Agentic AI systems are evolving beyond simple question and answer interactions. Modern AI agents can execute code, process files, query databases, interact with application programming interfaces (APIs) and perform multi-step workflows on behalf of users. While these capabilities unlock new levels of automation, they also introduce new infrastructure and security requirements. Executing agent-generated code directly on a host system can expose organizations to software bugs, prompt-injection attacks, data leakage, or privilege-escalation risks.

To address these challenges, agentic AI frameworks rely on isolated execution environments, commonly referred to as sandboxes. As AI agent adoption grows, sandboxing becomes more than a security feature. Agents frequently create, use, and destroy execution environments within seconds, making sandbox provisioning efficiency a key component of overall responsiveness and scalability. The ability to combine strong isolation with rapid provisioning is becoming increasingly important for large-scale agentic AI deployments.

Sandboxing: A Core Component of Agentic AI

Several sandboxing approaches are commonly used today, including virtual machines, containers, microVMs, and the open-source Tencent Cloud Cube Sandbox. While these technologies provide stronger security and isolation, they also require infrastructure to efficiently provision and manage isolated execution environments at scale.

The Sandbox Lifecycle

In a typical agentic AI deployment, sandbox creation sits directly on the critical path of task execution. Before an agent can run code or invoke tools, a sandbox must first be provisioned, initialized, and made available for use.

A simplified execution flow is shown below:

Agent request → Sandbox creation → Task execution → Result return → Sandbox teardown

In large-scale agent deployments, sandbox creation and teardown occur continuously as workflows execute. The efficiency of this lifecycle can have a direct impact on application responsiveness, infrastructure utilization, and overall throughput.

Evaluating Sandbox Provisioning Performance

To evaluate sandbox provisioning performance under realistic operating conditions, Intel used the cube-bench create/delete workload, which measures how efficiently a platform can provide new sandbox environments.

The workload continuously issues sandbox creation requests through the CubeSandbox API while increasing aggregate concurrency. This approach assesses how effectively a platform can sustain provisioning demand as the number of concurrent sandbox requests grows.

A key metric in this evaluation is the 200-millisecond sandbox creation service-level agreement (SLA), which represents the target responsiveness threshold for delivering a usable sandbox environment. Average create-latency, along with throughput and tail-latency metrics, provides insight into how effectively a platform maintains responsiveness under increasing load.

Intel Xeon Processors Delivers Greater Provisioning Scalability than AMD EPYC Processors

Figure 1 below shows average sandbox creation latency as concurrency increases from 100 to 350 concurrent provisioning requests. While all platforms exhibit increasing latency under heavier load, platforms based on Intel^® Xeon^® processors maintain lower creation latency and sustain higher provisioning concurrency within the target 200-millisecond service-level objective. The Intel^® Xeon^® 6990E+ processor remains below the 200-millisecond SLA until approximately 313 concurrent provisioning requests. The Intel^® Xeon^® 6980P processor remains below the same threshold until 277 concurrent requests. In comparison, the AMD EPYC™ 9965 processor crosses the 200-millisecond threshold at approximately 246 concurrent requests. Compared with the AMD EPYC 9965, Intel Xeon 6990E+ processor supports roughly 27% higher provisioning concurrency within the 200-millisecond SLA, while Intel Xeon 6980P processor supports approximately 12% higher concurrency.

As provisioning demand increases, both Intel processor-based platforms continue to deliver strong scalability and predictable latency behavior. The platform based on the Intel Xeon 6990E+ processor provides the highest concurrency within the 200-millisecond target. The platform based on the Intel Xeon 6980P processor also maintains the SLA at substantially higher provisioning levels than AMD EPYC 9965 processor. These results demonstrate the ability of Intel Xeon platforms to sustain higher sandbox provisioning rates while maintaining responsive and consistent service-level performance underload.