Operations | Monitoring | ITSM | DevOps | Cloud

Across the IT industry, AI is being positioned as the next evolution of operations. But for many IT teams, AI still feels disconnected from the tools they rely on every day. Dashboards get smarter. Reports get faster. But workflows stay the same. Stuck in vendor silos or a CLI, IT teams have been looking for ways to bolt AI into workflows, but what often comes out is a Frankenstein-like web of APIs and MCP hosts. AI is meant to make life easier for IT teams – not make it more difficult.

Distributed enterprise applications eventually need to exchange messages across network boundaries - between datacenters, between application tiers, between geographic regions. A single broker cannot serve all of them efficiently.

Kotak811, the digital-first engine of Kotak Mahindra Bank, is a banking platform serving over 23 million users across India. Since its launch in 2017, Kotak811 has transformed into the bank’s primary growth driver, now accounting for 70% of all new customer acquisitions. The platform is widely recognized for offering a paperless, mobile-first experience, providing everything from instant zero-balance accounts to seamless UPI payments and investment tools.

Cloud native cost optimization requires rethinking how you track containers, serverless, and microservices spend. Here's a framework for 2026.

Digital services are the engine of your modern business, but keeping them running feels like a constant battle. The rapid increase in the volume and speed of operational data is a direct result of growing architectures and more intricate workloads. Alert fatigue is causing your teams to be slow and reactive in addressing incidents, and this is a surefire path to burnout. The pace of this new reality is beyond what traditional, human-led processes can match.

It’s 2 a.m. An alert fires. You acknowledge it, pull up the monitoring dashboard, and immediately hit a wall: Which team owns this? What services does it impact? Worse: this is the third time this month you’ve been paged for the same issue, and you still don’t have a clear path to fix it. What should take minutes stretches into hours of Slack threads, escalation guesswork, and frantic context gathering.

At the 2026 India AI Impact Summit in February 2026, 92 countries and international organizations (including the US, China, and the UK) signed a preliminary agreement that positions AI as both a development tool and a shared global responsibility. “India will not be a mere consumer in the AI age. We will be the creators, the builders, and the exporters of intelligence and we are proud to be able to participate in that future.” Gautam Adani, chairman of the Adani Group.

Monitoring tools track what’s happening across your systems and send a Slack message or email when something looks off. But they don’t call anyone and they don’t escalate the incident. If that Slack message goes unseen at 3 AM on a Saturday, the incident just sits there until someone opens their dashboard. Incident alerting fills this gap. When an incident triggers, it contacts the right person directly through a phone call or their preferred channel.

Years back I sat in on a platform evaluation with a customer who spent forty-five minutes of the meeting focusing on one thing: their custom PHP content management system. They had opinions about the CMS. Strong opinions. They had benchmarks, a migration plan, a proof of concept. They had a diagram. They had questions about the deployment pipeline for this CMS that were, for a single application, more thoroughly considered than most organizations' entire infrastructure strategies.

On April 7, Anthropic announced that its Claude Mythos Preview model had autonomously identified thousands of high- and critical-severity zero-day vulnerabilities across every major operating system and every major web browser. Over 99% of them were unpatched the day of disclosure. Two weeks later, on April 21, Mozilla said it had used the same model to find and patch 271 vulnerabilities in the latest Firefox release.