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What is PipeCD?

A robust continuous delivery platform crafted for diverse application types across various cloud ecosystems, empowering engineers to deploy with enhanced speed and reliability. This GitOps solution streamlines deployment tasks via pull requests on Git, while its deployment pipeline interface provides a clear visualization of active processes. Each deployment is accompanied by a specialized log viewer, ensuring transparency regarding individual deployment activities. Users benefit from real-time application status updates and receive deployment notifications through Slack and webhook integrations. Performance insights related to delivery are easily accessible, further enriched by automated deployment evaluations that leverage metrics, logs, and outgoing requests. In case of any failure during an analysis or within a pipeline stage, the system automatically reverts to the most recent stable configuration. Furthermore, it quickly detects configuration drift, alerting users to any changes that have occurred. A new deployment is triggered automatically when specific events take place, such as a fresh container image being uploaded or a Helm chart being released. The platform also features single sign-on and role-based access control, ensuring that credentials are safeguarded and remain secure within the cluster without exposure in the control plane. By offering such comprehensive capabilities, this solution not only facilitates the deployment process but also significantly boosts overall operational efficiency and productivity.

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

AWS Lambda
Amazon Elastic Container Service (Amazon ECS)
Amazon SageMaker
Amazon Web Services (AWS)
Datadog
Git
GitHub
Google Cloud Trace
Kubernetes
Prometheus
Terraform

Integrations Supported

AWS Lambda
Amazon Elastic Container Service (Amazon ECS)
Amazon SageMaker
Amazon Web Services (AWS)
Datadog
Git
GitHub
Google Cloud Trace
Kubernetes
Prometheus
Terraform

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

PipeCD

Company Location

United States

Company Website

pipecd.dev/

Company Facts

Organization Name

Amazon

Date Founded

2006

Company Location

United States

Company Website

aws.amazon.com/sagemaker/pipelines/

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

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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