Average Ratings 0 Ratings
Average Ratings 0 Ratings
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
OES boasts high availability and scalability, making it suitable for managing growing deployment workloads, while also being adaptable enough to work seamlessly with various SDLC tool chains. It provides a user-friendly interface for defining custom stages that allow for simultaneous deployments across multiple targets, significantly reducing time spent on deployment. Actions such as rolling back, moving forward, or halting all parallel deployments can be performed effortlessly with just a click. Additionally, the platform enables automation of repetitive tasks within the SDLC process by allowing the creation of numerous child pipelines that can be triggered from a parent pipeline. With its modular design and API-based architecture, OES functions effectively as a central Continuous Delivery (CD) tool for numerous enterprises. This flexibility allows developers on different teams to easily connect external services with Spinnaker for streamlined deployment orchestration, enhancing overall productivity and collaboration. As a result, OES stands out as a powerful solution for optimizing deployment processes across various environments.
API Access
Has API
No
API Access
Has API
Yes
Integrations
Amazon Web Services (AWS)
Yes
Amazon S3
No
Amazon SageMaker
Yes
Ansible
No
Apache Mesos
No
Bitbucket
No
Checkmarx
No
Datadog
No
Elasticsearch
No
GitHub
No
Integrations
Amazon Web Services (AWS)
Yes
Amazon S3
Yes
Amazon SageMaker
No
Ansible
Yes
Apache Mesos
Yes
Bitbucket
Yes
Checkmarx
Yes
Datadog
Yes
Elasticsearch
Yes
GitHub
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
Yes
Free Version
No
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
No
Mac
No
Linux
No
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
Yes
Live Training (Online)
Yes
In Person
Yes
Vendor Details
Company Name
Amazon
Founded
2006
Country
United States
Website
aws.amazon.com/sagemaker/pipelines/
Vendor Details
Company Name
OpsMx
Founded
2017
Country
United States
Website
www.opsmx.com/opsmx-enterprise-spinnaker/scalable-and-extensible/
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
Application Development
Access Controls/Permissions
No
Code Assistance
No
Code Refactoring
No
Collaboration Tools
No
Compatibility Testing
No
Data Modeling
No
Debugging
No
Deployment Management
No
Graphical User Interface
No
Mobile Development
No
No-Code
No
Reporting/Analytics
No
Software Development
No
Source Control
No
Testing Management
No
Version Control
No
Web App Development
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