Operations | Monitoring | ITSM | DevOps | Cloud

For the last two years, enterprise AI strategy has largely focused on one thing: adoption. Organizations encouraged employees to experiment with ChatGPT, Claude, Copilot, Gemini, and dozens of emerging AI tools in the hope that productivity gains would naturally follow. CIOs approved pilots, departments launched AI task forces, and leaders pushed teams to integrate AI into everyday work as quickly as possible. But the enterprise AI conversation is beginning to change.

The Agile software development lifecycle was designed to surface problems early, with short sprints, iterative testing, and continuous integration built on the premise that faster feedback loops produce better software. AI coding tools have changed the velocity equation across every phase of that loop, but the phases designed to catch failures are struggling to keep up because build speed and validation capacity have not accelerated at the same rate, and the gap between them is widening with every sprint.

ServiceNow is a powerful, highly customizable platform built for the complex operations of mid-sized and large enterprises. Its strength is flexibility, with modules spanning IT service management (ITSM), IT operations management (ITOM), HR service delivery, customer service management, and security operations. That modular structure is also why ServiceNow pricing is not sold as a standard price list.

Long-lookback alert policies for PromQL cover up to two years of metrics in Cloud Monitoring for year-over-year and quarter-over-quarter analysis.

Most network monitoring tools alert you that a device is down. The best ones help you determine whether the problem is your WAN circuit, your ISP, or your SaaS provider before your users file a ticket. Traditional network monitoring tools were built for static networks. You poll devices, check interface counters, and still can’t explain why users are complaining about latency.

Polling has been the go-to approach for network monitoring for years, and it still plays an important role in keeping networks healthy. But as networks become more distributed, application-driven, and data-intensive, simply polling devices more often isn't always the most efficient way to gain deeper operational insights. That's where network telemetry comes in.