Articles about storage, backup, virtualization, technology, innovation, programming, leadership, management,... etc
Articles about storage, backup, virtualization, technology, innovation, programming, leadership, management,... etc
Configuring your IT infrastructure to support hybrid AI/ML workloads is a critical task that requires careful planning, the right technologies, and a scalable architecture. A hybrid AI/ML workload refers to workloads that may run across both on-premises infrastructure and public cloud environments. Below are the key steps to achieve this: 1. Assess Your Requirements Workload […]
Setting up automatic backups for your servers is critical to ensure data protection and disaster recovery. Below is a step-by-step process for implementing automatic backups: Step 1: Define Backup Requirements Understand What to Backup: Decide which data, applications, databases, and system configurations are critical. Prioritize files, application data, OS configurations, virtual machines, and databases. Define […]
Configuring GPU passthrough for virtual machines (VMs) allows you to dedicate a physical GPU to a VM, enabling high-performance workloads like AI, machine learning, video rendering, or gaming. Here’s a step-by-step guide to configure GPU passthrough, applicable to popular hypervisors such as VMware ESXi, Proxmox VE, or KVM/QEMU. Prerequisites: Hardware Requirements: A CPU and motherboard […]
Securing IT infrastructure for edge computing is critical as edge environments are often more vulnerable due to their distributed nature, limited physical security, and diverse endpoints. Below are best practices and strategies to secure your edge computing infrastructure: 1. Implement Strong Network Security Secure Communication Channels: Use VPNs, TLS encryption, or IPsec to secure communication […]
Optimizing IT infrastructure for real-time analytics requires a strategic approach that ensures high performance, scalability, reliability, and efficiency. Below are key steps and considerations to help you achieve this: 1. Assess Requirements Understand Data Ingest Rates: Determine the volume, velocity, and variety of data being generated. Define Latency Tolerance: Identify acceptable latency thresholds for real-time […]
Implementing IT infrastructure for AI/ML pipelines involves designing and deploying a robust, scalable, secure, and efficient environment to support data processing, model training, inference, and storage needs. Here’s a step-by-step guide tailored for your role: 1. Assess Business Requirements Understand AI/ML use cases: Identify the goals, datasets, and expected workloads (e.g., training, inference, batch processing, […]