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When should you use Runtime Instances instead of microVMs?
Choose Instances when an agent workflow needs a GPU, must run for an extended period, benefits from agents sharing a workspace, or needs configured EBS storage to retain files between compute instances. Choose the default microVM compute type for lightweight, API-driven agents that complete quickly. AWS describes Instances as EC2 managed infrastructure provisioned and operated in your AWS account, while microVMs use a serverless, consumption-based model. Amazon Bedrock AgentCore Instances documentation and AgentCore compute-type documentation explain the distinction.
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| Decision point | Instances | microVMs |
|---|---|---|
| Typical workload | Long-running, stateful, collaborative, or GPU-based agents | Lightweight, API-driven agents that finish quickly |
| Maximum documented session runtime | Up to 14 days | Up to 8 hours |
| GPU | Supported GPU families can be selected through a capacity provider | GPU is not supported |
| Agents sharing a session | Multiple agents can share an instance | One runtime hosts one agent |
| Infrastructure and billing model | EC2 instances are managed in your AWS account; applicable EC2 pricing mechanisms may be used | AgentCore consumption-based serverless model |
| Persistent filesystem | Configured capacity-provider EBS volumes can survive an instance stop until session deletion | Separate microVM storage options apply; check their current lifecycle and availability in the filesystem guide |
Instances do not make every agent faster by default. The official documentation describes supported hardware and workload categories, but provides no independent benchmark or comparative performance figures. Match the compute type to the workload rather than treating GPU availability or EC2 as a general performance guarantee.
Can multiple agents share one GPU instance?
Yes. The documented colocation mechanism is to configure the runtimes with the same capacity provider and invoke them using the same runtimeSessionId. AgentCore places those agents on the same EC2 instance. They share the instance filesystem and access to its GPUs, so this is shared infrastructure—not a dedicated GPU allocation for each agent. Plan for shared-resource coordination and avoid assuming that each agent receives an isolated GPU or filesystem.
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A capacity provider is also where you select the supported compute configuration. AWS lists NVIDIA families g4dn, g5, g6, g6e, gr6, g6f, gr6f, and g7e, plus AWS Inferentia2-powered inf2. The documentation identifies use cases including model inference, 3D rendering, and media processing, and says AgentCore provisions GPU drivers so standard container images can be used without bundling drivers. These families indicate supported options, not relative performance or availability in every AWS Region; verify the current list and regional availability when configuring a deployment. AWS’s Instances guide has the current service details.
Does session state survive when an instance stops?
A session and the EC2 instance currently serving it have related but distinct lifetimes. Instances sessions can run for up to 14 days. Lifecycle configuration controls idle timeout and maximum instance lifetime; the documented upper limit for Instances is 1,209,600 seconds. When an instance stops or reaches its lifetime limit, a later invocation using the same session ID can provision replacement compute and reattach the session’s persistent storage. The session can therefore continue across instances, but files survive only if they were stored on configured persistent volumes.
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Persistent EBS volumes
A capacity provider can define persistent EBS volumes. AgentCore creates these in your AWS account and mounts them into the agent, allowing workspace files, caches, and checkpoints to remain after an instance stops. Deleting the session also deletes its persistent volumes, so session deletion is a data-lifecycle event: copy anything you need to retain elsewhere first. AWS’s Runtime Instances data guide describes storage behavior.
Temporary storage
Root and ephemeral volumes are temporary and disappear when the instance terminates. Do not rely on them for files that must be available after a stop or replacement. Store durable workspace artifacts on the configured persistent volume, and keep a separate backup if they must outlive the session itself.
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Is persistent workspace storage the same as agent memory?
No. EBS-backed volumes preserve filesystem data such as files and checkpoints; they do not, by themselves, provide conversational recall. AgentCore Memory is a separate capability for retaining selected conversational insights across sessions. Likewise, EFS or S3 Files mounts and microVM session storage are distinct storage options with their own sharing behavior, availability, and networking requirements. Check the current filesystem guide before choosing among them rather than treating all AgentCore storage as interchangeable. AWS’s AgentCore filesystem configuration guide and AgentCore Memory guide describe these separate capabilities.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What should you check before deploying?
- Region and GPU family: Confirm the desired instance family is currently available for AgentCore in your target Region. The supported-family list is not a region-by-region availability guarantee.
- Session and lifecycle settings: Set idle timeout and maximum instance lifetime around the workflow, and ensure callers reuse the intended
runtimeSessionIdwhen continuity or colocation is required. - Storage lifecycle: Identify which data belongs on persistent EBS, which can be temporary, and what must be copied before session deletion.
- Networking and access: Review the capacity provider, VPC networking, IAM roles, and any mounted storage requirements for the workload.
- Cost assumptions: Instances run EC2 infrastructure in your AWS account, but no defensible cost estimate is possible without the instance type, Region, storage, and runtime duration. Check the applicable EC2 pricing and billing details for your configuration; microVMs follow a different consumption-based model.
AWS manages provisioning, patching, scaling, and teardown of Runtime Instances, while the infrastructure is provisioned in your account. For the current service model and lifecycle settings, see the Instances guide and lifecycle configuration documentation.
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