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@tellsaqib shared a link, 1 month, 1 week ago

How Cloudways is manages its 90K servers fleet using Agentic SRE

Scaling Autonomous Site Reliability Engineering: Architecture, Orchestration, and Validation for a 90,000+ Server Fleet

How Cloudways is manages its 90K servers fleet using Agentic SRE
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@kala shared an update, 1 month, 1 week ago
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Anthropic Asked 81,000 People What They Want From AI. Here's What They Said.

Claude Code Claude

Anthropic's global AI study surveyed 80,508 participants across 159 countries, revealing desires for more personal time and concerns about AI's unreliability and job displacement. Sentiments vary regionally, with lower-income countries seeing AI as an equalizer, while Western Europe and North America focus on governance issues. The study highlights a complex mix of hope and fear regarding AI's impact.

Anthropic Asked 81,000 People What They Want From AI. Here's What They Said.
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@kala added a new tool Claude , 1 month, 1 week ago.
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@varbear shared a link, 1 month, 1 week ago
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How Slack Rebuilt Notifications

At Slack, notifications were redesigned to address the overwhelming noise issue by simplifying choices and improving controls. The legacy system had complex preferences that made it difficult for users to understand and control notifications. Through a collaborative effort, the team refactored prefe.. read more  

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@varbear shared a link, 1 month, 1 week ago
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The Slow Collapse of MkDocs

On March 9, 2026 a former maintainer grabbed the PyPI package forMkDocs. The original author's rights got stripped. Ownership snapped back within six hours. Core development stalled for 18 months.Material for MkDocswent into maintenance. The ecosystem splintered intoProperDocs,MaterialX, andZensical.. read more  

The Slow Collapse of MkDocs
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@varbear shared a link, 1 month, 1 week ago
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How we monitor internal coding agents for misalignment

AI systems are acting with more autonomy in real-world settings, with OpenAI focusing on responsibly navigating this transition to AGI by building capable systems and developing monitoring methods to deploy and manage them safely. OpenAI has implemented a monitoring system for coding agents to learn.. read more  

How we monitor internal coding agents for misalignment
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@varbear shared a link, 1 month, 1 week ago
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Why I Vibe in Go, Not Rust or Python

In a world where the machine writes most of the code, Python lacks solid type enforcement, Rust is overly strict with complex lifetimes, while Go strikes the right balance by catching critical issues without hindering development velocity. The article argues in favor of Go over Python and Rust for A.. read more  

Why I Vibe in Go, Not Rust or Python
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@varbear shared a link, 1 month, 1 week ago
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What if Python was natively distributable?

The Python ecosystem's insistence on solving multiple problems when distributing functions has led to unnecessary complexity. The dominant frameworks have fused orchestration into the execution layer, imposing constraints on function shape, argument serialization, control flow, and error handling. W.. read more  

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@kaptain shared a link, 1 month, 1 week ago
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AWS Load Balancer Controller Reaches GA with Kubernetes Gateway API Support

AWS ships GAGateway APIsupport in theAWS Load Balancer Controller. Teams can manageALBandNLBwith the SIG standard. The controller swaps annotation JSON for validated CRDs -TargetGroupConfiguration,LoadBalancerConfiguration,ListenerRuleConfiguration- and handles L4 (TCP/UDP/TLS) and L7 (HTTP/gRPC). M.. read more  

AWS Load Balancer Controller Reaches GA with Kubernetes Gateway API Support
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@kaptain shared a link, 1 month, 1 week ago
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A one-line Kubernetes fix that saved 600 hours a year

Atlantis, a tool for planning and applying Terraform changes, faced slow restarts of up to 30 minutes due to a safe default in Kubernetes that became a bottleneck as the persistent volume used by Atlantis grew to millions of files. After investigation, a one-line change to fsGroupChangePolicy reduce.. read more  

A one-line Kubernetes fix that saved 600 hours a year
Slurm Workload Manager is an open-source, fault-tolerant, and highly scalable cluster management and scheduling system widely used in high-performance computing (HPC). Designed to operate without kernel modifications, Slurm coordinates thousands of compute nodes by allocating resources, launching and monitoring jobs, and managing contention through its flexible scheduling queue.

At its core, Slurm uses a centralized controller (slurmctld) to track cluster state and assign work, while lightweight daemons (slurmd) on each node execute tasks and communicate hierarchically for fault tolerance. Optional components like slurmdbd and slurmrestd extend Slurm with accounting and REST APIs. A rich set of commands—such as srun, squeue, scancel, and sinfo—gives users and administrators full visibility and control.

Slurm’s modular plugin architecture supports nearly every aspect of cluster operation, including authentication, MPI integration, container runtimes, resource limits, energy accounting, topology-aware scheduling, preemption, and GPU management via Generic Resources (GRES). Nodes are organized into partitions, enabling sophisticated policies for job size, priority, fairness, oversubscription, reservation, and resource exclusivity.

Widely adopted across academia, research labs, and enterprise HPC environments, Slurm serves as the backbone for many of the world’s top supercomputers, offering a battle-tested, flexible, and highly configurable framework for large-scale distributed computing.