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@varbear shared a link, 2 months, 1 week ago
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Using Rust and Postgres for everything: patterns learned over the years

Rust and PostgreSQL are considered the best tools in the software world due to their performance and reliability. Rewriting a backend service from Go to Rust led to significant improvements in processing speed and memory usage. Using sqlx for database operations and leveraging PostgreSQL features li.. read more  

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@kaptain shared a link, 2 months, 1 week ago
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Running Agents on Kubernetes with Agent Sandbox

Agent Sandbox unveils the Sandbox CRD to map long-lived, singleton AI agents onto Kubernetes. It adds stable identity and lifecycle primitives. It supports runtimes like gVisor and Kata Containers. It enables zero-scale resume. It includes SandboxWarmPool with SandboxClaim and SandboxTemplate to kil.. read more  

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@kaptain shared a link, 2 months, 1 week ago
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Securing Production Debugging in Kubernetes

The post prescribes an on-demand SSH gateway pod. It usesshort-lived, identity-bound credentialsandKubernetes RBACto grant scoped, auditable debug sessions. It recommends anaccess brokerthat binds Roles to groups, issues ephemeral certs and OpenSSH user certificates, rotates CAs, enforces command-le.. read more  

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@kaptain shared a link, 2 months, 1 week ago
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The Invisible Rewrite: Modernizing the Image Promoter

SIG Release rewrote theimage promotercore. It cut 20% of the code. It added apipeline engine,cosignsigning, andSLSAattestations. Signing now sits separate fromsignature replication. Registry reads run in parallel - plan time dropped ~20m → ~2m. Per-request timeouts, retries, and HTTP connection reus.. read more  

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@kaptain shared a link, 2 months, 1 week ago
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Kubernetes v1.36 - Sneak Peek

Kubernetes v1.36 (Apr 22, 2026) enablesHPAScaleToZeroby default. That lets theHPAuseminReplicas: 0and read only controller-owned pod metrics. The release swaps long-lived image-pull secrets forephemeral KSA tokens. It deprecatesIPVS, retiresIngress NGINX, and aligns withcontainerd 2.x. The release f.. read more  

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@kala shared a link, 2 months, 1 week ago
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OpenClaw is a great movement, but dead product. what's next?

After talking to 50+ individuals experimenting with OpenClaw, it's clear that while many have tried it and even explored it for more than 3 days, only around 10% have attempted automating real actions. However, most struggle to maintain these automations at a production level due to challenges with .. read more  

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@kala shared a link, 2 months, 1 week ago
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OpenClaw Tutorial: AI Stock Agent with Exa and Milvus

An autonomous market agent ships. OpenClaw handles orchestration. Exa returns structured, semantic web results. Milvus (or Zilliz Cloud) stores vectorized trade memory. A 30‑minute Heartbeat keeps it running. Custom Skills load on demand. Recalls query 1536‑dim embeddings. Entire stack runs for abou.. read more  

OpenClaw Tutorial: AI Stock Agent with Exa and Milvus
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@kala shared a link, 2 months, 1 week ago
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Scaling Karpathy's Autoresearch: What Happens When the Agent Gets a GPU Cluster

A team pointedClaude Codeatautoresearchand spun up 16 Kubernetes GPUs. The setup ran ~910 experiments in 8 hours.val_bpbdropped from 1.003 to 0.974 (2.87%). Throughput climbed ~9×. Parallel factorial waves revealedAR=96as the best width. The pipeline usedH100for cheap screening andH200for validation.. read more  

Scaling Karpathy's Autoresearch: What Happens When the Agent Gets a GPU Cluster
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@kala shared a link, 2 months, 1 week ago
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OpenAI to acquire Astral

OpenAI will acquire Astral, pending regulatory close. It will fold Astral's open-source Python tools —uv,Ruff, andty— intoCodex. Teams will integrate the tools.Codexwill plan changes, modify codebases, run linters and formatters, and verify results acrossPythonworkflows. System shift:This injects pr.. read more  

OpenAI to acquire Astral
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@kala shared a link, 2 months, 1 week ago
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Building AI Teams with Sandboxes & Agent

Docker Agentruns teams of specialized AI agents. The agents split work: design, code, test, fix. Models and toolsets are configurable. Docker Sandboxesisolate each agent in a per-workspacemicroVM. The sandbox mounts the host project path, strips host env vars, and limits network access. Tooling move.. read more  

Building AI Teams with Sandboxes & Agent
AWX is the open source, community supported upstream project for Red Hat Ansible Automation Platform, formerly known as Ansible Tower. It gives teams a web based interface, a full REST API, and a distributed task engine on top of Ansible, turning command line playbook runs into a managed, auditable automation service.

The project began at AnsibleWorks as the commercial Ansible Tower product, and after Red Hat acquired Ansible, it open sourced the codebase as AWX in September 2017, positioning it as the development ground where new features land before they are hardened into the supported Automation Platform controller. With AWX, you organize automation around projects (synced from Git or other source control), inventories (static or dynamically pulled from cloud providers), credentials (stored encrypted and injected at runtime), and job templates that tie a playbook to its inventory and credentials. On top of that, it adds role based access control, a visual dashboard, job scheduling, workflow chaining, webhooks, and real time job output, so multiple teams can run, track, and delegate automation without sharing SSH keys or sitting at a terminal.

Modern AWX runs on Kubernetes or OpenShift through the AWX Operator, which manages installation, upgrades, and scaling declaratively, reflecting its shift from a single host application to a cloud native, container based platform. Because it is the upstream of a paid product, AWX moves fast and ships frequently, which makes it ideal for labs, learning, and self managed deployments, though teams needing formal support and long term stability typically run the downstream Automation Platform instead.