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Cloud platforms, services, and infrastructure

GKE Cost Optimization Starts With Workload Requests, Then Scales to Nodes and GPUs
AI & ML

GKE Cost Optimization Starts With Workload Requests, Then Scales to Nodes and GPUs

GKE’s automation can manage infrastructure, but teams still need to right-size workloads and match capacity to demand. New utilization data shows where to start.

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EKS Cost Optimization: Why Kubernetes Clusters Leave CPU and GPUs Idle
AI & ML

EKS Cost Optimization: Why Kubernetes Clusters Leave CPU and GPUs Idle

EKS fleets average 8% CPU and 5% GPU utilization. Rightsizing, workload sharing and smarter Spot placement can turn idle capacity into useful compute.

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Kubernetes-Native ML Platforms Need Declarative Lifecycle Management
AI & ML

Kubernetes-Native ML Platforms Need Declarative Lifecycle Management

Kubernetes can schedule ML workloads, but declarative lifecycle control is what makes training, evaluation, and deployment observable and recoverable.

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CIQ Stratum Kubernetes Engine Bundles Cluster Deployment and AI Agent Controls
AI & ML

CIQ Stratum Kubernetes Engine Bundles Cluster Deployment and AI Agent Controls

CIQ’s open-source Stratum SKE packages Kubernetes in one signed binary, with managed upgrades and tiered MCP tools for controlled agent access.

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Mirantis Offers VMware-to-Kubernetes Migration Help for OpenStack
AI & ML

Mirantis Offers VMware-to-Kubernetes Migration Help for OpenStack

Mirantis will assess and migrate VMware workloads to its MOSK platform, with typical projects taking about five weeks and aiming to reuse existing infrastructure.

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Akamai Agent Sandbox Uses WebAssembly to Isolate AI-Generated Code
AI & ML

Akamai Agent Sandbox Uses WebAssembly to Isolate AI-Generated Code

Akamai’s beta sandbox isolates code written by AI agents with WebAssembly, addressing growing security risks as agents gain access to company systems.

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Argo CD at 34 Clusters: What Makes a GitOps Control Plane Work
AI & ML

Argo CD at 34 Clusters: What Makes a GitOps Control Plane Work

A 34-cluster Argo CD fleet shows how clear cluster contracts, rendered diffs and cautious deletion settings can keep GitOps manageable at scale.

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Circle and ACI Pilot USDC Settlement on Colombia’s Existing Banking Rails
AI & ML

Circle and ACI Pilot USDC Settlement on Colombia’s Existing Banking Rails

Circle and ACI will test USDC settlement alongside Colombia’s instant payment network, exploring how stablecoins can fit banks’ existing systems.

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Kubernetes Workload Identity: Short-Lived Tokens for Secure Cloud Access
AI & ML

Kubernetes Workload Identity: Short-Lived Tokens for Secure Cloud Access

Kubernetes workload identity replaces static credentials with short-lived tokens, while requiring trusted issuers, audience checks and token rotation.

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Ken Griffin Warns of an AI Bubble While Seeing Long-Term Potential
AI & ML

Ken Griffin Warns of an AI Bubble While Seeing Long-Term Potential

Griffin warns AI chip oversupply and cheaper models could pressure returns, even as AI agents show practical productivity gains.

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GitOps Release Promotion Adds Control to Kubernetes Fleet Deployments
AI & ML

GitOps Release Promotion Adds Control to Kubernetes Fleet Deployments

For fleets of hundreds of Kubernetes clusters, staged release promotion adds verification, visibility and a stop point between a Git merge and broad deployment.

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Infrastructure as Code Gives AI Agents a Safer Path to Kubernetes Changes
AI & ML

Infrastructure as Code Gives AI Agents a Safer Path to Kubernetes Changes

IaC makes Kubernetes and hybrid infrastructure changes reviewable, helping teams manage upgrades and drift while keeping AI agents inside human approval workflows.

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Adapting Service Virtualization Strategies for Evolving Cloud-Native Architectures
AI & ML

Adapting Service Virtualization Strategies for Evolving Cloud-Native Architectures

Service virtualization must evolve with cloud-native architectures to ensure accuracy, as independent deployments can lead to misalignment and integration risks.

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Streamlining WordPress with Containers on Kubernetes: A Practical Approach
AI & ML

Streamlining WordPress with Containers on Kubernetes: A Practical Approach

Exploring the practical integration of headless WordPress and Kubernetes for improved scalability and deployment efficiency in web applications.

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Reevaluating Autoscaling: Aligning Scheduler and Infrastructure Metrics
AI & ML

Reevaluating Autoscaling: Aligning Scheduler and Infrastructure Metrics

A hands-on approach to test autoscaling reveals vital discrepancies between scheduler capacity and infrastructure metrics, essential for optimized operations.

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Maximizing Azure Kubernetes Service: Addressing Resource Inefficiencies in AI Workloads
AI & ML

Maximizing Azure Kubernetes Service: Addressing Resource Inefficiencies in AI Workloads

Research shows Azure Kubernetes Service suffers from significant resource inefficiencies, with up to 98% of GPU costs wasted due to overprovisioning.

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Understanding Secrets Synchronization Issues in Kubernetes Deployments
AI & ML

Understanding Secrets Synchronization Issues in Kubernetes Deployments

Explore how mismatches in Kubernetes Secrets across pods can lead to performance issues and learn strategies for effective deployment verification.

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Nvidia Surges to $5.7 Trillion Valuation Amid Record Buyback and AI Demand
AI & ML

Nvidia Surges to $5.7 Trillion Valuation Amid Record Buyback and AI Demand

Nvidia's stock hits an all-time high, reflecting strong AI-driven revenue and a historic $150 billion buyback, solidifying its top position in the tech sector.

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Microsoft Embeds Linux Container Functionality in Windows for Developers
AI & ML

Microsoft Embeds Linux Container Functionality in Windows for Developers

Microsoft's latest update integrates Linux container support directly into Windows, simplifying development for Linux-based applications.

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Anthropic's Financial Review: A Candid Look at AI Investment and Revenue Risks
AI & ML

Anthropic's Financial Review: A Candid Look at AI Investment and Revenue Risks

Anthropic faces significant financial challenges with a $42 billion loss projected for 2025, raising concerns about the sustainability of its AI expansion efforts.

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