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ContentUpdates and recent posts about Google Kubernetes Engine (GKE)..
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@devopslinks shared a link, 4 weeks ago
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A complete guide to HTTP caching

A fresh guide reframes HTTP caching as less of a tweak, more of an architectural move. It breaks caching into layers - browser memory, CDNs, reverse proxies, app stores - and shows how each one plays a part (or gets in the way). It gets granular with headers likeCache-Control,ETag, andVary, calling .. read more  

A complete guide to HTTP caching
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@devopslinks shared a link, 4 weeks ago
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Terraform Stacks: A Deep-Dive for Azure Practitioners in Europe

Terraform Stacksjust hit GA onHCP Terraform, and they bring some real structure to the chaos. Think modular, declarative, and way less workspace spaghetti. Build reusablecomponents(a.k.a. modules), bundle them intodeployments, and wire up stacks usingpublish/consume patterns- complete with automated.. read more  

Terraform Stacks: A Deep-Dive for Azure Practitioners in Europe
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Unlocking self-service LLM deployment with platform engineering

A new platform stack - Port+GitHub Actions+HCP Terraform** - is turning LLM deployment into a clean self-service flow. The result => predictable, governed pipelines that ship faster. Infra gets standardized. Provisioning? Handled through GitHub Actions. Policies? Baked in via HCP Terraform. Port tie.. read more  

Unlocking self-service LLM deployment with platform engineering
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@devopslinks shared a link, 4 weeks ago
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Post-quantum (ML-DSA) code signing with AWS Private CA and AWS KMS

AWS Private CA now supportspost-quantum ML-DSA X.509 certificates. That means quantum-resistant roots of trust - for code signing, mTLS, and device auth. It's wired up with AWS KMS, so you can handle signing workflows usingML-DSA keysand verify them with standard tools like OpenSSL usingCMS detached.. read more  

Post-quantum (ML-DSA) code signing with AWS Private CA and AWS KMS
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WTF is ... - AI-Native SAST?

AI-native SAST is replacing the “LLM as magic scanner” myth. Instead, the smart play is combining language models with real static analysis. That’s how teams are catching the gnarlier stuff - like business logic bugs - that usually slip through. The trick?Use static analysis to grab clean, relevant .. read more  

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@varbear shared an update, 4 weeks, 1 day ago
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New MCP Release v0.10.0 Supercharges AI-Assisted Web Development

chrome-devtools-mcp

Chrome DevTools MCP v0.10.0 unlocks deeper AI-powered debugging with new tools for DOM access, network request detection, page reload automation, performance insights, and snapshot saving.

Google Launches Chrome DevTools MCP Server Preview for AI-Driven Web Debugging
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@varbear added a new tool chrome-devtools-mcp , 4 weeks, 1 day ago.
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@varbear shared an update, 4 weeks, 1 day ago
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AWS Lambda Gets Python 3.14: Faster, Smarter, and More Serverless-Friendly

AWS Lambda

Python 3.14 is now available in AWS Lambda, enabling developers to leverage new Python features for serverless applications.

AWS Lambda Gets Python 3.14: Faster, Smarter, and More Serverless-Friendly
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@kaptain shared an update, 4 weeks, 1 day ago
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The Most Absurd (and Brilliant) Kubernetes Cluster at KubeCon 2025

Kubernetes Talos Linux

Engineer Justin Garrison showcased a backpack-sized PETAFLOP Kubernetes cluster at KubeCon 2025, demonstrating localized AI capabilities without cloud reliance.

The Most Absurd (and Brilliant) Kubernetes Cluster at KubeCon 2025
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@kaptain added a new tool Talos Linux , 4 weeks, 1 day ago.
Google Kubernetes Engine (GKE) offers a Kubernetes experience on Autopilot that manages the underlying compute infrastructure without the need for manual configuration or monitoring. It provides container-native networking and security features, prebuilt Kubernetes applications and templates, pod and cluster autoscaling, and automated tools for workload migration. GKE clusters consist of a control plane and nodes that run the services supporting the containers. Autopilot mode manages the complexity of the cluster while allowing you to deploy and run your apps easily. The common uses of GKE include continuous integration and delivery, migrating workloads, and deploying and running applications. GKE pricing is based on the mode of operation, cluster management fees, and applicable multi-cluster ingress fees, with a free tier and a pricing calculator available to estimate costs. You can also connect with Google's sales team to get a custom quote for your organization or start your proof of concept.