Articles about storage, backup, virtualization, technology, innovation, programming, leadership, management,... etc
Articles about storage, backup, virtualization, technology, innovation, programming, leadership, management,... etc
Implementing Just-In-Time (JIT) access for critical IT infrastructure systems is a great strategy for reducing the attack surface, improving security, and ensuring that privileged access is only granted when absolutely necessary. Below are the key steps to implement JIT access: 1. Define Scope and Objectives Identify Critical Systems: Pinpoint the systems requiring JIT access (e.g., […]
Troubleshooting IT infrastructure application compatibility issues requires a systematic approach to identify the root cause and resolve the conflict. Here’s a step-by-step guide tailored for an IT environment that includes datacenters, storage, backup systems, servers, virtualization, operating systems, Kubernetes, AI workloads, GPU graphic cards, and other components: Step 1: Identify the Scope of the Issue […]
Troubleshooting IT infrastructure integration issues can be complex due to the diverse components involved, such as servers, storage systems, virtualization platforms, networks, and applications. Below is a structured approach to help you address integration challenges effectively: 1. Identify the Scope and Impact Understand the problem: Gather detailed information about the issue from users, logs, or […]
Configuring LUN masking and zoning on a Storage Area Network (SAN) is essential for securing and optimizing storage access in your IT infrastructure. Below are the steps to configure LUN masking and zoning effectively: 1. Prerequisites Ensure you have administrative access to your SAN fabric (via the SAN switch management interface) and storage array management […]
Configuring NVIDIA GPU drivers for deep learning workloads on Linux involves several steps to ensure your system is ready for high-performance computations. Here’s a detailed guide: 1. Check GPU Compatibility Verify your NVIDIA GPU model is supported for deep learning workloads by checking compatibility with CUDA and cuDNN libraries on the NVIDIA website. 2. Prepare […]
Scaling GPU resources for AI training involves several considerations, including hardware, software, workload management, and infrastructure planning. Here are the steps to effectively scale GPU resources: 1. Assess Workload Requirements Understand the Model: Determine the size and complexity of the AI model you’re training. Larger models (e.g., transformer-based models like GPT) require more GPU memory […]