Operations | Monitoring | ITSM | DevOps | Cloud

The 14 Cloud Security Principles from the UK's National Cyber Security Centre form the primary framework for UK public sector cloud procurement and, increasingly, for private sector regulated workloads. Any credible cloud security case in the UK context has to address these principles explicitly. For organizations placing workloads on sovereign cloud specifically, the mapping matters more than for general cloud procurement.

We are thrilled to announce an update to our Excel Add-ins, bringing expanded support for popular cloud services and databases. The release introduces new objects, fields, API capabilities, and authentication options for BigCommerce, FreshBooks, HubSpot, NetSuite, QuickBooks Online, Zoho CRM, Oracle, MySQL, and PostgreSQL.

Back when I was a network administrator, one of the most frustrating phrases I would hear was: “The application is slow.” Today, after years of working with customers, not much has changed. The technologies are different, the networks are faster, and the applications are increasingly distributed across data centers, cloud platforms, and SaaS providers, but the troubleshooting challenge is often the same. Users know something is slow. Application teams believe the servers are healthy.

Most companies buy AI tools for developers and hope the impact shows up somewhere. A faster sprint. Fewer escaped bugs. Something. What they don’t have is a way to actually see it happening, which means adoption becomes a leap of faith instead of a measured bet. That’s the gap Kepler and GitKraken Insights close together, and it’s worth understanding as one story, not two separate product updates.

AI is expensive because the model bill is only part of the cost. Three components set the floor: model subscriptions, per-token API pricing, and infrastructure. Three more make it move: adapting models to your business, catching and fixing errors, and rising energy and datacenter costs. Efficiency doesn't fix it, because cheaper AI gets used more, not less. Businesses are willing to spend on AI. Research from Deloitte found that in 2025, 85% of organizations increased their AI investments.

People run Codex on their own laptops. When Codex is signed in with a ChatGPT subscription, OpenAI’s own admin console shows who used it and how much: messages and credits. What it doesn’t show is what any of that usage was for, or how it compares to what your team spent on other AI tools. The CloudZero desktop agent for macOS installs on a Mac, sees the traffic from AI coding tools, and prices what those tools use.

Budget season is starting and most finance teams are finding the AI line is the most evasive line on the page. You lived through the year. AI spend came in higher than planned and moved in ways nobody could foresee or forecast. And when the board asked what it produced, the honest answer probably was “we’re working on it.”

TLDR: When you work in Harness AI Chat, your work doesn't stop at Harness. Your pipelines live here, but the change you actually need to make might be a YAML file in GitHub, a Jira ticket, or a Confluence doc. So we built an MCP Gateway inside Harness that lets AI Chat reach those third-party apps for you: safely, under Harness's own access controls and secrets, and without dropped sessions across our distributed fleet. This is the story of what we built and why.