Cloud-Native Architecture
Rearchitecting Legacy Systems for Real-Time AI: Practical Patterns for Cloud-Native Migration
Artificial intelligence is changing what enterprises expect from software platforms. Systems that once processed transactions in batches are increasingly expected to evaluate events, apply intelligence and respond in near real time. The ...
Best Strategies for Cloud Native Cost Optimization
The rise of cloud-native technologies—containers, microservices, serverless computing and Kubernetes—has pushed companies to think more carefully about how to control the costs associated with these technologies. As the number of organizations deploying ...
CNCF Graduates Kubeflow for Production AI on Kubernetes
The Cloud Native Computing Foundation has graduated Kubeflow, giving the open source AI and machine learning platform CNCF’s highest maturity designation as enterprises move more AI workloads into production. Kubeflow runs on ...
The Foundation Was Already Poured
Techstrong's Experts Exchange this October, Cloud Native Now: The AI Stack, and this November's KubeCon in Salt Lake City are both making the same case for cloud native and AI. The argument ...
Alan Shimel | | agent governance, agent identity, agentic AI, AI agents, AI governance, AI infrastructure, AI security, AI stack, AI strategy, AI Workloads, cloud native, cloud native developers, cncf, enterprise AI, GPU scheduling, KubeCon, kubernetes, Kubernetes AI, MLOps, model serving, observability, platform engineering, sigstore, SLSA, software supply chain security
Beyond the Model: Why AI Agent Orchestration Requires Cloud-Native Engineering
AI agent orchestration is a distributed systems challenge. Cloud-native engineering provides the resilience, observability, security and scalability needed for production AI ...
Nithiya Dharshini | | agent communication, agentic AI infrastructure, AI agent orchestration, AI governance, AI infrastructure, AI observability, AI scalability, AI security, AI workflow monitoring, AI workload management, automated scaling, cloud native AI, cloud-native engineering, containerized AI services, distributed AI systems, distributed tracing, enterprise AI agents, event-driven architecture, GitOps, Kubernetes for AI, multi-agent systems, platform engineering, production AI systems, resilient AI systems
Stop Treating Your Models Like Microservices
A few years ago, it felt like Kubernetes had become the universal answer to infrastructure problems. Teams wanted resiliency? Kubernetes. Faster deployments? Kubernetes. Scalability? Kubernetes again. Eventually, the industry stopped treating cloud-native ...
How Cloud-Native Complexity is Outpacing Test Automation Strategy
Cloud-native architectures evolve faster than most test automation strategies. Understand where the gap is widest and what teams can do about it. ...
Cloud Native Is Becoming AI Native
Open Source Summit North America has always been a good place to see where infrastructure is going before the market fully catches up. This year, the signal is not exactly subtle. The ...
Beyond the Runbook: How to Scale SRE Operations for Cloud-Native Infrastructure
The uncomfortable truth is plain for all to see: Trying to keep dynamic, living systems running with static runbook methodologies is dead thinking... What’s emerging to replace the runbook is a machine ...
Why Observability is Critical for Modern Cloud‑Native Systems
In the future, observability will be a key factor for any organization looking to succeed with the concept of cloud native architectures ...

