Operations | Monitoring | ITSM | DevOps | Cloud

SolarWinds is a popular IT infrastructure monitoring tool deployed on-prem, most well-known for its network and server monitoring capabilities. While it offers rich telemetry, it’s easy to miss the bigger picture. SquaredUp turns this complex monitoring data into clear, shareable dashboards that make it easier to spot trends, catch issues early, and keep everyone on the same page.

Synthetic monitoring simulates user interactions with applications to proactively identify performance issues before they impact real users. Modern distributed systems require sophisticated monitoring capabilities to effectively test microservices, APIs, and complex user journeys across diverse environments. This article provides a framework to evaluate synthetic monitoring platforms in 2025.

Every interaction a customer has with a brand helps shape their loyalty and long-term relationship with it. As AI becomes an increasingly central part of customer experience (CX), businesses are arriving at a critical crossroads. When done right, AI has the power to deepen trust and build meaningful, lasting customer connections. But when it falls short, it can unravel hard-earned loyalty.

The landscape of IT Incident Management and Digital Operations is changing rapidly. Atlassian’s recent announcement that Opsgenie is being phased out in favor of Jira Service Management (JSM) signals a critical turning point for businesses that rely on robust, efficient incident management solutions. Organizations now face the imperative task of evaluating alternatives that offer the adaptability, automation, and intelligence necessary to maintain operational excellence.

Apache Flink is an open-source, distributed stream processing engine built for real-time, high-throughput data pipelines. It excels at processing continuous data streams with low latency, making it a great fit for use cases like fraud detection, log analytics, real-time dashboards, personalized recommendations, and IoT telemetry.

Monitoring deployed applications with eBPF is quickly becoming the standard for good reasons, eBPF: Revolutionizing Observability for DevOps and SRE Teams. Not in the least because it allows monitoring to be a purely operations affair, instead of having to instrument each and every application individually. The security-conscious SRE and SRE manager will immediately ask the question: is this secure? And how about this claim that HTTPS traffic can be monitored?

When was the last time you asked about the architecture behind your observability provider? For most IT professionals whether in development, operations, or security, it’s not a question that naturally comes up. Yet, this architectural detail could be the difference between insight at scale and runaway costs. People are drawn to the features, the shiny things. They promise to unlock insight, drive faster response times, and tighten security.

If you’re a technology reseller in today’s uncertain software virtualization market, you and your customers are probably actively exploring options for virtualized environments. Of course, finding the perfect alternative is easier said than done: it needs to be scalable, easy to migrate to, cost efficient, and provide the same technical capabilities as preexisting virtualization solutions. That’s a seemingly tall order – but luckily, there are a range of options.

You shipped your latest release. You tested it on emulators, QA devices, and the latest OS versions. But now it’s live and running on thousands or millions of mobile devices, across a jungle of screen sizes, hardware specs, OS versions, and network conditions. A user reports a crash on an old Samsung device over 3G. Someone else complains the app feels “sluggish” after updating. You dig through logs. Rebuild test cases. Ping the backend team. Try to reproduce. Yet, still no answers.

With advances in AI and heightened compliance requirements, the way we handle data is changing rapidly. This makes a robust database change management process crucial for organizations who still need to ship value to market, while getting the right data into the hands of decision-makers faster. It’s a tough set of demands for any organization to grapple with as they modernize their data for the future.