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Average Ratings 0 Ratings

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ease
features
design
support

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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

Our SaaS solution integrates seamlessly with your current CI/CD pipeline, enabling the creation of preview environments and the execution of comprehensive end-to-end tests. When a developer commits code, we swiftly duplicate your stack in mere seconds by utilizing snapshots from prior builds. In one instance of your stack, you can conduct end-to-end testing, while in another, you might build and push Docker images, and yet in a different instance, you can establish temporary review environments. Once a modification has been approved, it can be rapidly deployed to users through your existing deployment pipeline. After a single setup of your stack on webapp.io, you can instantly generate 10 copies, allowing for parallel execution of all your end-to-end and acceptance tests, thus streamlining the development process and enhancing efficiency. The flexibility of our platform ensures that development teams can optimize their workflows and minimize the time between code changes and production deployment.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Amazon SageMaker
Amazon Web Services (AWS)
Angular
Bitbucket
BrowserStack
ConfigCat
Cypress
Django
Docker
GitHub
GitLab
Kubernetes
Laravel
MongoDB
MySQL
Node.js
React
Reflect
Ruby on Rails
Selenium

Integrations

Amazon SageMaker
Amazon Web Services (AWS)
Angular
Bitbucket
BrowserStack
ConfigCat
Cypress
Django
Docker
GitHub
GitLab
Kubernetes
Laravel
MongoDB
MySQL
Node.js
React
Reflect
Ruby on Rails
Selenium

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

webapp.io

Founded

2018

Country

Canada

Website

webapp.io

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 Integration

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

Alternatives

Alternatives

Amazon SageMaker Ground Truth Reviews

Amazon SageMaker Ground Truth

Amazon Web Services