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Description
AWS CodeDeploy is a comprehensive deployment service that streamlines the process of deploying software across various compute resources, including Amazon EC2, AWS Fargate, AWS Lambda, and your own on-premises servers. By facilitating rapid feature releases, AWS CodeDeploy helps maintain application uptime during deployments and simplifies the often complex task of updating applications. This service allows for the automation of software deployments, which reduces the risk associated with manual procedures. Additionally, it scales effortlessly to meet your deployment requirements. Being platform and language agnostic, AWS CodeDeploy ensures a consistent experience across different environments, whether you are deploying to Amazon EC2, AWS Fargate, or AWS Lambda, and you can conveniently repurpose your existing setup code as needed. Furthermore, CodeDeploy can seamlessly integrate with your current software release workflows or continuous delivery pipelines, such as AWS CodePipeline, GitHub, or Jenkins, thereby enhancing your overall deployment strategy and efficiency. In this way, AWS CodeDeploy not only simplifies the deployment process but also enhances the reliability and speed of software updates.
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 Fargate
AWS Hybrid Cloud
AWS Lambda
Amazon EC2
Amazon SageMaker
Amazon Web Services (AWS)
Causal
Faros AI
Humanitec
Integrations
AWS App Mesh
AWS Fargate
AWS Hybrid Cloud
AWS Lambda
Amazon EC2
Amazon SageMaker
Amazon Web Services (AWS)
Causal
Faros AI
Humanitec
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/codedeploy
Vendor Details
Company Name
Amazon
Founded
2006
Country
United States
Website
aws.amazon.com/sagemaker/pipelines/
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
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
