As IT infrastructures grow more complex and resource-intensive, achieving efficient workload distribution across a large-scale environment becomes increasingly important. That’s where OpenNebula’s new AI-powered Distributed Resource Scheduler (OneDRS) comes into play—bringing intelligent automation and predictive optimization to help cloud administrators get the most out of their clusters.

With OneDRS, workloads are no longer assigned arbitrarily or managed manually. Instead, you can rely on data-driven recommendations—powered by resource usage forecasting—to make smarter scheduling decisions, improve host utilization, and support both real-time and long-term capacity planning.

AI-Driven Scheduling with OneDRS

OpenNebula DRS introduces a set of advanced features to streamline resource management:

• Cluster Load Balancing. Automatically distributes workloads to avoid overloading specific hosts.
• Initial VM Placement. Ensures virtual machines are deployed on the most suitable host from the start.
• Migration Plans. Provides actionable migration recommendations, either fully automated or manually approved.
• Forecast-Enhanced Decisions. Uses historical and predictive metrics to make smarter placement and migration choices.
• Custom Automation Levels. Supports manual, partial, and fully automated operation modes based on your policy preferences.

These capabilities turn the guessing game of VM management into a policy-driven, intelligent scheduling process.

How Forecasting Enhances OneDRS

The AI-based forecasting component adds another layer of intelligence to the DRS engine. Instead of basing decisions solely on current metrics, OpenNebula can factor in future predictions for CPU, memory, disk, and network usage.

• Anticipate bottlenecks before they occur
• Make smarter, data-driven infrastructure decisions
• Optimize both short-term actions and long-term planning

Administrators can configure the predictive influence using a simple slider—e.g., 30% predictive input means decisions are based on 70% real-time data and 30% forecasted metrics. More historical data leads to more accurate predictions, and you can even visualize forecast graphs directly within the Sunstone interface.

Step-by-Step Optimization in Action

We’ve prepared a demonstration of DRS in action on a 4-host OpenNebula cluster running 8 virtual machines. Key steps include:

• Deployment Using Packing Policy. Initially, VMs are densely placed on the same host using a “Pack” policy to minimize host usage.
• Manual Optimization with Balance Policy. Switching to the “Balance” policy spreads VMs evenly across hosts based on CPU metrics. The optimization is triggered manually and applied with a single click.
• Automated Repack with Threshold. The demo then sets a migration threshold of two VMs and reverts to the “Pack” policy. With full automation enabled, OpenNebula migrates only two VMs per optimization cycle to consolidate workloads again.

Throughout, the demo highlights how to configure each OneDRS setting—including the migration threshold, predictive forecasting level, policy type (Pack vs. Balance), and automation mode—directly from the Sunstone UI or by editing config files like /etc/one/oned.conf and /etc/one/one_drs.conf.

Scaling Up: Large-Scale Optimization Test

To demonstrate OneDRS at scale, the screencast wraps up with a test involving 1,000 hosts and thousands of VMs. In this scenario, the environment initially suffers from uneven load distribution. By enabling DRS in manual mode with the “Balance” policy, the tool generates a detailed migration plan to redistribute workloads across the infrastructure.

Once applied, the plan successfully balances VM distribution, maximizing the use of all available resources—even in a highly complex, large-scale environment.

Watch the Full Demo: AI-Powered OneDRS in Action

The full screencast walks you through each configuration step and showcases real-time workload migrations, predictive planning, and policy tuning—all within OpenNebula’s user-friendly Sunstone interface.

In this demo, you’ll see how to:

• Deploy and configure OneDRS on a 4-host cluster
• Set up policies and automation modes for workload optimization
• Use predictive scheduling to enhance placement decisions
• Visualize historical vs. forecasted metrics for hosts and VMs
• Scale optimization across a massive 1,000-host environment.

This screencast demonstrates OpenNebula’s growing capabilities in intelligent cloud automation and scalable infrastructure optimization.

To learn more, click here.

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