Operations | Monitoring | ITSM | DevOps | Cloud

 A major studio drops its new episode at midnight. Millions are queued to watch. Push notifications hit, the app surges in traffic, and then timeout. Spinning wheels. Frozen screens. Social media lights up. Customers don’t just notice they remember. For today’s communications, media, and information (CMI) brands, digital reliability is the product. Viewers, subscribers, and enterprise users aren’t comparing your uptime to industry benchmarks.

In recent months, there has been growing discussion among business and IT leaders around the rapid expansion of SaaS solutions. McKinsey’s recent report on the current state of SaaS notes that while the industry has experienced a slowdown, largely driven by economic factors such as rising interest rates and reduced IT spending by enterprises, it has seen a decade of rapid growth, with the market being valued at approximately $3 trillion in 2022.

Imagine if degrading network performance—not just bad code—disrupted your live stream during a high-profile event. Customers start flooding support lines. Social media lights up. Your NOC teams scramble to identify the root cause amid fragmented systems. The outage impacts not only your broadcast, but also subscriber logins, ad delivery, and mobile apps. Advertisers want refunds. Executives ask, “Why didn’t we see this coming?”

The aspirational target state for a cognitive system is to “take responsibility” for a domain (e.g., an autonomous car). To reach that level of sophistication, the system must achieve high levels of maturity simultaneously along two dimensions: Reasoning ability and Automation ability.

Previously, I discussed the challenges of adopting AI in enterprises, focusing on middle managers’ concerns about its impact on their roles. In case you missed it, you can read it here: AI resistance isn’t where you expect it In this post, I’ll highlight the crucial steps for ensuring successful AI adoption. All business transformations are complex by nature because they change the organizational balance – that is, the equilibrium of power held among different leaders.

In recent years, container platforms – also referred to as container orchestration systems – have grown in popularity and transformed the processes of software development, testing, and deployment.

Enterprise operations monitor various metrics associated with the stability, performance, availability, and other such aspects of business, application, and IT infrastructure. These could be business KPIs such as footfall, checkout time, and sales of the flagship stores. These could be performance metrics such as the response time of business-critical applications. These could be the queue length or enqueue rate of the backbone message queues.