Operations | Monitoring | ITSM | DevOps | Cloud

You’re staring at logs, trying to figure out what caused that odd error in the middle of the night. Or maybe you're following a chain of requests across services, hoping to understand how one user action triggered a series of unexpected behaviors. That’s where distributed tracing and request tracking—specifically, correlation IDs and trace IDs—are invaluable. It’s the kind of detail that can make debugging faster and less painful.

As much as you try to prevent it, your product will break sometimes. While you hope it would have the decency to do so while you are awake and already working, sometimes the product is inconsiderate and decides to break outside your office hours. Being woken up from a page at 3 am sucks, and being woken up again two hours later (when you get pinged for a follow-up issue you missed the first time) sucks even more.

Every business strives to optimize operational costs and efficiency. In the DevOps world, where cloud-scale operations are the norm, this becomes even more critical. At JFrog, while delivering a robust and highly scalable SaaS solution to our customers, we are equally focused on optimizing operational costs and maximizing infrastructure efficiency.

In the race to ship software faster, many teams have turned to automation, decentralised tools, and powerful pipelines. But lurking under the surface of these streamlined processes is a growing and often invisible Identity and Access Management (IAM) threat vector. — a core vulnerability in modern CI/CD security.

AI is no longer just a buzzword. According to a 2024 McKinsey survey, 72% of companies now use AI in at least one area of their business. By 2027, nearly all executives expect their organizations to use generative AI for both internal and external purposes. However, with this rapid adoption comes significant security risks. As organizations rush to implement AI solutions, many overlook a critical vulnerability: prompt security.

Modern systems throw off logs like confetti—and making sense of all that noise is half the battle. OpenTelemetry logging offers a way to bring some order to the chaos. It helps DevOps teams collect logs in a consistent format, no matter what language or framework they’re working with. In this guide, we’ll walk through what OpenTelemetry logging is, why it matters, and how to put it to work in your stack.

Modern applications rely on numerous interconnected endpoints to function properly. Maintaining visibility into these critical connection points is fundamental to both system reliability and security. When endpoints fail, degrade, or become compromised, the impact cascades to users, teams, and ultimately affects your bottom line. Effective endpoint monitoring provides the visibility needed to prevent these issues.

Internal developer portals (IDPs) have become essential tools in platform engineering, helping standardize developer workflows and reduce friction by providing self-service access to tools, APIs, and infrastructure. During my time on a platform team, I experienced firsthand the transformative power of IDPs. Our team implemented custom solutions that significantly reduced load on developers, allowing them to focus on writing code rather than navigating complex infrastructure.