Data Protection and Container Security in 5G Edge Deployments
5G networks running on the edge will move applications and data closer to the user to reduce latency and improve performance, but these advancements will introduce new security challenges. 5G far-edge deployments ...
Why 5G Needs Kubernetes
As with many things, COVID-19 sped up the need for high bandwidth delivered fast to end users. Working from home, Zoom calls, VPN connections, social media—all of it requires speed, resiliency and ...
GitOps is Essential for 5G Deployment
As 5G rollouts begin in earnest during 2021-2022, carriers are beginning to face the incredible challenge of deploying and configuring millions of devices, VMs and containers across not just the data center ...
CNFs to Drive Container App Deployment on 5G Networks in 2021
The widespread availability of next-generation 5G wireless networking services will drive a wider range of containerized applications to edge computing platforms in 2021. Most of those 5G networking services will be accessed ...
Kubermatic Joins 5G Consortium to Advance Kubernetes Adoption
Kubermatic, a provider of open source management platforms for Kubernetes clusters, has become a member of the 5G Open Innovation Lab, a global consortium of developers, startups, enterprises, academia and government institutions ...
Red Hat Extends Container Alliance With NVIDIA to 5G Edge
At the Mobile World Congress event this week, Red Hat and NVIDIA extended their alliance to include deployment of containerized artificial intelligence (AI) applications and services at the emerging 5G network edge ...
Why Your Kubernetes Readiness Probes Are Lying During Rolling Updates
Kubernetes readiness probes can pass while applications are still unable to serve real traffic. Protocol-aware checks help close the gap between “running” and truly “ready.” ...
Kubernetes Wasn’t Built for GPUs. Make It Behave
Kubernetes counts whole GPUs and treats pods as disposable. An LLM pod is neither. Share the silicon with MIG/MPS/time-slicing and stop paying for idle ...
Sneha Gullapalli | | A100, AI infrastructure, AI Workloads, cloud native AI, Dynamic Resource Allocation, GPU autoscaling, GPU cost reduction, GPU optimization, GPU partitioning, GPU sharing, GPU time-slicing, GPU utilization, H100, Karpenter, KServe, Kubernetes DRA, Kubernetes GPU scheduling, LLM Inference, model caching, multi-instance GPU, NVIDIA GPU Operator, NVIDIA MIG, NVIDIA MPS, scale-to-zero, VRAM
Stop Treating GPUs Like Web Pods
Kubernetes schedules accelerators as opaque integers, and your bill pays for it. Share the silicon, scale on the right signal and keep weights out of the image ...
Veera Ravindra Divi | | AI infrastructure, AI serving, autoscaling, cloud costs, cloud native AI, DCGM exporter, DRA, Dynamic Resource Allocation, GPU costs, GPU scheduling, GPU sharing, GPU utilization, GPUs, inference workloads, KEDA, kubernetes, Kubernetes GPU scheduling, LLM Inference, MIG, model weights, MPS, NVIDIA GPUs, NVIDIA MIG, Prometheus, scale-to-zero, time-slicing
Software Supply Chain Security: Why 99% of Your Container is Mystery Code
In a recent talk, the disparity between developers and platform engineers in container security was highlighted, revealing how a single line of code can pull in thousands of vulnerabilities. This article discusses ...
Jeroen van Erp | | Attestation, container security, Continuous Integration/Continuous Deployment (CI/CD), Dependency Management, Developer Relations, GitOps, Kubewarden, platform engineering, Provenance, Secure Base Images, SLSA compliance, Software Bill of Materials (SBOM), software supply chain security, Trust in Software Development., vulnerabilities

