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@laura_garcia shared a post, 9 hours ago

Software Developer, RELIANOID

🔐 RELIANOID Load Balancer – Security Contributions

At RELIANOID, we actively and selflessly contribute to improving global cybersecurity, staying true to our open-source spirit. 🤝 We maintain close collaborations with security platforms, forums, and threat-intelligence communities, sharing our expertise to help strengthen protection across the Inter..

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@tiennm99 started using tool Java , 12 hours, 36 minutes ago.

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@tiennm99 started using tool Go , 12 hours, 36 minutes ago.

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@laura_garcia shared a post, 1 day, 8 hours ago

Software Developer, RELIANOID

📍 RELIANOID at Bett UK 2026

We’re excited to take part in Bett UK 2026, the world’s leading EdTech event, bringing together educators, innovators, and decision-makers shaping the future of education. 🗓 January 21–23, 2026 📍 London, United Kingdom Join us to discover how RELIANOID enables secure, scalable, and highly available ..

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@nagarjun-avala started using tool Kubernetes , 1 day, 19 hours ago.

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@nagarjun-avala started using tool GitHub Actions , 1 day, 19 hours ago.

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@nagarjun-avala started using tool Docker , 1 day, 19 hours ago.

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@laura_garcia shared a post, 2 days, 8 hours ago

Software Developer, RELIANOID

🚀 If you’re building AI systems, reliability is no longer optional

Many teams are rushing to adopt AI, but few are asking the most critical question: 👉 What happens when AI fails? Back in December, we published an article that remains more relevant than ever: AI is redefining Site Reliability Engineering (SRE). Why? Because AI inference workloads introduce new reli..

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@aleonrangel gave 🐾 to Difference between Agile and Scrum , 3 days ago.

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@aleonrangel gave 🐾 to Difference between Agile and Scrum , 3 days ago.

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.

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