Kubernetes

If you are a platform engineer at a bank, you already know that adopting Kubernetes in a regulated environment is a different problem from adopting it at a SaaS startup. The control-plane security, audit trail requirements, and operational governance that satisfy your risk committee are not the same ones that satisfy a DevOps team shipping a web application. We have deployed all three of the major enterprise Kubernetes platforms — Rancher, OpenShift, and VMware Tanzu — in production at tier-one banks and hedge funds. We have run the RFI process, built the landing zones, and operated the clusters through regulatory audits. This is what we learned. ...

Quantitative research teams consume GPU compute differently from standard ML teams. A single backtest of a reinforcement learning strategy may require 8 H100 GPUs for 72 hours, then nothing for a week. A risk model training run may consume 4 A100s for 6 hours, but the researcher needs interactive access to the dashboard throughout. Peak demand is unpredictable and hit-driven. We have built GPU infrastructure for quant hedge funds and bank research desks on Kubernetes. Here is what we learned about scheduling, sharing, and cost management for financial ML workloads. ...

The operational overhead of managing physical or virtual servers—ranging from patching OS vulnerabilities to manually configuring scaling groups—has long been a persistent bottleneck for engineering teams. The fundamental problem being solved by serverless architecture is the decoupling of infrastructure management from application delivery. By abstracting the hardware layer and scaling on demand, teams can focus strictly on core application logic. In this article, we’ll examine the primary solutions across modern hyperscalers, detailing the differences between event-driven Functions-as-a-Service (FaaS) and serverless container deployments. ...

Container escapes represent one of the most critical security threats in modern containerized environments. When attackers break out of container isolation, they can gain access to the host system and potentially compromise entire infrastructure. Understanding these vulnerabilities and implementing proper defenses is crucial for secure container deployments. Understanding Container Escape Vectors Container escapes exploit weaknesses in isolation mechanisms that separate containers from their host systems. These attacks can occur through various vectors, each requiring specific defensive measures. ...

Service meshes solve the wrong problem if you adopt them for the wrong reasons. In financial services, the reason is not traffic management or observability — it is security and compliance. Every service-to-service communication must be encrypted, authenticated, and auditable. Manual certificate management and network policies do not scale when you have hundreds of microservices across multiple clusters. We have deployed both Istio and Linkerd in production at banks and fintechs. The choice depends on your security requirements, operational maturity, and team expertise — not which mesh has more GitHub stars. ...

By mid-2022, most banks had completed Kubernetes proof-of-concept deployments. The question was no longer “can we run Kubernetes?” but “how do we run Kubernetes in production while satisfying regulators?” The gap between POC and production is where most Kubernetes deployments fail — not because of technical limitations, but because of operational and compliance gaps. We have deployed production Kubernetes clusters at tier-one banks that satisfy regulatory audit requirements. The architecture is fundamentally different from Kubernetes at a SaaS startup. Here is what production Kubernetes looks like in a regulated environment. ...