What’s actually slowing this PC down?
Pick the symptom - the matching free tool is one click away.
Amazon Omics is now documented by AWS as AWS HealthOmics, a managed platform for running bioinformatics workflows, storing genomic data and supporting genomic analysis. AWS says it supports WDL, Nextflow and CWL workflows and can scale across more than 100,000 concurrent vCPUs; those are AWS-stated capabilities, not independent benchmark results.
What AWS HealthOmics does
HealthOmics brings together three service areas: Workflows for bioinformatics computation, Storage for sequence and reference data, and Analytics for preparing genomic variant and annotation data for querying and cohort analysis. AWS describes the service as HIPAA-eligible and intended to accelerate clinical diagnostic testing, drug discovery and agriculture research.
The name reflects a shift from the original Amazon Omics launch description, which presented the service as a way to store, query and analyze genomic, transcriptomic and other omics data. The current AWS documentation calls it AWS HealthOmics.
Workflows
Workflows run bioinformatics pipelines written in WDL, Nextflow or CWL. HealthOmics manages the infrastructure for workflow runs, including provisioning and scaling resources. A run is one invocation of a workflow; its tasks are the individual processes carried out during that invocation.
#1 Best Overall
Storage
Sequence stores hold read sets such as FASTQ, BAM and CRAM files. Reference stores hold genome references. The service also works alongside AWS services including S3 and ECR, so data and container images can fit into a broader AWS-based workflow.
Analytics
Analytics is designed to prepare genomic variant and annotation data for queries and cohort analysis. AWS also describes integrations with Lake Formation, Athena and SageMaker. However, new customers cannot currently use HealthOmics variant stores or annotation stores; the availability restriction is described below.
How HealthOmics scales workflow runs
AWS says HealthOmics can support more than 100,000 concurrent vCPUs and tens of thousands of tests per day. These are vendor-stated capabilities, not independently verified throughput guarantees; actual capacity and performance can depend on workflow design, resource needs and account limits.
Automatic provisioning and scaling reduce the need to manage the underlying compute infrastructure for each run. For operational control, run groups can set limits on concurrent runs, vCPUs and run duration. Service quotas also shape the resources an account can use.
Rank #3
Run groups and quotas
Use run groups to place practical caps around workload execution—for example, to limit how many runs execute at once or how much CPU capacity a group can consume. Quotas provide another control on service use. These mechanisms help manage resource consumption; they do not replace workflow-level optimization.
How to optimize cost and performance
AWS recommends starting with task-level evidence rather than tuning a whole pipeline by guesswork. Run Analyzer extracts resource-usage information for workflow tasks, which can reveal opportunities to adjust resource requests or identify bottlenecks.
Rank #4
- Review task usage with Run Analyzer. Look for tasks whose requested resources do not match their observed needs, then validate changes against representative runs.
- Choose run storage for the workload. Dynamic storage provisions faster and adjusts to run needs, making it useful for development and troubleshooting. Static storage takes longer to provision but may be faster for some high-concurrency or high-I/O production runs, particularly when more than 9.6 TiB of capacity is needed.
- Reduce container image size. Smaller images can reduce the amount of data that must be handled when a workflow starts.
- Parameterize container images. Making container-image choices configurable can help adapt a workflow without unnecessarily duplicating pipeline definitions.
- Use run groups and quotas. Set concurrency and resource boundaries that fit operational and budget requirements.
- Tag runs and monitor them. Tags support cost tracking, while CloudWatch logs and EventBridge alerts can help with operational visibility.
- Reassess periodically. Rerun analysis when workflows change or sample variability shifts, since earlier resource assumptions may no longer fit.
Dynamic and static run storage compared
| Storage type | Provisioning | Where it may fit | Trade-off |
|---|---|---|---|
| Dynamic | Provisions faster and scales with run needs. | Development and troubleshooting. | May not be the fastest choice for some high-concurrency or high-I/O production workloads. |
| Static | Takes longer to provision. | Some high-concurrency or high-I/O production runs, especially when capacity above 9.6 TiB is needed. | Provisioning takes longer; the performance advantage applies to some workloads, not every run. |
How HealthOmics pricing works
HealthOmics pricing has separate dimensions rather than one universal rate. Private workflows are charged according to requested compute and file-system resources, while Ready2Run workflows have a fixed price per run. Sequence and reference storage, as well as variant and annotation stores, have their own pricing models. The applicable rates depend on the service and usage; the pricing information summarized here does not establish a single total cost for a project.
Free-tier allowance
AWS’s current pricing information states that the first two months include the following free-tier usage allowances. Restrictions apply, and unused usage does not roll over.
Recommended Free Tools
Best Value
| Usage category | First-two-month allowance stated by AWS |
|---|---|
| Workflow compute | 275 omics.m.xlarge-equivalent instance hours |
| Run storage | 49,000 GB-hours |
| Active sequence storage | 1,500 gigabase-months |
| Archive sequence storage | 1,500 gigabase-months |
| Variant storage | 200 GB-months |
These are usage allowances, not cash credits or a promise that every workflow is free during its first two months. Check the current AWS pricing terms and the account’s eligibility before estimating spend, particularly because new-customer access to variant and annotation stores is restricted.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Can new customers use HealthOmics variant stores?
No. AWS currently states that HealthOmics variant stores and annotation stores are no longer open to new customers. Existing customers can continue using the service as normal. Since product availability can change, confirm the current AWS service notice before planning a new implementation that depends on either store.
This restriction applies to those analytics stores; it does not mean that the entire HealthOmics service is unavailable to new customers. Workflows and sequence/reference storage are separate service components, though specific access and capacity can still depend on AWS account and service conditions.
What to evaluate before adopting HealthOmics
For a real deployment, compare platforms against the workflow and governance needs of the project rather than concurrency claims alone. Useful evaluation criteria include:
Quick wins for a faster PC:
Fix the driver behind crashes, sound loss and screen glitchesFind Drivers →Clear out junk files and repair common Windows errorsFree Scan →Quick Recap
- Whether the required workflows are supported in WDL, Nextflow or CWL, and how much pipeline adaptation is needed.
- How much infrastructure the service manages versus what the team must configure and operate.
- How concurrency, quotas and throughput limits apply to the target account.
- Whether genomic data storage tiers and data organization fit the workload.
- How governance, access controls and auditing will work in the intended AWS environment.
- How the needed components integrate with S3, Athena, Lake Formation and SageMaker.
- Whether required variant or annotation analytics are available to the target account.
- How compute, run-storage and genomic-storage charges combine for representative workloads.
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
