Average Ratings 2 Ratings
Average Ratings 0 Ratings
Description
AWS CodePipeline is a comprehensive continuous delivery service that streamlines the automation of your release pipelines, ensuring swift and dependable updates for both applications and infrastructure. By integrating automation into the build, test, and deployment stages of your release workflow upon any code modification, as per your defined release model, CodePipeline facilitates the fast and reliable delivery of new features and updates. This service is designed to be easily customizable, allowing you to extend its functionality to meet your specific requirements. You have the flexibility to utilize either pre-existing plugins or create your own custom plugins for any phase of the release process. For instance, you can source your code from GitHub, leverage an on-premises Jenkins server for builds, conduct load testing with an external service, or relay deployment information to a personalized operations dashboard. With AWS CodePipeline, you can start mapping out your software release process without the hassle of server provisioning or setup. This not only saves time but also enhances your team's efficiency in managing deployments effectively.
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.
API Access
Has API
API Access
Has API
Integrations
AWS App Mesh
AWS App2Container
AWS Developer Tools
Alibaba Cloud Container Registry
Amazon SageMaker
Amazon Web Services (AWS)
Apica
Causal
ConnectALL
ContextQA
Integrations
AWS App Mesh
AWS App2Container
AWS Developer Tools
Alibaba Cloud Container Registry
Amazon SageMaker
Amazon Web Services (AWS)
Apica
Causal
ConnectALL
ContextQA
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
1994
Country
United States
Website
aws.amazon.com/codepipeline/
Vendor Details
Company Name
Amazon
Founded
2006
Country
United States
Website
aws.amazon.com/sagemaker/pipelines/
Product Features
Configuration Management
Access Control / Permissions
Application Deployment
Automated Provisioning
Infrastructure Automation
Node Management
Orchestration
Reporting Analytics / Visualization
Task Management
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
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