Manage and Retire EC2 Capacity Reservations for Electronic Design Automation Workloads

By Aditi Singh (Sr. Technical Account Manager) and Aneesh Varghese (Sr. Technical Account Manager)

In Part 1: Plan and create EC2 Capacity Reservations for EDA workloads, you learned how to plan capacity needs for EDA workloads and create On-Demand Capacity Reservations (ODCRs) and Capacity Blocks.

In this post, you will learn how to manage On-Demand Capacity Reservations (ODCRs) as your chip design project progresses, and how to retire them promptly when they are no longer needed. Note: Capacity Blocks are immutable and cannot be modified or cancelled post creation.

Phase 3: Manage

As your EDA project moves through synthesis, place-and-route, and signoff, your capacity needs change. The manage phase covers scaling, redistribution, and optimization of your existing reservations.

Scale up or down

Scale up for tapeout ramp: Modify an existing ODCR for immediate use The following example scales up an existing ODCR to 20 instance:

aws ec2 modify-capacity-reservation \
  --capacity-reservation-id cr-0123456789abcdef0 \
  --instance-count 20

Scale down after tapeout completes: Modify an existing ODCR for immediate use The following example scales down an existing ODCR to 5 instance:

aws ec2 modify-capacity-reservation \
  --capacity-reservation-id cr-0123456789abcdef0 \
  --instance-count 5

Increasing ODCR size is subject to capacity availability. If unused capacity exists in another ODCR you own, moving or splitting that capacity is a better option than requesting additional capacity through a modify operation.

Split capacity across teams

When one design team finishes early and another needs capacity, use the split capability to divide an existing ODCR. The following example splits an existing ODCR owned by you into a new one:

aws ec2 create-capacity-reservation-by-splitting \
  --source-capacity-reservation-id cr-0123456789abcdef0 \
  --instance-count 25 \
  --tag-specifications 'ResourceType=capacity-reservation,Tags=[{Key=Team,Value=AnalogDesign}]'

This creates a new ODCR with 25 instances taken from the source reservation, without requiring new capacity allocation.

Move capacity between reservations

You can redistribute instances between two existing ODCRs:

aws ec2 move-capacity-reservation-instances \
  --source-capacity-reservation-id cr-source123 \
  --destination-capacity-reservation-id cr-dest456 \
  --instance-count 10

Both ODCRs must meet the following requirements: owned by the same account, in the active state, and have matching instance type, instance platform, Availability Zone, tenancy, placement group, and end time. For the complete list of requirements, see Move a Capacity Reservation in the Amazon EC2 documentation.

Moving is preferable to creating new ODCRs when capacity is constrained because it redistributes existing reserved capacity without requiring new allocation.

Share capacity across accounts

Semiconductor companies often use multiple AWS accounts per design team, per project, or per business unit. Use AWS Resource Access Manager (AWS RAM) to share ODCRs across accounts within your AWS Organizations organization.

You can split an ODCR and share the new portion with another account. When sharing ODCRs, be aware of billing behavior: the owner's account pays for the ODCR capacity, and the shared account is billed independently for its usage. Use consolidated billing or explicitly assign billing responsibility to avoid unexpected charges.

Use interruptible Capacity Reservations for off-peak workloads

Interruptible Capacity Reservations let you temporarily share unused ODCR capacity with other workloads in your organization while retaining the ability to reclaim it.

This is useful for EDA environments in several scenarios:

• During off-peak hours your tapeout ODCR sits idle overnight, and regression or ML training jobs can use it until the design team starts their shift.
• Between project phases after synthesis completes but before place-and-route starts, batch DRC jobs can consume the idle capacity.
• For cross-team sharing one design team's idle ODCR can serve another team's burst needs.

For details on reclamation behavior and timing, see Interruptible Capacity Reservations in the Amazon EC2 documentation.

Monitor utilization

Set up monitoring to track ODCR usage and identify optimization opportunities. Use Amazon CloudWatch metrics to track the ratio of used instances to total reserved instances. Create Amazon EventBridge rules to alert when utilization drops below a threshold (for example, below 50 percent for more than 24 hours), which indicates an opportunity to scale down or cancel.

Phase 4: Retire

When a design phase or project completes, retire your Capacity Reservations promptly to stop incurring charges.

