Unleash the full potential of Linux with a high-memory, agile virtual environment.
This, optimized Ubuntu Virtual Machine is designed for developers, data analysts, and IT professionals who need significant RAM for in-memory processing but require a compact, efficient storage footprint. Pre-configured with 16GB of dedicated RAM, this VM handles heavy multitasking, large database queries, and complex compilation tasks without breaking a sweat, while the 32GB storage keeps the footprint lean.
Core Features
16GB Dedicated RAM: Experience exceptional responsiveness. Ideal for running heavy IDEs (IntelliJ, VS Code), browser-based testing, simulation tools, and Docker containers simultaneously without using slow swap space.
Optimized 32GB Virtual Disk: Pre-installed Ubuntu Desktop/Server, providing ample room for system files, essential development tools, and project files while staying lightweight.
High-Performance Setup: Pre-configured for rapid booting and smooth GUI performance, utilizing virtualization technology to ensure native-like speed.
Ready-to-Use: Save hours of setup time. This VM comes with Ubuntu pre-installed, updated, and configured for immediate deployment.
Ideal Use Cases
Web & Software Development: Ideal for running heavy localized development environments, microservices, and databases.
Data Science & Analysis: Run large datasets in memory (Pandas/Python) without running out of RAM.
Docker & Containerization: Enough memory to host multiple containers for microservices development.
Linux Training & DevOps: A safe, isolated sandbox for experimenting with server configurations, scripting, and shell commands.
Ubuntu Latest LTS (Desktop or Server)
16 GB DDR4 Equivalent (Allocated)
32 GB Virtual Disk (Dynamically Allocated)
Why 16GB RAM / 32GB HDD?
This configuration is specifically chosen for in-memory tasks. Because 16GB is more than enough for most Linux operations, you reduce disk I/O (swapping), making the 32GB disk perform faster than a lower-RAM system. It is perfect for applications that live in RAM rather than needing massive local storage.