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What is Azure DevOps Projects?

Build an Azure application in under five minutes with simplicity and efficiency. The platform provides smooth integration with popular application frameworks and boasts an automated CI/CD pipeline that facilitates a more effective development process. You will also gain access to integrated monitoring features via Application Insights, enabling you to deploy on your chosen platform. Thanks to DevOps Projects, you can start your application deployment on any Azure service by following three easy steps: selecting your application language, choosing a runtime, and picking an Azure service. You can work with a diverse array of programming languages, including .NET, Java, PHP, Node.js, Python, and Go, and utilize either their well-known frameworks or push your custom application from a source control repository. Whether deploying on Windows or Linux, you have the choice to utilize Azure Web App, Virtual Machine, Service Fabric, or Azure Kubernetes Service. In spite of the wide variety of choices, the process remains accessible and efficient for all users. Furthermore, you will benefit from detailed performance monitoring, reliable alert systems, and user-friendly dashboards, all of which ensure your applications are highly available and performing at their best. This streamlined method not only boosts productivity but also allows developers to dedicate their time to crafting innovative solutions that can meet diverse business needs. The ease of use and comprehensive features make Azure an attractive option for developers looking to create and manage applications effectively.

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

5X
7pace Timetracker
Alemba Service Manager
Atomicwork
Azure Marketplace
Cardagraph
Delinea Cloud Access Controller
Dimodelo
Microsoft Viva Goals
OnePlan
PVS-Studio
Pull Sense
Resmo
StoriesOnBoard
Symbio
Tromzo
Unleash
UseResponse
WorkBoard
esChecker

Integrations Supported

5X
7pace Timetracker
Alemba Service Manager
Atomicwork
Azure Marketplace
Cardagraph
Delinea Cloud Access Controller
Dimodelo
Microsoft Viva Goals
OnePlan
PVS-Studio
Pull Sense
Resmo
StoriesOnBoard
Symbio
Tromzo
Unleash
UseResponse
WorkBoard
esChecker

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

Microsoft

Date Founded

1975

Company Location

United States

Company Website

azure.microsoft.com/en-us/features/devops-projects/

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

Continuous Integration

Build Log
Change Management
Configuration Management
Continuous Delivery
Continuous Deployment
Debugging
Permission Management
Quality Assurance Management
Testing Management

DevOps

Approval Workflow
Dashboard
KPIs
Policy Management
Portfolio Management
Prioritization
Release Management
Timeline Management
Troubleshooting Reports

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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