Overview
Nowadays, transparency, explainability and security of AI models is more important than ever. Having a safe and secure environment to deploy your models enables you to continuously monitor your model performance with confidence and responsibility. Easily integrate Deeploy Core with your existing AWS stack. Deploying and maintaining ML systems requires involvement of people and tools. Deeploy Responsible AI software giving data science teams autonomy to create and maintain their models.
The challenges Deeploy solves:
- A safe and responsible MLOps environment: organized and monitored deployments
- Explain and understand AI decisions: create human-AI interaction with experts
- Traceback how decisions are made: be able to correct, report and reproduce.
Highlights
- A safe and responsible MLOps environment: organized and monitored deployments
- Explain and understand AI decisions: create human-AI interaction with experts
- Traceback how decisions are made: be able to correct, report and reproduce
Details
Features and programs
Financing for AWS Marketplace purchases
Pricing
- $900.00/month
Vendor refund policy
no refunds, but free to cancel anytime
Legal
Vendor terms and conditions
Content disclaimer
Delivery details
Main Installation
- Amazon EKS
Container image
Containers are lightweight, portable execution environments that wrap server application software in a filesystem that includes everything it needs to run. Container applications run on supported container runtimes and orchestration services, such as Amazon Elastic Container Service (Amazon ECS) or Amazon Elastic Kubernetes Service (Amazon EKS). Both eliminate the need for you to install and operate your own container orchestration software by managing and scheduling containers on a scalable cluster of virtual machines.
Version release notes
1.44.0
Release notes
New features
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Deployment approval Ensure your Deployment quality by requesting approval from your Workspace members before deploying it. The Deployment version will be pending until it has been approved, after which you can deploy it.
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Select compliance templates per Deployment You can now add and remove specific compliance documentation and checklist templates on a Deployment level. Tailor your compliance towards what is important for a specific Deployment.
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Upgrade Deployments Upgrade your Deployment to unlock more of Deeploy's functionalities! Go to your registration or external Deployment details, click upgrade, and follow the upgrade flow to upgrade your Deployment use case.
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Filter monitoring graphs Filter your monitoring graphs to refine your Deployment monitoring graphs even better. Go to your Deployment's monitoring page and click Filters to add the desired filters to your graphs.
Improvements
- Okta has been added as an option for OIDC Authentication (Private Cloud only)
- Introduced a status and status code filter for the request logs
- Added an endpoint type filter to the prediction logs
- Improved handling of a failed Deployment in the UI
- Added a loader to the drift monitoring graphs
Bug fixes
- Fixed incorrect "custom id" name in a filter of predictions.
- Fixed an issue when switching between Deployments sometimes showed the old Deployment details
- Fixed the notification pagination
- Fixed slow loading of external Deployments in the Deployment overview
Additional details
Usage instructions
The general installation steps are as follows: a. Make sure to follow the installation steps as described here: https://docs.deeploy.ml/category/amazon-eks (start at step 2, since you already subscribed to the marketplace listing) b. Install the Deeploy software requirements and helm chart. For the latest stable release checkout: https://artifacthub.io/packages/helm/deeploy-core/deeploy . Use the Deeploy helm chart repository and follow the instructions in the README: https://gitlab.com/deeploy-ml/deeploy-install .
Resources
Vendor resources
Support
Vendor support
Default community support is included. Additional support and SLA are available on request: sales@deeploy.ml
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.
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