Overview
Dagster asset graph
The Dagster UI served on port 80 through an authenticating nginx proxy, showing the demo project's software-defined asset graph and lineage.
Dagster asset graph
Dagster run view
Dagster runs list
This is a repackaged open source software product wherein additional charges apply for cloudimg support services.
Overview Dagster is a fast, open source data orchestration platform for the development, production and observation of data assets. You define assets and jobs in plain Python and Dagster gives you a rich web interface to materialize them, schedule them, watch them run and inspect their lineage, with full visibility into every run. This image delivers Dagster fully installed in a dedicated virtual environment and run as system services, so a working orchestration platform is serving within minutes of launch.
Application Stack Dagster installed into a dedicated Python virtual environment under /opt/dagster and run by an unprivileged service account. The Dagster instance directory, holding the instance configuration and the run, event and schedule storage, stored on a dedicated data disk so it is independently resizable. Two systemd services: the webserver that serves the UI and the GraphQL API, and the daemon that drives schedules, sensors and the run queue. An nginx reverse proxy that publishes the UI on port 80 behind HTTP Basic authentication, with the WebSocket upgrade the UI needs to render fully.
Ready To Run Demo Project A demo Dagster project ships at /opt/dagster/demo: a handful of software-defined assets and a job, with a workspace file the webserver loads on start. It shows what a Dagster project looks like out of the box and gives you a working example to learn from. Point the workspace at your own code location and restart the services to go live.
Secure First Boot On the first boot of your instance a one shot service generates a fresh admin password, unique to that instance, writes it into the nginx credentials file and writes the password to a root only file. The Dagster webserver itself binds to loopback only and is never exposed without authentication. No shared or default credentials ship in the image.
Full WebSocket Support The Dagster UI streams live run and event updates over a GraphQL websocket. The bundled nginx proxy forwards the WebSocket upgrade and connection headers, so the UI loads and updates live behind authentication instead of hanging on a loading screen. The webserver info endpoint is reachable for monitoring.
cloudimg Support 24/7 technical support by email and chat. Help with deployment, defining assets and jobs, code locations and workspaces, scheduling and sensors, swapping the SQLite instance storage for PostgreSQL, TLS and performance tuning.
Use Cases Data pipeline and ELT orchestration. Software-defined asset management and lineage. Scheduled and event-driven data jobs. A self hosted control plane for analytics and machine learning workflows. A single-node Dagster deployment for development, demos and small teams.
All product and company names are trademarks or registered trademarks of their respective holders. Use of them does not imply any affiliation with or endorsement by them.
Highlights
- Dagster preinstalled in a dedicated Python virtual environment and run as the webserver and daemon systemd services behind an authenticating nginx proxy with full WebSocket support, serving a ready-to-run demo project on port 80, no manual setup required
- Define assets and jobs in plain Python and materialize, schedule, run and observe them from the web interface; the Dagster instance directory lives on a dedicated independently resizable data disk with default SQLite storage and no external database
- Hardened first boot generates a fresh admin password for every instance and stores it in a file only the root user can read, the webserver binds to loopback only, with 24/7 technical support from cloudimg
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Dimension | Description | Cost/hour |
|---|---|---|
t3.large Recommended | t3.large | $0.08 |
t2.micro | t2.micro instance type | $0.04 |
t3.micro | t3.micro instance type | $0.04 |
m5a.large | m5a.large instance type | $0.08 |
r5dn.24xlarge | r5dn.24xlarge instance type | $0.24 |
r8ib.metal-96xl | r8ib.metal-96xl instance type | $0.24 |
c8ine.xlarge | c8ine.xlarge instance type | $0.12 |
m5ad.xlarge | m5ad.xlarge instance type | $0.12 |
m6idn.32xlarge | m6idn.32xlarge instance type | $0.24 |
m7i.2xlarge | m7i.2xlarge instance type | $0.24 |
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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
Initial release of Dagster 1.13.10 with a ready-to-run demo project, the webserver and daemon services and an authenticating nginx proxy.
Additional details
Usage instructions
Connect via SSH on port 22 as the default login user for your operating system variant (the user guide lists it per variant). The Dagster UI is served on port 80: browse to http://<instance-public-ip>/ and sign in with user admin and the generated password. Retrieve the credentials with: sudo cat /root/dagster-credentials.txt. nginx reverse-proxies port 80 to the Dagster webserver on 127.0.0.1:3000 (with the GraphQL WebSocket upgrade the UI needs) behind HTTP Basic auth; the daemon (schedules, sensors, run queue) runs alongside it. A demo project ships at /opt/dagster/demo; point the workspace at your own code and restart: sudo systemctl restart dagster-webserver.service dagster-daemon.service. Install extra Python packages into the bundled virtual environment with: sudo /opt/dagster/venv/bin/pip install <package>. The Dagster instance directory DAGSTER_HOME, including the run and event storage, lives on a dedicated data disk mounted at /var/lib/dagster.
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Support
Vendor support
cloudimg provides 24/7 technical support for this product by email and live chat. Our engineers help with deployment, configuration, updates, performance tuning and troubleshooting; critical issues receive a one hour average response. Contact support@cloudimg.co.uk .
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.