The New Stack Podcast29 Apr 2025

Why Kubernetes Cost Optimization Keeps Failing

In today’s uncertain economy, businesses are tightening costs, including for Kubernetes (K8s) operations, which are notoriously difficult to optimize. Yodar Shafrir, co-founder and CEO of ScaleOps, explained at KubeCon + CloudNativeCon Europe that dynamic, cloud-native applications have constantly shifting loads, making resource allocation complex.

Engineers must provision enough resources to handle spikes without overspending, but in large production clusters with thousands of applications, manual optimization often fails. This leads to 70–80% resource waste and performance issues. Developers typically prioritize application performance over operational cost, and AI workloads further strain resources. Existing optimization tools offer static recommendations that quickly become outdated due to the dynamic nature of workloads, risking downtime.

Shafrir emphasized that real-time, fully automated solutions like ScaleOps' platform are crucial. By dynamically adjusting container-level resources based on real-time consumption and business metrics, ScaleOps improves application reliability and eliminates waste. Their approach shifts Kubernetes management from static to dynamic resource allocation. Listen to the full episode for more insights and ScaleOps' roadmap.

Learn more from The New Stack about the latest in scaling Kubernetes and managing operational costs:

ScaleOps Adds Predictive Horizontal Scaling, Smart Placement

ScaleOps Dynamically Right-Sizes Containers at Runtime

Join our community of newsletter subscribers to stay on top of the news and at the top of your game.

Det här avsnittet är hämtat från ett öppet RSS-flöde och publiceras inte av Podme. Det kan innehålla reklam.

Avsnitt(300)

Why CPUs still matter in the age of AI agents

As AI evolves from conversational chatbots to autonomous agents, CPUs are becoming an increasingly important part of the infrastructure equation. In this episode, The New Stack speaks with Bhumik Pate...

11 Aug 26min

Why Doist Says Less AI Can Deliver More

Doist CTO Gonçalo Silva says AI is reshaping software development, but success depends on restraint rather than rapid feature expansion. Instead of chasing every AI capability, Doist prioritizes “subt...

31 Juli 35min

Why your company should (try to) build its own AI SRE

As AI coding agents accelerate software development, they also create new challenges for site reliability engineers (SREs), who are increasingly responsible for debugging systems that no single human ...

30 Juli 30min

Nvidia

In this episode with The New Stack Agents, Frederic Lardinois, NVIDIA’s Joey Conway says advances in AI over the past year have dramatically improved the capabilities of local models, making them prac...

23 Juli 32min

Meet Brain, the AI that decides when Azure is officially down

In this episode, Mark Russinovich, CTO of Microsoft Azure revealed Brain, the AI-powered AIOps system that continuously monitors Azure’s health, detects incidents, identifies root causes, and increasi...

14 Juli 19min

What comes after attention? This startup says it already knows.

Subquadratic is beginning to back up its ambitious claims with benchmarks and third-party validation for its SubQ 1.1 Small model, which uses its proprietary Sparse Attention (SSA) architecture to dra...

7 Juli 20min

“The harness is where the hard work is”: Harness bets on agents that enterprises can trust in production

Harness has introduced Autonomous Worker Agents, a new capability that allows enterprises to replace rigid CI/CD pipeline scripts with AI agents that can deploy applications, run tests, and perform se...

2 Juli 19min

Public cloud vs. on-prem: Summit on where each workload belongs

More than two decades after AWS helped usher in the public cloud era, many organizations are reassessing whether a cloud-first strategy still delivers the cost and operational benefits it once promise...

25 Juni 36min