Operations | Monitoring | ITSM | DevOps | Cloud

Why does SOX season turn into a hunt for screenshots and forwarded approval emails? The controls were almost certainly running all year. The record of them running is scattered across a ticketing tool, an identity directory, a backup console, and someone's inbox. SOX compliance puts financial reporting under a legal standard, and the IT team ends up carrying a large share of the proof. Change approvals, user access lists, backup jobs, and batch schedules all become audit evidence.

Telemetry passes through several stages before anyone can use it. Searching it, charting it, and alerting on it all come later. Each stage makes one decision about the data. Their order separates a pipeline that saves money from one that adds a hop. Most teams meet this layer late, usually after a monitoring bill jumps. Here is how a telemetry pipeline works, stage by stage: By the end you can map your own telemetry flow against the five stages, and see which one is costing you.

Task containers are now generally available on Upsun Cloud, giving you a place to run AI agents alongside the rest of your application. The agent runs as a container inside your Upsun Cloud project, next to the app it works on, with the same access to your environment and data as everything else deployed there. The lifecycle is the part that's new: it fits how agent workloads behave instead of forcing them to pretend to be servers. A few things up front: This is a hands-on guide.

Session replay software lets you see exactly what your users saw without having to pull a Freaky Friday with your customer. The question is: which tool actually delivers on that for your team, your stack, and your regulatory environment?

What's in this article? For over a decade, the enterprise IT narrative was simple: move everything to the public cloud. Yet as enterprise architectures have matured, many UK technology leaders have discovered that hyperscale cloud environments do not always deliver the outcomes they expected. The promises of seamless scalability and lower total cost of ownership often come with trade-offs that become more apparent over time.

Every organization knows what their database monitoring tool costs on the invoice. Almost none of them have added up what it costs in the people running it, the incidents it doesn't catch fast enough, and the savings sitting in the environment that nobody has visibility to find.

GitHub Copilot Enterprise pricing is $39 per user per month, and since June 1, 2026, each seat includes $39 in monthly GitHub AI Credits, pooled across your whole organization and consumed by token usage at per-model rates. The seat price is fixed. The bill is not: usage beyond the pooled credits is charged on top, which is why the real Enterprise question in 2026 isn't the price per seat. It's your engineers' token consumption.

CUR 2.0 is generally available and on by default, so every AWS connection you make now starts with the richest billing data AWS offers. That richness is important. CUR 2.0 carries AWS caller identity, which is what puts Bedrock and other AI spend on the role that drove it instead of leaving it as one number in your bill. It also populates AWS Account Name automatically. Both of those are yours the moment the connection is live. Getting there is a single step now.

New pricing for Aiven for Apache Kafka is now live for all new customers on AWS, GCP and Azure. For our existing customers: nothing changes. When choosing your cluster you are guided by three things: And you pay for three things.

In conversations with customers, compliance rarely starts as a tooling discussion. It usually starts with a practical concern: how do we keep moving, keep modernizing, and still know that our infrastructure is aligned to the policies we are accountable for? That question comes up because the pressure is real. Teams are managing hybrid estates, responding to audit requests, dealing with drift, supporting new platforms, and being asked to move faster without creating more risk.