping code in Shopware without clear performance observability, this is your wake-up call. Everything was working, until it wasn’t.

For many enterprises, Drupal has been the backbone of their web operations for years. It’s a battle-tested CMS that handles complex content needs with elegance. But business needs have evolved. Today, it’s rare for a company to rely only on Drupal. They are spinning up Python APIs, .NET backend services, Node.js apps, Java microservices — expanding their digital ecosystems around Drupal’s core.

Swift is the default and preferred language for developing applications within the Apple ecosystem. The Swift Package Manager (SwiftPM) has become the de-facto dependency manager for Swift, enabling developers to share and reuse code effortlessly. While its elegance lies in its simplicity, there’s a common concern about integrating SwiftPM into robust, enterprise-grade development workflows. This is where JFrog Artifactory shines.

We consistently roll out helpful updates and fun features in Grafana Cloud, our fully managed observability platform powered by the open source Grafana LGTM Stack ( Loki for logs, Grafana for visualization, Tempo for traces, and Mimir for metrics). In case you missed them, here’s our monthly round-up of the latest and greatest Grafana Cloud updates.

AWS Step Functions offers the Distributed Map state, enabling you to coordinate massively parallel workloads within your serverless applications. With this feature, a single Step Functions execution can fan out into up to 10,000 parallel workflows simultaneously, making it possible to efficiently process millions of items in parallel. This capability unlocks new possibilities for large-scale data processing, such as image transformation, log ingestion, or batch analytics.

You deploy a fix late Friday and spend the weekend refreshing dashboards, hoping nothing breaks. You shouldn’t have to babysit a dashboard to know when something’s wrong. With the latest updates to Insights, you can now create alerts directly from any chart. Whether it’s a spike in 4xx errors after a deploy, a jump in P95 latency for an API endpoint, or a drop in throughput for a background job, you can set up alerts with just two clicks.

If your legal department is anything like ours, you’re being inundated with requests from the business to use more and more AI tools. Whether it's developers wanting to use coding agents like Cursor, to security implementing AI-driven investigations, to sales and marketing leveraging AI for call insights and competitive research, we've seen a shift in what teams are trying and buying.

You can write clean code, test obsessively, and deploy with crossed fingers…but errors always find a way. And if you’re not tracking them? You’re gonna get bugged. Whether it’s a silent failure or a full-blown crash, every unreported issue is a hit to your app’s reputation.

The complexity of modern enterprises has pushed IT operations to the limit. Hybrid cloud environments, CI/CD pipelines, microservices, and agile methodologies revolutionized IT, but caused an explosion of scale and data fragmentation. This complexity simply cannot be managed by legacy tools or manual ITSM processes designed for monolithic systems and static infrastructures.