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Average Ratings 0 Ratings

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features
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support

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Write a Review

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

Concourse serves as an open-source tool designed for continuous automation, effectively streamlining processes through its foundational elements of resources, tasks, and jobs, making it particularly suitable for CI/CD applications. Its pipeline functions similarly to a distributed, ongoing Makefile, where each job outlines a build plan that specifies input resources and the actions to take upon their changes. The web UI visually represents your pipeline, allowing users to seamlessly navigate from a job failure to understanding the underlying issues with just a single click. This visualization acts as a "gut check" feedback mechanism: if something appears off, it likely warrants attention. Additionally, jobs can be linked through dependency configurations, creating an interconnected graph of jobs and resources that perpetually advances your project from the initial codebase to deployment. All aspects of configuration and management are handled via the fly CLI, with the fly set-pipeline command being used to upload the configuration to Concourse. Once you confirm that everything is set up correctly, you can then commit the configuration to your source control repository, ensuring that your automation remains aligned with your project's evolving needs. This flexibility and clarity make Concourse an invaluable asset for developers looking to enhance their continuous integration and delivery workflows.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Amazon SageMaker Yes 
Amazon Web Services (AWS) Yes 
Cycloid No 
LT Browser No 
Netdata No 
OverOps No 
Qyrus No 
StackHawk No 
Trivy No 

Integrations

Amazon SageMaker No 
Amazon Web Services (AWS) No 
Cycloid Yes 
LT Browser Yes 
Netdata Yes 
OverOps Yes 
Qyrus Yes 
StackHawk Yes 
Trivy Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

Free
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 Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
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

Concourse CI

Website

concourse-ci.org

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 

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