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Accelerate serverless testing with LocalStack integration in VS Code IDE

The AWS Toolkit for VS Code now hooks straight into **LocalStack**. Run full end-to-end tests for **serverless workflows**—Lambda, SQS, EventBridge, the whole crew—without bouncing between tools or writing boilerplate. Just deploy to LocalStack from the IDE using the **AWS SAM CLI**. It feels like .. read more  

Accelerate serverless testing with LocalStack integration in VS Code IDE
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@faun shared a link, 6 months, 4 weeks ago
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Best 20 Linux Commands for Daily Use in Production Servers

A fresh roundup drops20 go-to Linux commandsfor production sysadmins, dialing in on modern defaults likehtop > top,ss > netstat, andip > ifconfig. The shift? Faster tools that actually get updates. Built with systemd in mind, too. Expect the usual suspects—journalctl,rsync,crontab—all still pulling.. read more  

Best 20 Linux Commands for Daily Use in Production Servers
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SLI Evolution Stages

A new SLI evolution model lays out a maturity roadmap—from rebranded latency/error metrics to ones that actually track business impact. It replaces shallow signals and pulls in the stuff that matters: how service failures hit user goals, tasks, and bottom lines... read more  

SLI Evolution Stages
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Introducing Budget Controls for AWS: Automatically Manage Your Cloud Costs

**Budget Controls for AWS** just got better. The open-source tool now reins in more than just EC2. It wrangles **RDS Aurora**, **SageMaker**, and **OpenSearch** too. Under the hood, it taps **AWS Budgets**, **AWS Config**, and **custom tags** to watch spend like a hawk. Hit a budget threshold? It c.. read more  

Introducing Budget Controls for AWS: Automatically Manage Your Cloud Costs
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@faun shared a link, 6 months, 4 weeks ago
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%CPU Utilization Is A Lie

Stress tests on the Ryzen 9 5900X uncovered a big gap between **reported CPU utilization** and what the chip actually pushes. Around 50% on paper? Could mean close to full throttle in reality—thanks to sneaky behaviors from **SMT resource sharing** and **Turbo frequency scaling**. **Takeaway:** Raw.. read more  

%CPU Utilization Is A Lie
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@faun shared a link, 6 months, 4 weeks ago
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Fast, Secure Kubernetes with AKS Automatic

Azure dropped **AKS Automatic**, a new managed Kubernetes tier that tries to do it all—so you don’t have to. It comes with baked-in best practices: autoscaling via HPA, VPA, KEDA, and Karpenter. Automated patching. Node repair. Monitoring. All wired up by default. You still get full access to the .. read more  

Fast, Secure Kubernetes with AKS Automatic
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@faun shared a link, 6 months, 4 weeks ago
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v1.34: Pods Report DRA Resource Health

Kubernetes v1.34 lands with an alpha upgrade to **[KEP-4680](https://github.com/kubernetes/enhancements/tree/master/keps/sig-node/4680-add-resource-health-to-pod-status)**, pushing **Dynamic Resource Allocation (DRA)** into smarter territory: health-aware Pods. DRA drivers can now stream device heal.. read more  

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v1.34: Recovery From Volume Expansion Failure (GA)

Kubernetes v1.34 bumps **automated recovery from botched PVC expansions** to GA. Users can now fix bad volume size requests—no admin, no drama. It cleans up unused quota, slows down retry spam, and surfaces progress with new PVC status fields... read more  

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v1.34: Decoupled Taint Manager Is Now Stable

Kubernetes 1.34 graduates the taint eviction controller to GA. Now, the node lifecycle controller only applies taints, while a dedicated taint eviction controller manages pod eviction. First split in 1.29, now stable in 1.34... read more  

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v1.34: DRA Consumable Capacity

Kubernetes 1.34 rolls in **consumable capacity** for Dynamic Resource Allocation (DRA). That means device plugins can now carve up resources—GPU memory, NIC bandwidth, etc.—into precise slices for Pods, ResourceClaims, and namespaces. The scheduler tracks it all, so nothing spills over... read more  

NanoClaw is an open-source personal AI agent designed to run locally on your machine while remaining small enough to fully understand and audit. Built as a lightweight alternative to larger agent frameworks, the system runs as a single Node.js process with roughly 3,900 lines of code spread across about 15 source files.

The agent integrates with messaging platforms such as WhatsApp and Telegram, allowing users to interact with their AI assistant directly through familiar chat applications. Each conversation group operates independently and maintains its own memory and execution environment.

A core design principle of NanoClaw is security through isolation. Every agent session runs inside its own container using Docker or Apple Container, ensuring that the agent can only access files and resources that are explicitly mounted. This approach relies on operating system–level sandboxing rather than application-level permission checks.

The architecture is intentionally simple: a single orchestrator process manages message queues, schedules tasks, launches containerized agents, and stores state in SQLite. Additional functionality can be added through a modular skills system, allowing users to extend capabilities without increasing the complexity of the core codebase.

By combining a minimal architecture with container-based isolation and messaging integration, NanoClaw aims to provide a transparent, customizable personal AI agent that users can run and control entirely on their own infrastructure.