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About

Using Amazon SageMaker Pipelines, you can create ML workflows with an easy-to-use Python SDK, and then visualize and manage your workflow using Amazon SageMaker Studio. You can be more efficient and scale faster by storing and reusing the workflow steps you create in SageMaker Pipelines. You can also get started quickly with built-in templates to build, test, register, and deploy models so you can get started with CI/CD in your ML environment quickly. Many customers have hundreds of workflows, each with a different version of the same model. With the SageMaker Pipelines model registry, you can track these versions in a central repository where it is easy to choose the right model for deployment based on your business requirements. You can use SageMaker Studio to browse and discover models, or you can access them through the SageMaker Python SDK.

About

A unified continuous delivery solution for multiple application kinds on multi-cloud that empowers engineers to deploy faster with more confidence. A GitOps tool that enables doing deployment operations by pull request on Git. Deployment pipeline UI shows clarify what is happening. Separate logs viewer for each individual deployment. Real-time visualization of application state. Deployment notifications to slack, and webhook endpoints. Insights show the delivery performance. Automated deployment analysis based on metrics, logs, and emitted requests. Automatically roll back to the previous state as soon as analysis or a pipeline stage fails. Automatically detect configuration drift to notify and render the changes. Automatically trigger a new deployment when a defined event has occurred (e.g. container image pushed, helm chart published, etc). Support single sign-on and role-based access control. Credentials are not exposed outside the cluster and not saved in the control plane.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Individuals that need a first purpose-built CI/CD service for machine learning

Audience

Developers, teams and engineers interested in a solution to deploy their applications faster

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Amazon
Founded: 2006
United States
aws.amazon.com/sagemaker/pipelines/

Company Information

PipeCD
United States
pipecd.dev/

Alternatives

Alternatives

Amazon SageMaker Ground Truth

Amazon SageMaker Ground Truth

Amazon Web Services
Jenkins X

Jenkins X

The Linux Foundation

Categories

Categories

Integrations

AWS Lambda
Amazon Elastic Container Service (Amazon ECS)
Amazon SageMaker
Amazon Web Services (AWS)
Datadog
Git
GitHub
Google Cloud Trace
Kubernetes
Prometheus
Terraform

Integrations

AWS Lambda
Amazon Elastic Container Service (Amazon ECS)
Amazon SageMaker
Amazon Web Services (AWS)
Datadog
Git
GitHub
Google Cloud Trace
Kubernetes
Prometheus
Terraform
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