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Kubernetes automation

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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 | October 29, 2025 | 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

K0rdent, costs, scheduling, cost, Kubecost cloud-native costs OpenCost Stackwatch Kubecost cost allocation Reduce Virtual Machine Licensing Costs

Building FinOps With k0rdent Open Source

Learn how open-source k0rdent and KOF enable platform teams to build custom FinOps solutions with predictive cost forecasting and real-time savings insights ...

Satyam Bhardwaj | October 9, 2025 | AI-driven FinOps, cloud cost optimization, cloud financial management, cloud utilization optimization, cloud-native FinOps framework, cluster cost reduction, FinOps Agent, FinOps pipeline, Grafana dashboards, idle resource detection, k0rdent, k0rdent MultiClusterService, KOF, Kubernetes automation, Kubernetes cost visibility, Kubernetes FinOps, Kubernetes monitoring, Kubernetes observability, Kubernetes scalability, multi-cluster Kubernetes management, open-source FinOps tools, OpenTelemetry, predictive cost forecasting, Prometheus metrics, time series forecasting, TOTO model

Akuity, SUSE, Nutanix, kubernetes, cycle, Mirantis, kubernetes, LoftLabs, vNode, Komodor, configurations, application, clusters, virtual, Red Hat, Kubernetes clusters, Komodor, kubernetes, clusters, kubernetes, IDPs, TLS, certificates, clusters, virtual clusters, Kubernetes, Kubernetes, vCluster CAST AI KBOM DoKC Platform9 Kubernetes

CNCF Elevates Platform for Managing Bare Metal Servers Running Kubernetes

CNCF elevates Metal3.io to incubation, advancing open-source automation for managing Kubernetes clusters on bare-metal infrastructure ...

Mike Vizard | September 3, 2025 | AI workloads bare metal, Baremetal Operator BMO, cloud-native infrastructure automation, Cluster API Provider Metal3 CAPM3, CNCF incubation project, CNCF open source projects, Ericsson Metal3, Ironic framework, Kubernetes automation, Kubernetes bare metal, Kubernetes infrastructure management, Kubernetes on bare metal, Kubernetes operators, Metal3.io, Red Hat Metal3

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Modernizing Manufacturing: How to Move from Legacy Infrastructure to Cloud-Ready Operations

18 August 2026

Modernizing Manufacturing: How to Move from Legacy Infrastructure to Cloud-Ready Operations

Migrating Apache Solr Workloads to Amazon OpenSearch Service

28 July 2026

Migrating Apache Solr Workloads to Amazon OpenSearch Service

From Pilot to Production: AI that Delivers Business Outcomes

27 July 2026

DevOps in the Age of AI Native

17 August 2026

DevOps in the Age of AI Native

AI Writes Code Fast. Can You Trust What Gets Deployed?

12 August 2026

AI Writes Code Fast. Can You Trust What Gets Deployed?

How the Biggest Banks Stay Fast, Nimble, and Multi-Vendor

5 August 2026

How the Biggest Banks Stay Fast, Nimble, and Multi-Vendor

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ThreatHunter.ai Halts Hundreds of Attacks in the past 48 hours: Combating Ransomware and Nation-State Cyber Threats Head-On

ThreatHunter.ai Halts Hundreds of Attacks in the past 48 hours: Combating Ransomware and Nation-State Cyber Threats Head-On

Deloitte Partners with Memcyco to Combat ATO and Other Online Attacks with Real-Time Digital Impersonation Protection Solutions

Deloitte Partners with Memcyco to Combat ATO and Other Online Attacks with Real-Time Digital Impersonation Protection Solutions

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MOST READ

Google OpenRL Tames AI Model Tuning, Kubernetes-Style

June 17, 2026

Linkerd 2.20, the Latest Release of the Cloud-Native Service Mesh, Arrives

June 24, 2026

Minimus Makes Hardened Container Images Freely Available to All Developers

June 23, 2026

Upbound Unfurls Control Plane for Managing AI Inference Workloads

June 23, 2026

Tigera Introduces Lynx, a Unified Control Plane for Kubernetes‑Native AI Agents

July 2, 2026

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Software Testing and Test Automation

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Which of the following best describes your involvement in software testing or test automation at your organization? (Select one)*
- I actively perform software testing or test automation
- I manage or lead software testing or QA teams
- I make decisions about testing tools, frameworks, or automation strategy
- I do both hands-on testing and make strategic/tool decisions
- None of the above

How much of your organization's software testing is still performed manually today? (Select one)*
- Almost all
- More than half
- About half
- Less than half
- Almost none

How much effort does your team spend maintaining existing automated tests compared to creating new test coverage? (Select one)*
- Mostly maintaining existing tests
- More maintenance than new coverage
- About equal
- More new coverage than maintenance
- Very little maintenance required

How much has AI-assisted software development increased the pressure on your testing teams over the past 12 months? (Select one)*
- Significantly increased pressure
- Moderately increased pressure
- Slightly increased pressure
- No meaningful impact yet
- Unsure

What is the biggest obstacle preventing your organization from expanding software test automation and adopting agentic testing? (Select one)*
- Automated tests are too difficult or costly to maintain
- Release cycles move too quickly to keep tests current
- Too much coding or scripting expertise is required
- Testing tools and frameworks are too fragmented
- Lack of time, budget, or staffing
- Difficulty proving business value or ROI
- Insufficient AI or intelligent automation capabilities

Which improvement would create the greatest business impact for your organization over the next 12 months? (Select one)*
- Reducing manual testing effort
- Reducing automated test maintenance
- Accelerating release cycles
- Expanding test coverage across more technologies
- Consolidating testing tools and frameworks
- Enabling more non-developers to automate testing
- Improving the resilience and adaptability of automated tests

Which statement best reflects your organization's current perspective on AI-powered or agentic software testing? (Select one)*
- We are actively evaluating or adopting AI-powered testing approaches
- We are interested, but still assessing practical value and trust
- We believe current automated testing approaches are sufficient
- We are primarily focused on improving existing automation before adopting AI-assisted testing
- We have not yet explored AI-powered testing in a meaningful way

How important is the ability to execute continuous, largely autonomous software testing with minimal human intervention ("lights-out" or "dark factory" testing) to your organization's future software delivery strategy? (Select one)*
- Critical strategic priority
- Important, but still early-stage
- Somewhat important
- Low priority today
- Not relevant to our organization
- Unsure

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