Operations | Monitoring | ITSM | DevOps | Cloud

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.

Hariom Gupta Follow 4 min read· 1 hour ago -- Listen Share Starting this journey was both exciting and fulfilling — and now, here I am at the finish line, having successfully completed the LFX Mentorship Program and reflecting on the experience through this blog. The past three months have been incredible — surpassing my expectations in so many ways.

OpenTelemetry is rapidly becoming the backbone of modern observability, but true innovation happens when you build directly on its latest capabilities. For Launch Week 4.0, we’re excited to showcase five powerful features; each crafted to help you get more value from your telemetry, make debugging faster, and deliver a unified observability experience. Here’s a quick look at what’s new, why it matters, and how SigNoz is pushing the boundaries of what’s possible with OTel.

The Grafanaverse just got a little bit bigger. Today at its annual Build conference, Microsoft introduced Azure Monitor dashboards with Grafana, a new service that provides Azure users with Grafana dashboards natively integrated in the Azure Portal at no additional cost and with little administrative overhead required.

Amazon Web Services (AWS) powers everything from scrappy startups to Fortune 500 giants. So, AWS interview questions are relevant for all kinds of roles, from infrastructure design to cost governance. Now, while some interviews test definitions and acronyms, the best ones dig deeper. They explore how well you understand AWS trade-offs—think of performance vs. cost, scalability vs. complexity, or security vs. usability.