Cancel an ODCR

The following example cancels an existing ODCR

aws ec2 cancel-capacity-reservation \
  --capacity-reservation-id cr-0123456789abcdef0

Cancellation is immediate and irreversible, cancellation does not affect the instance state of EC2 instances. Running instances continue running at standard On-Demand rates, or at a discounted rate if you have a matching Savings Plans commitment or Regional Reserved Instance.

Follow these best practices when canceling:

• Drain before canceling. Stop or migrate instances before canceling to avoid unexpected On-Demand charges on instances that were previously covered by Savings Plans matched to the ODCR.
• Update job scheduler configuration. If your IBM Spectrum LSF, PBS Pro, Slurm, or AWS Batch configuration references the ODCR through launch templates or resource definitions, update it before canceling to prevent job launch failures.
• Audit unused ODCRs regularly. Schedule monthly ODCR audits to cancel unused reservations and right-size active ones. An unused ODCR costs the same as running instances.
• Use end dates for project-bound reservations. Instead of relying on manual cancellation, set a specific end date aligned with your project milestone. This prevents forgotten ODCRs from accumulating charges.

Handle Capacity Block expiration

Capacity Blocks cannot be canceled. They expire automatically. Instance termination begins at 11:00 AM UTC on the final day, and the block fully expires at 11:30 AM UTC. Checkpoint ML training jobs and persist results to Amazon S3 or Amazon EBS before the termination window begins.

Common Pitfalls

The following table summarizes common mistakes and how to avoid them.

Pitfall	Impact	Mitigation
Platform mismatch (RHEL vs. Linux/UNIX)	ODCR goes unused while you pay full On-Demand rates	Verify AMI platform with describe-images before creating the ODCR
Accepting ODCR before Savings Plans are active	On-Demand rates apply from the moment of acceptance	Confirm Savings Plans or Reserved Instance commitments are active before the ODCR becomes active
Creating immediate ODCR when pool is exhausted	ODCR creation fails	Use future-dated ODCRs (5–120 days) for constrained instance types
Forgetting to cancel after project ends	Ongoing charges for idle capacity	Set specific end dates and monitor with CloudWatch underutilization alerts
Moving ODCRs with mismatched configurations	Move fails with error	Verify both source and destination ODCRs have matching instance type, platform, AZ, tenancy, placement group, and end time
Shared ODCR billing confusion	Unexpected charges across accounts	Use consolidated billing or explicitly assign billing responsibility when sharing via AWS RAM

EDA-Specific Recommendations

Integrate with your job scheduler

Most EDA environments use a job scheduler. Integrate ODCRs with your scheduler to direct jobs to reserved capacity. For example:

• IBM Spectrum LSF: Use awstemplate resource definitions with capacityReservationTarget to direct jobs to specific ODCRs.
• AWS ParallelCluster: Configure capacity reservation targeting in your cluster configuration to use ODCRs for compute nodes.
• AWS Batch: Use launch template overrides to target ODCRs for specific compute environments.

Plan for tapeout peaks

Tapeout is the most capacity-intensive phase of chip design. Follow these best practices:

• Request capacity 8 or more weeks in advance using future-dated ODCRs.
• Reserve across two Availability Zones so that if one Availability Zone has issues, your tapeout is not blocked.
• Include a 20–30 percent buffer above your estimated peak.
• Set the end date 1–2 weeks after the planned tapeout completion to account for re-spins.
• Monitor utilization daily during tapeout and scale down early if the project finishes ahead of schedule.

Summary

Capacity Reservations ensure availability of compute during critical design milestones, but unused reservations are wasted spend. Treat them as living resources that need active management throughout your design cycle. The key principles are: plan early with appropriate buffers, create reservations that match your workload patterns, monitor and adjust as your project progresses, and cancel promptly when work completes.

If you are just getting started with Capacity Reservations, begin with a single ODCR for your most predictable workload (such as a regression farm) and expand from there. If you already use ODCRs, review your utilization metrics and consider splitting or sharing idle capacity across teams.

Resources

• Amazon EC2 On-Demand Capacity Reservations
• Capacity Blocks for ML
• Capacity Reservations in cluster placement groups
• AWS Resource Access Manager
• Amazon CloudWatch metrics for EC2
• Amazon EventBridge