The New Stack Podcast

Running AI models on Kubernetes has historically been inconsistent, with workloads behaving differently across cloud providers due to variations in GPUs, networking, and autoscaling. As organizations move AI from experimentation to production, standardization has become critical. In this episode of The New Stack Makers, Jonathan Bryce, Executive Director of The Cloud Native Computing Foundation sh...

At KubeCon EU 2026, Mitch Connors of Microsoft outlined a vision to make service meshes effectively invisible to users. Now working on Azure Kubernetes Application Network, a fully managed service built on Istio’s ambient mode, Connors aims to deliver core capabilities like mTLS without requiring users to engage with the complexity traditionally associated with service meshes. Ambient mode elimina...

At KubeCon + CloudNativeCon Europe 2026 in Amsterdam, Alex Kestner, principal product manager for Amazon Elastic Kubernetes Service (EKS), discussed how Amazon EKS Auto Mode aims to reduce the operational burden of running Kubernetes at scale. While Kubernetes delivers significant power, it also introduces complexity—particularly through repetitive, day-to-day tasks like managing node lifecycles,...

At KubeCon + CloudNativeCon Europe 2026, Lena Hall and Thorsten Hans of Akamai outlined how the company is evolving from a CDN provider into a developer-focused cloud platform for AI. Akamai’s strategy centers on low-latency, distributed computing, combining managed Kubernetes, serverless functions, and a distributed AI inference platform to support modern workloads. With a global footprint of cor...

In this episode of The New Stack Makers, Microsoft Corporate Vice President and Technical Fellow, Brendan Burns discusses how AI is reshaping Kubernetes and modern infrastructure. Originally designed for stateless applications, Kubernetes is evolving to support AI workloads that require complex GPU scheduling, co-location, and failure sensitivity. Features like Dynamic Resource Allocation and proj...

In this episode of The New Stack Agents , Marcin Wyszynski, co-founder of Spacelift and OpenTofu, explains how AI is transforming infrastructure as code (IaC). Originally built for individual operators, tools like Terraform struggled to scale across teams, prompting Wyszynski to help launch OpenTofu after HashiCorp’s 2023 license change. Now, the bigger shift is AI: engineers no longer write confi...

Woodson Martin, CEO ofOutSystems, argues that successful enterprise AI deployments rarely rely on standalone agents. Instead, production systems combine AI agents with data, workflows, APIs, applications, and human oversight. While claims that “95% of agent pilots fail” are common, Martin suggests many of those pilots were simply low-commitment experiments made possible by the low cost of testing...

On a recent episode of the The New Stack Agents, Inception Labs CEO Stefano Ermon introduced Mercury 2, a large language model built on diffusion rather than the standard autoregressive approach. Traditional LLMs generate text token by token from left to right, which Ermon describes as “fancy autocomplete.” In contrast, diffusion models begin with a rough draft and refine it in parallel, similar t...

On The New Stack Agents , Gavriel Cohen discusses why he built NanoClaw, a minimalist alternative to OpenClaw, after discovering security and architectural flaws in the rapidly growing agentic framework. Cohen, co-founder of AI marketing agencyQwibit, had been running agents across operations, sales, and research usingClaude Code. When Clawdbot (laterOpenClaw) launched, it initially seemed ideal....

A few weeks after Dynatrace acquired DevCycle, Michael Beemer and Andrew Norris discussed on The New Stack Makers podcast how feature flagging is becoming a critical safeguard in the AI era. By integrating DevCycle’s feature flagging into the Dynatrace observability platform, the combined solution delivers a “360-degree view” of software performance at the feature level. This closes a key visibili...

Dynatrace is at a pivotal point, expanding beyond traditional observability into a platform designed for autonomous operations and security powered by agentic AI. In an interview on *The New Stack Makers*, recorded at the Dynatrace Perform conference, Chief Technology Strategist Alois Reitbauer discussed his vision for AI-managed production environments. The conversation followed Dynatrace’s acqui...

Matan-Paul Shetrit, Director of Product Management at Writer, argues that people must take responsibility for how they use AI. If someone produces poor-quality output, he says, the blame lies with the user—not the tool. He believes many misunderstand AI’s role, confusing its ability to accelerate work with an abdication of accountability. Speaking on The New Stack Agents podcast, Shetrit emphasize...

