Operations | Monitoring | ITSM | DevOps | Cloud

At Almaden, our mission with Collective IQ (CIQ) has been about moving IT from a reactive “firefighting” mode to a proactive, data-driven approach that anticipates impacts to employee productivity. But to build an AI-powered platform that helps other companies work smarter, we have to work smarter ourselves. We also need to deliver responsible solutions which don’t compromise corporate privacy goals.

You can hit every DORA target and still be losing ground. Deploy frequency up, lead time down, change failure rate and MTTR both healthy, but underneath it could be hiding an organization slowly getting worse at turning work into reliable software. New services shipping without clear owners, an attack surface widening faster than anyone is tracking, on-call rotations quietly filling up, a migration that was supposed to close last quarter still limping along.

AI is pushing code volume up almost everywhere. Shipping it is still the hard part, and the gap between leaders and everyone else is getting wider. Today we’re releasing the 2026 State of Software Delivery Q2 Pulse report, a shorter check-in between our annual reports. We analyzed more than 20 million CircleCI workflows from March 2026 to see what’s changed since the comprehensive 2026 State of Software Delivery report we published in Q1.

CloudZero now breaks out Snowflake Cortex spend on its own, so the AI usage buried in your Snowflake bill becomes a line item you can track and allocate before it ramps into a surprise.

A deployment strategy is the method an engineering team uses to release new software to production. The six core deployment strategies are recreate (big bang), rolling update, blue-green, canary, A/B testing, and shadow deployment. Each trades off between downtime risk, rollback speed, infrastructure cost, and complexity. This guide covers all six along with what each strategy actually costs in cloud and AI infrastructure spend.

As.NET Multi-platform App UI (MAUI) becomes the default cross-platform UI framework in the Microsoft ecosystem, many teams are standardizing on it to build mobile applications for iOS and Android. However, observability has not kept pace with the shift in adoption. Developers often rely on unsupported community bindings or maintain their own wrappers around native iOS and Android SDKs, which introduces instability and ongoing maintenance.

I spend a good amount of my time deploying Aiven services for demos and examples. Traditionally the tools I reach for are: If I’m writing a program, I may also look to the Aiven API, perhaps using curl at the command line or in a shell script, or perhaps with direct HTTP requests in a Python program. The API is how the console and the CLI tool talk to Aiven, but I generally find that too low level to be comfortable, and I always have to look up how to pass in the Aiven user token.

How do you pick the right IT help desk software when every vendor calls itself the best? It comes down to three things. Your team size, your deployment rules, and whether you need full ITSM or plain ticketing. A five-person startup can run support from a shared inbox. A 200-person IT team cannot. Add asset tracking, SLAs, and change control, and that inbox falls apart. The right IT support software routes tickets on its own, links every request to the asset behind it, and shows you where time goes.

Standard BGP can be slow to react. See how BFD and BGP Add-Path help improve uptime and path diversity on MegaIX. When peering on a public Internet Exchange (IX), standard BGP behavior can introduce delays during topology changes. But if you use MegaIX, there are workarounds. In this blog, we explain two lesser-used features available on MegaIX which maximize uptime and path diversity: Bidirectional Forwarding Detection (BFD) and BGP Add-Path.