Operations | Monitoring | ITSM | DevOps | Cloud

Logging and auditing activity across your AWS environment is a must for security, governance, and compliance. Yet, between management events, data events, and optional insights, it’s easy to overspend on tracking activity without realizing it. In this guide, we’ll break down CloudTrail pricing in plain terms and see what impacts your final bill. We’ll also share immediately actionable ways to keep your CloudTrail costs in check without sacrificing full observability.

Redgate Monitor has long helped data teams and DBAs keep track of SQL Agent Jobs. Now, with version 14.0.53, it extends that visibility to Azure Elastic Jobs, giving you a centralized view of all your scheduled tasks, whether they run on SQL Server, Azure SQL Managed Instances, or Azure SQL Databases.

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.

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.

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.

Modern systems throw off a lot of data—metrics, traces, logs—sometimes more than we know what to do with. When you're trying to understand how values spread out over time (like response times, memory usage, or queue lengths), averages alone don’t tell the full story. OpenTelemetry histograms help fill in those gaps. This guide walks through what they are, why they matter, and how DevOps engineers can use them to improve observability in real systems.

The 17th century saw the onset of the Scientific Revolution. It was a time of knowledge explosion. During this time, scientific practices were still evolving, with no universally accepted protocols for data collection and analysis. Individuals documented any observation, resulting in the collection of massive amounts of information, but much of it was hard to leverage to draw useful conclusions. The development of the scientific method provided a common approach to capturing and analyzing data.

One of my favourite authors, Douglas Adams, once said that “we are stuck with technology when what we really want is just stuff that works.” Whilst Adams is right about a lot of things, he got this one wrong – at least when it comes to infrastructure. As our Infra Masters 2025 event demonstrated, infrastructure is the technology that makes everything work – from managing a satellite in outer space, to, say, livestreaming an event.