Operations | Monitoring | ITSM | DevOps | Cloud

This blog was released off the back of our white paper, The Cost of Cloud 2025 - India Edition. Research was conducted with over 600 Indian tech professionals to create a comprehensive analysis of the Indian cloud market.

Has Kubernetes made your DevOps team faster, or just busier? Most teams adopt it for speed and portability, and they get both. What arrives with it is a quieter cost: the operational weight of running the cluster day to day. That weight shows up in the manual work the platform was supposed to eliminate. A resource limit set incorrectly can waste infrastructure for months.

There’s a question we hear constantly from platform and engineering leaders right now, “which agent SDK should we standardize on for our Kubernetes clusters?” The honest answer is that the question is slightly wrong, and the rest of this post explains why. But it’s a fair question, so let’s compare the contenders first.

The phrase "cloud first" dominated IT strategy for the better part of a decade. It was gospel, practically unchallengeable, and for a lot of organizations, it was the right call. But something shifted between 2024 and 2026, and it shifted fast. Bills stopped being defensible. Vendor pricing imploded. Sovereignty stopped being a compliance checkbox and became a procurement requirement.

To meet community demand, we have restored the global workload overview in Rancher Manager. After previously removing the feature due to performance constraints, we prioritized user feedback and rebuilt it from the ground up. Powered by a new, optimized API, the updated UI is both highly scalable and resilient.

Monitoring load is not always steady. A team might add a new batch of checks or run several ad hoc tests during a rollout. When that happens, your Private Location agents need to pick up more work at once. If there aren’t enough agents available during a burst, checks start piling up in the queue, which can delay or disrupt check execution. But solving this by running a high number of agents around the clock has the opposite problem: most of that capacity sits idle until the next busy period.

Financial services in the UK operates under one of the most demanding regulatory frameworks in the world. The FCA and PRA between them set expectations for operational resilience, outsourcing, data governance, and concentration risk that shape every infrastructure decision a regulated firm makes. Cloud adoption in the sector has happened, but it's happened under regulatory scrutiny that's grown steadily more pointed over the last several years.

AI workloads have a distinctive infrastructure profile that's exposing the cost and architectural assumptions baked into public cloud over the last decade.