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What is Argo CD?

Argo CD functions as a continuous delivery solution specifically tailored for Kubernetes, following a declarative and GitOps methodology. It guarantees that application definitions, configurations, and environments are not only defined declaratively but are also subject to version control. The process of managing application deployment and its lifecycle is crafted to be automated, easily auditable, and accessible for users. By placing a strong emphasis on the GitOps framework, Argo CD employs Git repositories as the authoritative source for defining the desired state of applications. Through the automation of the deployment workflow, it effectively oversees the progression to the intended application states within specific environments. Moreover, Argo CD facilitates the monitoring of deployments in relation to various updates, such as branches, tags, or particular versions of manifests associated with a Git commit, which enhances both flexibility and accuracy in application management. This feature ultimately aids developers in sustaining consistency and reliability throughout their deployment processes, fostering an efficient workflow in the development lifecycle.

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

Akuity
Amazon SageMaker
Amazon Web Services (AWS)
Appvia Wayfinder
Argo
Cortex
Diego
Jit
Kubernetes
Kustomize.io
Lens Autopilot
Loft
Ondat
OpsMx Enterprise for Spinnaker
Opsera
Port
RapidFort
Syself
mirrord

Integrations Supported

Akuity
Amazon SageMaker
Amazon Web Services (AWS)
Appvia Wayfinder
Argo
Cortex
Diego
Jit
Kubernetes
Kustomize.io
Lens Autopilot
Loft
Ondat
OpsMx Enterprise for Spinnaker
Opsera
Port
RapidFort
Syself
mirrord

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

Applatix

Date Founded

2017

Company Website

argoproj.github.io/argo-cd/

Company Facts

Organization Name

Amazon

Date Founded

2006

Company Location

United States

Company Website

aws.amazon.com/sagemaker/pipelines/

Categories and Features

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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