Operations | Monitoring | ITSM | DevOps | Cloud

As the travel and hospitality landscape continues to evolve, Artificial Intelligence (AI) and Autonomous IT have become indispensable for staying competitive. These technologies are fundamentally transforming how enterprises deliver seamless guest experiences while ensuring resilient, efficient operations.

Discover the ITSM metrics that matter most—and how focused, action-oriented reporting can turn service data into better decisions. Effective IT service management depends on visibility, and visibility depends on measurement. Reliable reporting gives IT teams a factual basis for decisions and replaces assumptions with evidence.

Conversational AI has arrived in Alloy Software documentation, making it easier to find the exact answers you need. Ask a question, follow up naturally, and refine the response until you reach the right instructions or product details, without starting over or digging through pages. The redesigned experience keeps the conversation in context and lets you go as deep as you need.

Enterprise IT has reached an inflection point. Your teams are responsible for hybrid cloud infrastructure, microservices, third-party dependencies, and shipping AI-generated code at unprecedented velocity. IT environments are becoming more complex faster than traditional tools and processes can keep pace. Alert volumes keep climbing. Institutional knowledge keeps walking out the door. And the pressure to do more with flat or shrinking budgets isn’t letting up.

“AI-powered” has become a marketing label applied to almost any data center software feature. A more useful and precise term is actionable intelligence — a four-level maturity model (descriptive, diagnostic, predictive/prescriptive, and cognitive) that shows whether a platform’s AI claims are backed by real data infrastructure or just a chatbot layered on top of an incomplete system.

A WooCommerce checkout monitor should verify that a shopper can open a product, add it to the cart, reach checkout, enter valid details, and see a usable payment option. Playwright is a good fit because these failures often happen after the server has already returned a successful HTTP response. WooCommerce itself uses Playwright for its end-to-end tests. A scheduled production check uses the same browser behavior for a different purpose: finding a broken customer journey between deployments.

A Magento checkout monitor should prove that a customer can select a product, create a cart, reach checkout, enter a shipping address, and load the expected delivery and payment methods. Playwright can test the rendered storefront while also checking the GraphQL or REST requests behind it. Adobe Commerce and Magento Open Source provide several testing tools, including a Functional Testing Framework and web API tests.

How to find, search and retain the SharePoint audit log in Microsoft 365 - the Purview audit search, Search-UnifiedAuditLog PowerShell, retention limits, and where the native audit trail falls short.

This post is a joint effort by the OpenLIT and VictoriaMetrics teams. OpenLIT brings the OTel-native GPU collector for NVIDIA, AMD, and Intel hardware, while VictoriaMetrics provides the storage and query layer for the resulting metrics. We wrote it together to show how the two projects fit into a single, self-hosted observability pipeline, and to share the queries and rules that worked well for us along the way.

Decisions in each SDLC phase from planning to design, development, testing, deployment, and maintenance are made without sight of live production behavior. AI coding agents are widening that visibility gap faster, working faster than human engineers ever could. This piece maps exactly how this gap presents at each phase, and the harm that this brings.