Average Ratings 0 Ratings
Average Ratings 2 Ratings
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
Your entire team can instantly build and ship code from anywhere, in one consistent process. You can either automate or manual deployments. You can trigger a deployment when you are ready, or deploy on every push of a branch. Tools for multiple environments. Each deployment environment (such as Production and Staging), can ship code from different branches to one of many servers simultaneously. Code cannot be deployed in many cases without being built first. DeployBot allows you to execute or compile any code from our servers during deployment. You can use pre-defined or completely customized Docker containers. You can also run shell scripts on your server before, during, and after deployment. We will notify you via your preferred communication channels about every deployment. Analyze how each deployment affects performance and application stability using third-party integrations.
API Access
Has API
No
API Access
Has API
Yes
Integrations
Amazon Web Services (AWS)
Yes
Amazon SageMaker
Yes
Bitbucket
No
Bugsnag
No
DigitalOcean
No
GitHub
No
GitLab
No
Heroku
No
New Relic
No
Shopify
No
Integrations
Amazon Web Services (AWS)
Yes
Amazon SageMaker
No
Bitbucket
Yes
Bugsnag
Yes
DigitalOcean
Yes
GitHub
Yes
GitLab
Yes
Heroku
Yes
New Relic
Yes
Shopify
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
$25 per month
Free Trial
No
Free Version
Yes
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Amazon
Founded
2006
Country
United States
Website
aws.amazon.com/sagemaker/pipelines/
Vendor Details
Company Name
SaaS.tech
Founded
2018
Country
United States
Website
deploybot.com
Product Features
Continuous Delivery
Application Lifecycle Management
No
Application Release Automation
No
Build Automation
No
Build Log
No
Change Management
No
Configuration Management
No
Continuous Deployment
No
Continuous Integration
No
Feature Toggles / Feature Flags
No
Quality Management
No
Testing Management
No
Continuous Integration
Build Log
No
Change Management
No
Configuration Management
No
Continuous Delivery
No
Continuous Deployment
No
Debugging
No
Permission Management
No
Quality Assurance Management
No
Testing Management
No
Machine Learning
Deep Learning
No
ML Algorithm Library
No
Model Training
No
Natural Language Processing (NLP)
No
Predictive Modeling
No
Statistical / Mathematical Tools
No
Templates
No
Visualization
No
Product Features
Continuous Delivery
Application Lifecycle Management
No
Application Release Automation
No
Build Automation
No
Build Log
No
Change Management
No
Configuration Management
No
Continuous Deployment
No
Continuous Integration
No
Feature Toggles / Feature Flags
No
Quality Management
No
Testing Management
No
Continuous Integration
Build Log
No
Change Management
No
Configuration Management
No
Continuous Delivery
No
Continuous Deployment
No
Debugging
No
Permission Management
No
Quality Assurance Management
No
Testing Management
No