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This product has charges associated with it for the FerroAir software, in addition to the underlying AWS infrastructure costs. FerroAir is a self-managed workflow orchestrator you run on your own Amazon EC2 instances: a single static Rust binary that implements an Apache Airflow 3.x scheduler, webserver, REST API v2, triggerer, and DAG processor. It is wire-compatible with the Apache Airflow 3.0/3.1/3.2 REST API v2 surface and the Apache Airflow AIP-72 task-execution interface. It serves a web UI on port 8080, a metrics and admin port 9080, and AIP-72 on port 8081. It syncs DAGs from Amazon S3, stores metadata in PostgreSQL or SQLite, runs an HA scheduler with leader election, and supports Kubernetes and Celery executors. See the product documentation for benchmark methodology and figures. Ships as an Amazon Linux 2023 AMI, billed per instance per hour with an annual option.
Overview
FerroAir is a self-managed workflow orchestrator that runs Apache Airflow 3.x workloads on your own Amazon EC2 instances. It is a single static Rust binary that implements an Apache Airflow 3.x scheduler, webserver, REST API v2, triggerer, and DAG processor. Task bodies keep executing on CPython through the upstream airflow.sdk over the Apache Airflow AIP-72 task-execution interface, while FerroAir owns the scheduler tick loop, DAG-folder watcher, REST API, metadata access, leader election, and executor dispatch in Rust. Apache Airflow is an open-source project (it is not an AWS service); FerroAir is wire-compatible with the Apache Airflow 3.0, 3.1, and 3.2 REST API v2 surface and the Apache Airflow AIP-72 task-execution interface.
A real, served interface. FerroAir serves a genuine web UI (a Leptos single-page application, no Node runtime) on port 8080 with the DAG list, graph, grid, gantt, calendar, and task-log views. A dedicated metrics and admin port 9080 exposes Prometheus metrics and the health, live, and ready probes, kept separate from the user-facing UI port. The Apache Airflow AIP-72 task-execution interface is served on port 8081 for the Python worker. The Apache Airflow REST API v2 surface is implemented so existing Apache Airflow REST API v2 clients are supported; see the product documentation for the compatibility matrix.
Operationally lean. The scheduler, webserver, triggerer, and DAG processor run unified in one static binary under a hardened systemd unit, instead of a multi-process Python deployment. For resource-footprint and latency figures (scheduler resident memory, scheduler tick, and DAG parse), see the product documentation for benchmark methodology and figures; those are local developer-workstation measurements, not a performance guarantee for any instance type, and Graviton (arm64) numbers are being re-measured.
State and storage. DAG files sync from an Amazon S3 bucket (or local disk). Metadata is stored in PostgreSQL or SQLite using an Apache Airflow 3 Alembic-compatible schema, so the metadata mount mode stays viable for import. The HA scheduler uses scheduler failover via leader election (openraft); for higher availability run several instances and let leader election promote a standby (see the product documentation for benchmark methodology and figures). Executors include the in-process local executor, a Kubernetes executor (kube-rs), and a Celery executor (Redis or RabbitMQ broker).
Bring your existing workflows across. FerroAir can import connections, variables, and pools from an existing managed Apache Airflow deployment and sync your DAG folder, so teams already running Apache Airflow elsewhere can move their orchestration layer. The post-purchase documentation on the AMI walks through the import tool, the runbook, the compatibility matrix, and validation.
Secrets and integration. Secrets resolve from environment, AWS Secrets Manager, GCP Secret Manager, Azure Key Vault, or Vault. Connections and variables are encrypted (Fernet). Task logs can be written to local disk, Amazon S3, GCS, Azure, or Amazon CloudWatch Logs. Authentication supports FAB auth, OAuth, OIDC, SAML, and LDAP.
No lock-in and no phone-home. FerroAir is a normal Amazon Linux 2023 AMI you run in your own VPC. There is no separate control plane, no telemetry home-call, and no license-key check - billing is AMI hourly plus an annual contract option through your AWS bill. Deploy with the included CloudFormation template and point your DAG bucket and metadata database at the instance.
