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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

With Amazon SageMaker Pipelines, you can effortlessly develop machine learning workflows using a user-friendly Python SDK, while also managing and visualizing your workflows in Amazon SageMaker Studio. By reusing and storing the steps you create within SageMaker Pipelines, you can enhance efficiency and accelerate scaling. Furthermore, built-in templates allow for rapid initiation, enabling you to build, test, register, and deploy models swiftly, thereby facilitating a CI/CD approach in your machine learning setup. Many users manage numerous workflows, often with various versions of the same model. The SageMaker Pipelines model registry provides a centralized repository to monitor these versions, simplifying the selection of the ideal model for deployment according to your organizational needs. Additionally, SageMaker Studio offers features to explore and discover models, and you can also access them via the SageMaker Python SDK, ensuring versatility in model management. This integration fosters a streamlined process for iterating on models and experimenting with new techniques, ultimately driving innovation in your machine learning projects.

Description

A comprehensive continuous delivery platform designed for various application types across multiple cloud environments, enabling engineers to deploy with increased speed and assurance. This GitOps tool facilitates deployment operations through pull requests on Git, while its deployment pipeline interface clearly illustrates ongoing processes. Each deployment benefits from a dedicated log viewer, providing clarity on individual deployment activities. Users receive real-time updates on the state of applications, along with deployment notifications sent to Slack and webhook endpoints. Insights into delivery performance are readily available, complemented by automated deployment analysis utilizing metrics, logs, and emitted requests. In the event of a failure during analysis or a pipeline stage, the system automatically reverts to the last stable state. Additionally, it promptly identifies configuration drift to alert users and showcase any modifications. A new deployment is automatically initiated upon the occurrence of specified events, such as a new container image being pushed or a Helm chart being published. The platform supports single sign-on and role-based access control, ensuring that credentials remain secure and are not exposed outside the cluster or stored in the control plane. This robust solution not only streamlines the deployment process but also enhances overall operational efficiency.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

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

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Amazon

Founded

2006

Country

United States

Website

aws.amazon.com/sagemaker/pipelines/

Vendor Details

Company Name

PipeCD

Country

United States

Website

pipecd.dev/

Product Features

Continuous Delivery

Application Lifecycle Management
Application Release Automation
Build Automation
Build Log
Change Management
Configuration Management
Continuous Deployment
Continuous Integration
Feature Toggles / Feature Flags
Quality Management
Testing Management

Continuous Integration

Build Log
Change Management
Configuration Management
Continuous Delivery
Continuous Deployment
Debugging
Permission Management
Quality Assurance Management
Testing Management

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

Product Features

Continuous Delivery

Application Lifecycle Management
Application Release Automation
Build Automation
Build Log
Change Management
Configuration Management
Continuous Deployment
Continuous Integration
Feature Toggles / Feature Flags
Quality Management
Testing Management

Alternatives

Alternatives

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