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What is CodeShip?

Do you prefer a quick setup for all your requirements, or do you appreciate the freedom to customize your environment and workflow according to your preferences? CodeShip allows developers to select the most suitable path for their individual needs, boosting productivity and enabling teams to evolve over time. It provides an extensive array of features, including deployment automation, notification systems, code coverage analysis, security checks, and on-premise source control management, which facilitates smooth integration with essential tools, services, or cloud platforms for an optimized workflow experience. Our aim is to ensure that CodeShip is not only user-friendly but also offers rapid and thorough support for developers when needed. Access to knowledgeable technical support without delay is vital when you face challenges or need guidance, and that is a promise we uphold at CodeShip. You can kick off your builds and deployments in under five minutes, thanks to CodeShip's simple environment and user-friendly interface. As your projects grow, you have the option to evolve into more sophisticated workflows and utilize configuration-as-code, allowing your tools to adapt alongside your changing needs. This adaptable strategy guarantees that your workflow remains responsive to your evolving requirements, helping you maintain momentum in your development process. Ultimately, CodeShip is committed to enhancing your development experience while ensuring that you never feel limited by your tools.

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.

Media

Media

Integrations Supported

Amazon SageMaker
Amazon Web Services (AWS)
CA Flowdock
CloudBees
ConnectALL
Crashtest Security
Google Cloud Container Registry
JFrog Pipelines
JFrog Platform
LT Browser
RedLine13
SOOS
Seeker
SpecFlow
Testim
Testsigma
UI-licious
VAddy

Integrations Supported

Amazon SageMaker
Amazon Web Services (AWS)
CA Flowdock
CloudBees
ConnectALL
Crashtest Security
Google Cloud Container Registry
JFrog Pipelines
JFrog Platform
LT Browser
RedLine13
SOOS
Seeker
SpecFlow
Testim
Testsigma
UI-licious
VAddy

API Availability

Has API

API Availability

Has API

Pricing Information

$49 per month
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

CloudBees

Date Founded

2011

Company Location

United States

Company Website

codeship.com

Company Facts

Organization Name

Amazon

Date Founded

2006

Company Location

United States

Company Website

aws.amazon.com/sagemaker/pipelines/

Categories and Features

Application Development

Access Controls/Permissions
Code Assistance
Code Refactoring
Collaboration Tools
Compatibility Testing
Data Modeling
Debugging
Deployment Management
Graphical User Interface
Mobile Development
No-Code
Reporting/Analytics
Software Development
Source Control
Testing Management
Version Control
Web App Development

Build Automation

Automated Testing
Build Cache
Build Management Tools
Build Metrics
Change Only Compiling
Debugging Tools
Dependency Management
IDE Compatibility
Parallel Testing
Plugin Library
Source Code Management
Version Conflict Resolution

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

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

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