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What is Amazon SageMaker Pipelines?

Amazon SageMaker Pipelines enables users to effortlessly create machine learning workflows using an intuitive Python SDK while also providing tools for managing and visualizing these workflows via Amazon SageMaker Studio. This platform enhances efficiency significantly by allowing users to store and reuse workflow components, which facilitates rapid scaling of tasks. Moreover, it includes a variety of built-in templates that help kickstart processes such as building, testing, registering, and deploying models, thus making it easier to adopt CI/CD practices within the machine learning landscape. Many users oversee multiple workflows that often include different versions of the same model, and the SageMaker Pipelines model registry serves as a centralized hub for tracking these versions, ensuring that the correct model can be selected for deployment based on specific business requirements. Additionally, SageMaker Studio enables seamless exploration and discovery of models, while users can leverage the SageMaker Python SDK to efficiently access these models, promoting collaboration and boosting productivity among teams. This holistic approach not only simplifies the workflow but also cultivates a flexible environment that accommodates the diverse needs of machine learning practitioners, making it a vital resource in their toolkit. It empowers users to focus on innovation and problem-solving rather than getting bogged down by the complexities of workflow management.

What is AWS CodeDeploy?

AWS CodeDeploy is an all-encompassing deployment solution that simplifies the delivery of software across multiple compute environments, including Amazon EC2, AWS Fargate, AWS Lambda, and local servers. Leveraging AWS CodeDeploy enables the efficient rollout of new features while significantly reducing downtime linked to application updates, as it alleviates the challenges often associated with deployment procedures. The service automates the deployment process, thereby diminishing the dependency on manual techniques that frequently lead to errors. Moreover, AWS CodeDeploy is crafted to adapt to your deployment needs, providing the necessary flexibility as your requirements change over time. Its compatibility spans various platforms and programming languages, ensuring a uniform deployment experience, whether utilizing Amazon EC2, AWS Fargate, or AWS Lambda. You can easily reuse existing setup code, which aids in creating a more seamless transition. Additionally, CodeDeploy integrates effortlessly with your existing software release frameworks or continuous delivery systems, such as AWS CodePipeline, GitHub, and Jenkins, thereby improving your entire development workflow. This capacity for integration not only boosts team productivity but also fosters a smoother transition to automated deployment strategies, making it a valuable asset for modern software development. Ultimately, AWS CodeDeploy helps teams to innovate rapidly while maintaining reliability in their deployment processes.

Media

Media

Integrations Supported

AWS App Mesh
AWS Fargate
AWS Hybrid Cloud
AWS Lambda
Amazon EC2
Amazon SageMaker
Amazon Web Services (AWS)
Causal
Faros AI
Humanitec
Kaholo
Klera
Plutora
Quickwork

Integrations Supported

AWS App Mesh
AWS Fargate
AWS Hybrid Cloud
AWS Lambda
Amazon EC2
Amazon SageMaker
Amazon Web Services (AWS)
Causal
Faros AI
Humanitec
Kaholo
Klera
Plutora
Quickwork

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Amazon

Date Founded

2006

Company Location

United States

Company Website

aws.amazon.com/sagemaker/pipelines/

Company Facts

Organization Name

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/codedeploy

Categories and 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

Categories and 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

Popular Alternatives

Popular Alternatives