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2026 Will Be the Year of Agentic Workloads in Production on Amazon EKS

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Kandungan disediakan oleh The New Stack Podcast and The New Stack. Semua kandungan podcast termasuk episod, grafik dan perihalan podcast dimuat naik dan disediakan terus oleh The New Stack Podcast and The New Stack atau rakan kongsi platform podcast mereka. Jika anda percaya seseorang menggunakan karya berhak cipta anda tanpa kebenaran anda, anda boleh mengikuti proses yang digariskan di sini https://ms.player.fm/legal.

AWS’s approach to Elastic Kubernetes Service has evolved significantly since its 2018 launch. According to Mike Stefanik, Senior Manager of Product Management for EKS and ECR, today’s users increasingly represent the late majority—teams that want Kubernetes without managing every component themselves. In a conversation onThe New Stack Makers, Stefanik described how AI workloads are reshaping Kubernetes operations and why AWS open-sourced an MCP server for EKS. Early feedback showed that meaningful, task-oriented tool names—not simple API mirrors—made MCP servers more effective for LLMs, prompting AWS to design tools focused on troubleshooting, runbooks, and full application workflows. AWS also introduced a hosted knowledge base built from years of support cases to power more capable agents.

While “agentic AI” gets plenty of buzz, most customers still rely on human-in-the-loop workflows. Stefanik expects that to shift, predicting 2026 as the year agentic workloads move into production. For experimentation, he recommends the open-source Strands SDK. Internally, he has already seen major productivity gains from BI agents that automate complex data analysis tasks.

Learn more from The New Stack about Amazon Web Services’ approach to Elastic Kubernetes Service

How Amazon EKS Auto Mode Simplifies Kubernetes Cluster Management (Part 1)

A Deep Dive Into Amazon EKS Auto (Part 2)

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  continue reading

917 episod

Artwork
iconKongsi
 
Manage episode 521642127 series 75006
Kandungan disediakan oleh The New Stack Podcast and The New Stack. Semua kandungan podcast termasuk episod, grafik dan perihalan podcast dimuat naik dan disediakan terus oleh The New Stack Podcast and The New Stack atau rakan kongsi platform podcast mereka. Jika anda percaya seseorang menggunakan karya berhak cipta anda tanpa kebenaran anda, anda boleh mengikuti proses yang digariskan di sini https://ms.player.fm/legal.

AWS’s approach to Elastic Kubernetes Service has evolved significantly since its 2018 launch. According to Mike Stefanik, Senior Manager of Product Management for EKS and ECR, today’s users increasingly represent the late majority—teams that want Kubernetes without managing every component themselves. In a conversation onThe New Stack Makers, Stefanik described how AI workloads are reshaping Kubernetes operations and why AWS open-sourced an MCP server for EKS. Early feedback showed that meaningful, task-oriented tool names—not simple API mirrors—made MCP servers more effective for LLMs, prompting AWS to design tools focused on troubleshooting, runbooks, and full application workflows. AWS also introduced a hosted knowledge base built from years of support cases to power more capable agents.

While “agentic AI” gets plenty of buzz, most customers still rely on human-in-the-loop workflows. Stefanik expects that to shift, predicting 2026 as the year agentic workloads move into production. For experimentation, he recommends the open-source Strands SDK. Internally, he has already seen major productivity gains from BI agents that automate complex data analysis tasks.

Learn more from The New Stack about Amazon Web Services’ approach to Elastic Kubernetes Service

How Amazon EKS Auto Mode Simplifies Kubernetes Cluster Management (Part 1)

A Deep Dive Into Amazon EKS Auto (Part 2)

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

Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

  continue reading

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