Operations | Monitoring | ITSM | DevOps | Cloud

The world is changing every day. From geopolitical shifts to legislation like GDPR which requires localized processing – these all create a complex and uncertain landscape where data storage, processing, and cloud services could potentially come to a sudden halt or suffer heavy disruption overnight. As a result, organizations are increasingly interested in potential routes for shifting cloud services to safer alternatives closer to their country of operation.

We work in a digital landscape where IT teams are expected to move faster, scale smarter, and deliver flawless digital experiences, automation is no longer optional; it’s foundational. But while most organizations have started down the automation path, far fewer can answer the critical question: How do we measure success? The problem isn’t just a lack of metrics. It’s that the wrong metrics are still steering the ship.

As organizations move beyond traditional hypervisors, Harvester continues to lead the way as an open source, Kubernetes-native virtualization solution. With the release of Harvester 1.5, users now have greater flexibility and ecosystem alignment than ever before—with General Availability (GA) for ARM64 and support for CSI-compatible storage backends. Harvester is part of a growing shift toward cloud-native infrastructure that unifies VMs and containers under the Kubernetes API.

IT Ops Problem Solver Series – Part 2: This article is a summary of a full report in our IT Ops Problem Solver Series. In this series, we’ll tackle the biggest problems facing IT Ops leaders and explore how some of Galileo’s clients are addressing them. In this part of the series, we delve into IT performance challenges and how to address them effectively.

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.

Effective microservices logging requires standardized formats, centralized storage, correlation IDs, and strong security measures. This guide walks you through setup strategies, best practices, and tool recommendations that won't break your budget.

Effective Node.js monitoring requires tracking runtime metrics (memory, CPU), application metrics (request rates, response times), and business metrics (user actions, conversion rates). This guide covers what to track, how to collect it, and how to set up meaningful alerts.

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.