Operations | Monitoring | ITSM | DevOps | Cloud

Spring Boot version upgrades—whether moving from 2.x to 3.x, 3.x to 4.x, or even minor bumps like 3.2.5 to 3.3.1—regularly introduce subtle, breaking changes that unit and integration tests miss. JSON serialization shifts, autoconfiguration reordering, and transitive dependency conflicts can silently alter your API contract.

Sovereign cloud conversations usually center on where customer data sits at rest. The provider points at a UK data center, the contract gets signed, and procurement marks the box. For most workloads, that's a defensible position. For GPU workloads, it isn't.

Microsoft 365 Backup, M365 Archive, Purview retention, EOA, and inactive mailbox - what each one actually does, and where third-party archivers fit.

Training a model is a project with an end date. Inference is what happens for the rest of the model's working life. The two workloads share GPUs, frameworks, and a lot of vocabulary, but the infrastructure decisions that make sense during training are usually the wrong ones in production. Teams that treat inference as "training, but smaller" tend to discover the gap somewhere around their first traffic spike.

Audit OneDrive and SharePoint Online sites over their licensed storage quota with PowerShell - useful for MC1310684 remediation and routine storage management.

Discover the Megaport MCP Server and how it enables AI-powered, agentic networking through natural language access to network infrastructure. By Miwa Fujii, Community Manager - Terraform and Ryan Tucker, Solutions Architect In the cloud networking era, we’ve moved from manual configurations in the Portal to Infrastructure as Code (IaC), Terraform. But the next frontier isn’t just code, it’s intelligence. We are pleased to announce the release of the Megaport MCP Server (Open Beta).

Tokens per watt (TpW) – the measure of useful AI work produced per watt of energy consumed – is the metric at top of mind for CEOs, heads of AI, and infrastructure teams alike. With the tremendous cost of GPU clusters, extracting as much value as possible from the expense is critical. But in the pursuit of tokens, it’s important to remember that hardware efficiency isn’t the only factor influencing data center operating costs, or the output of useful, revenue-generating AI work.