Overview

Product video
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
Free trial
Dimension | Description | Cost/unit/hour |
---|---|---|
Hours | Container Hours | $0.07 |
Vendor refund policy
Deeploy Core is not eligible for refunds, but customers are free to cancel anytime.
Custom pricing options
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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
New features
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Custom monitoring metrics Visualize your own metrics in the new Custom tab in Deployment monitoring. Add up to four custom metrics; calculate the data points you want to visualize and upload them using the Deeploy python client or API.
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Flexible input and output schema mapping Leverage Deeploy's full monitoring capabilities for external and custom Docker models with request and response mapping. Define a JSON mapping in your metadata for models that do not adhere to Deeploy's standard.
Improvements
- Created a new navbar and Workspace selector to easily navigate between Workspaces
- Improved error handling for connecting to an external object storage
- Detached the selection of nodes from selecting custom resources (Private cloud only)
- Improved validation for the validUntil property of tokens and personal key pairs
- Added state for missing metadata in the Deployment details
- Stricter validation on environment variable keys to prevent confusing Deployment errors
- Improved error handling for failed Deployment updates
Bug fixes
- Fixed an issue with upgrading Deployments to external or managed
- Fixed an issue where Deployments with a large amount of prediction logs couldn't be deleted
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/installation/amazon-eks/eks-2 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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