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Bryan Cantrill: How Kubernetes Broke the AWS Cloud Monopoly

Bryan Cantrill says Kubernetes didn’t just organize containers, it cracked open the cloud market. By letting teams provision infrastructure without locking into provider APIs, it broke AWS’s first-mover grip. That shift putcloud neutralityon the table, and suddenly multi-cloud wasn’t just a buzzword.. read more  

Bryan Cantrill: How Kubernetes Broke the AWS Cloud Monopoly
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Kubernetes by Example

K8s by Exampleis likeGo by Example, but for YAML and Kubernetes. It’s packed with annotated manifests that show real deployment, scaling, and self-healing patterns, stuff you'd actually use in prod... read more  

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Kubernetes Was Overkill. We Moved to Docker Compose and Saved 60 Hours.

A small team rolled back their Kubernetes move after six months in the weeds. The setup tanked productivity, bloated infra costs, and turned simple deploys into a slog. They ditched it, brought back Docker Compose, and chopped deploy time from 45 minutes to 4. That one change freed up 60+ engineerin.. read more  

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@kala shared a link, 1 month, 2 weeks ago
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8 plots that explain the state of open models

Starting 2026, Chinese companies are dominating the open AI model scene, with Qwen leading in adoption metrics. Despite the rise of new entrants like Z.ai, MiniMax, Kimi Moonshot, and others, Qwen's position seems secure. DeepSeek's large models are showing potential to compete with Qwen, but the Ch.. read more  

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Build an AI-powered website assistant with Amazon Bedrock

AWS spun up a serverless RAG-based support assistant usingAmazon BedrockandBedrock Knowledge Bases. It pulls in docs via a web crawler and S3, then stuffs embeddings intoAmazon OpenSearch Serverless. Access is role-aware, locked down withCognito. Everything spins up clean withAWS CDK... read more  

Build an AI-powered website assistant with Amazon Bedrock
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@kala shared a link, 1 month, 2 weeks ago
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Towards Generalizable and Efficient Large-Scale Generative Recommenders

Authors discuss their approach to scaling generative recommendation models from O(1M) to O(1B) parameters for Netflix tasks, improving training stability, computational efficiency, and evaluation methodology. They address challenges in alignment, cold-start adaptation, and deployment, proposing syst.. read more  

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Agentic AI, MCP, and spec-driven development: Top blog posts of 2025

AI speeds up dev - but it’s a double-edged keyboard. It sneaks in subtle bugs and brittle logic that break under pressure. To keep things sane, teams are fighting back withguardrail patterns,AI-aware linters, andtest suites hardened for hallucinated code... read more  

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@kala shared a link, 1 month, 2 weeks ago
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Where good ideas come from (for coding agents)

A new way to build agents treats prompting ascontext navigation, steering the LLM through ideas like a pilot, not tossing it prompts and hoping for magic. It maps neatly onto Steven Johnson’s seven patterns of innovation. For coding agents to actually pull their weight, users need to bring more than.. read more  

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Weaponizing the AWS CLI for Persistence

Researchers pulled off a slick persistence trick usingAWS CLI aliases. They chained dynamic alias renaming with command execution to swipe credentials, without breaking expected CLI behavior. No red flags. Perfect fit forautomated environmentslike CI/CD pipelines. Backdoors, no AWS CLI tampering req.. read more  

Weaponizing the AWS CLI for Persistence
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Cloud Workload Threats - Runtime Attacks in 2026

Cloud-native breaches keep slipping through the cracks, not because no one’s watching, but because they’re watching the wrong things. Static checks and posture tools can’t catch what happens in motion. That’s where most attacks live now: at runtime. Think app-layer exploits, poisoned dependencies, s.. read more  

Kata Containers is a Cloud Native Computing Foundation (CNCF) project designed to close the security gap between traditional Linux containers and virtual machines. Instead of sharing a single host kernel like standard containers, Kata Containers launches each pod or container inside its own lightweight virtual machine using hardware virtualization.

This approach dramatically reduces the attack surface and prevents container escape vulnerabilities, making Kata ideal for multi-tenant, untrusted, or sensitive workloads. Despite using VMs under the hood, Kata is optimized for fast startup times and integrates seamlessly with Kubernetes through the Container Runtime Interface (CRI), allowing it to be used alongside runtimes like containerd and CRI-O.

Kata Containers is commonly used in scenarios such as multi-tenant Kubernetes clusters, confidential computing, sandboxed AI workloads, serverless platforms, and agent execution environments where strong isolation is mandatory. It supports multiple hypervisors, including QEMU, Firecracker, and Cloud Hypervisor, and continues to evolve toward faster boot times, lower memory overhead, and better hardware acceleration support.