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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
Select the tools that best suit your needs, and we will handle everything else. Create an ideal CI/CD stack tailored to your organization's objectives without the worry of vendor lock-in. By eliminating the need for manual scripts and complex toolchain automation, your engineers can concentrate on your main business activities. Our pipeline workflows utilize a declarative approach, allowing you to prioritize essential tasks over the methods used to achieve them, covering aspects such as software builds, security assessments, unit testing, and deployment processes. With the help of Blueprints, you can troubleshoot any issues directly within Opsera, thanks to a detailed console output for each step of your pipeline's execution. Gain a holistic view of your CI/CD journey with extensive software delivery analytics, tracking metrics like Lead Time, Change Failure Rate, Deployment Frequency, and Time to Restore. Additionally, benefit from contextualized logs that facilitate quicker resolutions while enhancing auditing and compliance measures, ensuring that your operations remain efficient and transparent. This streamlined approach not only promotes better productivity but also empowers teams to innovate more freely.
API Access
Has API
API Access
Has API
Integrations
Amazon Web Services (AWS)
AWS Elastic Beanstalk
Amazon EKS
Bamboo
Checkmarx
CodeQL
Docker
Git
GitLab
JMeter
Integrations
Amazon Web Services (AWS)
AWS Elastic Beanstalk
Amazon EKS
Bamboo
Checkmarx
CodeQL
Docker
Git
GitLab
JMeter
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
$3.60 per user , Min 300 devs
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Amazon
Founded
2006
Country
United States
Website
aws.amazon.com/sagemaker/pipelines/
Vendor Details
Company Name
Opsera
Founded
2020
Country
United States
Website
www.opsera.ai/
Product 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
Product Features
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
Configuration Management
Access Control / Permissions
Application Deployment
Automated Provisioning
Infrastructure Automation
Node Management
Orchestration
Reporting Analytics / Visualization
Task Management
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