Contributed Content
Mastering AKS: Performance, Security and Cost Optimization in the Cloud
Master Azure Kubernetes Service (AKS) with best practices for performance, security, cost optimization, GitOps, and enterprise-grade operations. A complete guide for DevOps teams ...
Yash Kant Gautam | | AKS best practices, AKS cost optimization, AKS observability, AKS production deployment, AKS troubleshooting guide, Azure AD RBAC, Confidential computing AKS, enterprise Kubernetes, GitOps with Flux, KEDA autoscaling, Key Vault CSI driver, Kubernetes chaos engineering, Kubernetes cost reduction, Kubernetes node pool strategy, Kubernetes performance optimization, Kubernetes security, Predictive autoscaling AKS
From Chaos to Control: Managing Kubernetes Add-Ons at Scale
Learn how to manage Kubernetes add-ons at scale with better visibility, drift detection and automation to improve reliability and performance ...
Observability for Microservices vs Monoliths: Strategies that Worked in 2025
Learn how observability strategies differ between monolithic and microservice architectures. Explore challenges, best practices and tooling for DevOps and SRE teams in 2025 ...
Neel Shah | | AI-driven observability, centralized logging, DevOps observability strategies, distributed tracing, dynamic infrastructure observability, Grafana Honeycomb Middleware, microservices monitoring, microservices vs monoliths, monolith performance monitoring, observability, observability tools 2025, OpenTelemetry, scalable telemetry ingestion, service metrics, smart alerting, SRE best practices, telemetry data, tracing context propagation
How Containerization Enhances Enterprise Mobile App Deployment?
Containerization is revolutionizing enterprise mobile app deployment by improving speed, consistency, scalability, and security. Learn how containers streamline CI/CD pipelines, enhance collaboration, reduce costs, and ensure reliability across environments for modern, cloud-native ...
Arun Goyal | | 5G, AI integration, app deployment, automation, CI/CD, cloud infrastructure, consistency, container security, containerization, devops, digital transformation, docker, edge computing, enterprise mobile apps, kubernetes, microservices, mobile development, orchestration, scalability, security
How SREs are Using AI to Transform Incident Response in the Real World
Traditional incident response can’t keep pace with today’s complex, multi-cloud environments. Discover how AI-augmented SRE frameworks reduce MTTR, automate remediation, and strengthen reliability through a five-stage maturity model and modular architecture powered ...
Manvitha Potluri | | AI incident response, AI operations, AIOps, anomaly detection, autonomous remediation, cloud native, DevOps automation, event correlation, feedback-driven automation, intelligent observability, MTTR reduction, multi-cloud, observability, reliability engineering, root cause analysis, site reliability engineering, SLA compliance, SRE
Prepare for the Second Wave of Container Management
There’s no doubt that containers bring big advantages to the enterprise IT departments, particularly when it comes to simplifying work for application developers. Unfortunately, that simplicity doesn’t always translate to the operations ...
Why Kubernetes is Great for Running AI/MLOps Workloads
Kubernetes has become the de facto platform for deploying AI and MLOps workloads, offering unmatched scalability, flexibility, and reliability. Learn how Kubernetes automates container operations, manages resources efficiently, ensures security, and supports ...
Joydip Kanjilal | | AI containerization, AI model deployment, AI on Kubernetes, AI scalability, AI Workloads, cloud-native ML, container orchestration, data science infrastructure, DevOps for AI, edge AI, fault tolerance, federated learning, GPU management, hybrid cloud AI, Kubeflow, KubeRay, kubernetes, Kubernetes automation, Kubernetes security, machine learning on Kubernetes, ML workloads, MLflow, MLOps, persistent volumes, resource management, scalable AI infrastructure, TensorFlow
GPU Resource Management for Kubernetes Workloads: From Monolithic Allocation to Intelligent Sharing
AI and ML workloads in Kubernetes are evolving fast—but traditional GPU allocation leads to massive waste and inefficiency. Learn how intelligent GPU allocation, leveraging technologies like MIG, MPS, and time-slicing, enables smarter, ...
Ashfaq Munshi | | AI infrastructure optimization, AI workload orchestration, AI/ML GPU efficiency, GPU cost efficiency, GPU efficiency in AI workloads, GPU overprovisioning, GPU partitioning technologies, GPU resource allocation strategies, GPU resource management, GPU sharing in Kubernetes, GPU time-slicing, GPU utilization optimization, GPU workload rightsizing, intelligent GPU allocation, Kubernetes AI workloads, Kubernetes GPU performance, Kubernetes GPU scheduling, multi-instance GPU, multi-process service, NVIDIA MIG, NVIDIA MPS
Guided Observability: Faster Resolution Through Context and Collaboration
Cloud native has increased in complexity, producing massive volumes of telemetry that are costly to store and hard to use. Guided Observability is emerging as a practice to help teams cut through the ...
Do You Even Need Kubernetes for Reliable Service Delivery?
Kubernetes has become the default backbone of cloud native architecture. But does it actually help you ship services more reliably, or is it just more moving parts? Despite Betteridge’s law of headlines, ...