Highlights
- Single static Rust binary that implements an Apache Airflow 3.x scheduler, webserver, REST API v2, triggerer, and DAG processor; wire-compatible with the Apache Airflow 3.0/3.1/3.2 REST API v2 surface and the Apache Airflow AIP-72 task-execution interface. A served web UI on port 8080, a dedicated metrics and admin port 9080 (Prometheus plus health, live, and ready probes), and AIP-72 on port 8081.
- Operationally lean and self-managed in your own VPC: the scheduler, webserver, triggerer, and DAG processor run unified in one binary under a hardened systemd unit. For resource-footprint and latency figures, see the product documentation for benchmark methodology and figures (local developer-workstation measurements, not a performance guarantee for any instance type; Graviton numbers are being re-measured).
- Production wiring built in: Amazon S3 DAG sync, PostgreSQL or SQLite metadata (Apache Airflow 3 Alembic-compatible schema), an HA scheduler with leader-election failover, and Kubernetes plus Celery executors. Import connections, variables, and pools from an existing managed Apache Airflow deployment. No separate control plane, no telemetry home-call, no license-key check - billed per instance per hour through your AWS bill with an annual option.
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Delivery method
Delivery option
CloudFormation Quick Launch
64-bit (x86) Amazon Machine Image (AMI)
Latest version
Operating system
AmazonLinux 2023
Deployed on AWS
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Dimension | Description | Cost/hour |
|---|---|---|
c7i.large Recommended | FerroAir hourly software fee for instance type c7i.large | $0.20 |
c7i.xlarge | FerroAir hourly software fee for instance type c7i.xlarge | $0.20 |
c7i.2xlarge | FerroAir hourly software fee for instance type c7i.2xlarge | $0.20 |
c7i.4xlarge | FerroAir hourly software fee for instance type c7i.4xlarge | $0.20 |
m7i.large | FerroAir hourly software fee for instance type m7i.large | $0.20 |
m7i.xlarge | FerroAir hourly software fee for instance type m7i.xlarge | $0.20 |
m7i.2xlarge | FerroAir hourly software fee for instance type m7i.2xlarge | $0.20 |
m7i.4xlarge | FerroAir hourly software fee for instance type m7i.4xlarge | $0.20 |
c6i.large | c6i.large | $0.20 |
c6i.xlarge | c6i.xlarge | $0.20 |
Dimensions summary
You pay an hourly software fee per running instance, with no license keys. The 16 dimensions map to specific EC2 instance types you choose to run this orchestrator on. They fall into two compute families: c-class (compute-optimized) and m-class (general-purpose), across two generations (6i and 7i). Within each family, the size steps from large through xlarge, 2xlarge, and 4xlarge, so the fee scales with the instance capacity you select. Larger sizes carry higher hourly fees. You add your own EC2 charge on top. An annual billing option is also available.
Top-of-mind questions for buyers
The software fee is billed per instance per hour of runtime. A fully stopped instance stops accruing the hourly software fee. Stopped instances may still incur AWS storage charges for their attached volumes, but the software metering counts running time only.
Each unit is one running EC2 instance of the type you launch, billed per hour. You can run several instances at once; the high-availability scheduler uses leader election so a standby is promoted on failover. Each running instance accrues its own hourly fee.
The hourly option meters actual instance-hours with no upfront commitment, so it suits variable or short-lived workloads. The annual option is a flat term-based fee for continuous, always-on orchestration. Both bill through your AWS invoice, and your own EC2 compute charge is separate in either case.
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Delivery details
64-bit (x86) Amazon Machine Image (AMI)
Amazon Machine Image (AMI)
An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
Version release notes
Adds a CloudFormation Quick Launch delivery option. Software identical to version 1.0.1.
Additional details
Usage instructions
Deploy with the FerroAir CloudFormation Quick Start (marketplace/cloudformation/ferroair-quickstart.yaml), which provisions a VPC, an RDS Postgres metadata database, ElastiCache Redis, an internet-facing webserver ALB, scheduler / worker / triggerer Auto Scaling Groups, and Secrets Manager entries for the DB password, Fernet key and JWT secret. Pass an ACM certificate ARN to enable HTTPS on the ALB; leave it blank for an HTTP-only evaluation. The Airflow 3.x-compatible REST API + UI are served on the ALB (health check GET /healthz). A bare single-instance launch also starts in single-node SQLite evaluation mode on port 8080. See docs/marketplace/aws-marketplace-guide.md.
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Email support at aws-support@abyo.net .
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