AI coding assistants are boosting developer productivity, but most enterprises aren’t shipping software any faster. GitLab CEO Bill Staples says the reason is simple: coding was never the main bottleneck. After speaking with more than 60 customers, Staples found that developers spend only 10–20% of their time writing code. The remaining 80–90% is consumed by reviews, CI/CD pipelines, security scan...

Sean O’Dell of Dynatrace argues that enterprises are unprepared for a major shift brought on by AI: the rise of the developer. Speaking at Dynatrace Perform in Las Vegas, O’Dell explains that AI-assisted and “vibe” coding are collapsing traditional boundaries in software development. Developers, once insulated from production by layers of operations and governance, are now regaining end-to-end own...

In the era of agentic AI, attention has largely focused on data itself, while metadata has remained a neglected concern. Junping (JP) Du, founder and CEO of Datastrato, argues that this must change as AI fundamentally alters how data and metadata are consumed, governed, and understood. To address this gap, Datastrato created Apache Gravitino, an open source, high-performance, geo-distributed, fede...

Chris Aniszczyk, co-founder and CTO of the Cloud Native Computing Foundation (CNCF), argues that AI agents resemble microservices at a surface level, though they differ in how they are scaled and managed. In an interview ahead of KubeCon/CloudNativeCon Europe, he emphasized that being “AI native” requires being cloud native by default. Cloud-native technologies such as containers, microservices, K...

API sprawl creates hidden security risks and missed revenue opportunities when organizations lose visibility into the APIs they build. According to IBM’s Neeraj Nargund, APIs power the core business processes enterprises want to scale, making automated discovery, observability, and governance essential—especially when thousands of APIs exist across teams and environments. Strong governance helps i...

A CloudBees survey reveals that enterprise migration projects often fail to deliver promised modernization benefits. In 2024, 57% of enterprises spent over $1 million on migrations, with average overruns costing $315,000 per project. In The New Stack Makers podcast, CloudBees CEO Anuj Kapur describes this pattern as “the migration mirage,” where organizations chase modernization through costly mig...

IBM’s recent acquisitions of Red Hat, HashiCorp, and its planned purchase of Confluent reflect a deliberate strategy to build the infrastructure required for enterprise AI. According to IBM’s Sanil Nambiar, AI depends on consistent hybrid cloud runtimes (Red Hat), programmable and automated infrastructure (HashiCorp), and real-time, trustworthy data (Confluent). Without these foundations, AI canno...

Ari Zilka, founder of MyDecisive.ai and former Hortonworks CPO, argues that most observability vendors now offer essentially identical, reactive dashboards that highlight problems only after systems are already broken. After speaking with all 23 observability vendors at KubeCon + CloudNativeCon North America 2025, Zilka said these tools fail to meaningfully reduce mean time to resolution (MTTR), a...

Former GitHub CEO Thomas Dohmke’s claim that AI-based development requires progressive delivery frames a conversation between analyst James Governor and The New Stack’s Alex Williams about why modern release practices matter more than ever. Governor argues that AI systems behave unpredictably in production: models can hallucinate, outputs vary between versions, and changes are often non-determinis...

Most enterprises today run workloads across multiple IT infrastructures rather than a single platform, creating significant operational challenges. According to Nutanix CTO Deepak Goel, organizations face three major hurdles: managing operational complexity amid a shortage of cloud-native skills, migrating legacy virtual machine (VM) workloads to microservices-based cloud-native platforms, and run...

GPUs dominate today’s AI landscape, but Google argues they are not necessary for every workload. As AI adoption has grown, customers have increasingly demanded compute options that deliver high performance with lower cost and power consumption. Drawing on its long history of custom silicon, Google introduced Axion CPUs in 2024 to meet needs for massive scale, flexibility, and general-purpose compu...

Enterprises are racing to deploy AI services, but the teams responsible for running them in production are seeing familiar problems reemerge—most notably, silos between data scientists and operations teams, reminiscent of the old DevOps divide. In a discussion recorded at AWS re:Invent 2025, IBM’s Thanos Matzanas and Martin Fuentes argue that the challenge isn’t new technology but repeating organi...

Rob Whiteley, CEO of Coder, argues that the biggest winners in today’s AI boom resemble the “picks and shovels” sellers of the California Gold Rush: companies that provide tools enabling others to build with AI. Speaking on The New Stack Makers at AWS re:Invent, Whiteley described the current AI moment as the fastest-moving shift he’s seen in 25 years of tech. Developers are rapidly adopting AI to...