Ratings and Reviews 2 Ratings
Ratings and Reviews 0 Ratings
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What is DeployBot?
Your entire team can seamlessly develop and release code from any location, utilizing a unified process. Deployments can be automated or carried out manually. You have the flexibility to initiate a deployment when it suits you, or automatically deploy changes with every branch push. The platform supports multiple environments, allowing each deployment environment, such as Production and Staging, to deploy code from various branches to numerous servers at the same time. In many situations, code must be built prior to deployment. DeployBot enables you to compile or execute any code from our servers during the deployment process. You can opt for pre-defined Docker containers or create entirely custom ones. Additionally, shell scripts can be executed on your server at any stage of deployment—before, during, or after. We will keep you informed about each deployment through your chosen communication channels. You can assess the impact of each deployment on performance and application stability through third-party integrations, ensuring that your applications run smoothly and effectively. This comprehensive approach guarantees a streamlined workflow for your development team.
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.
Integrations Supported
Amazon Web Services (AWS)
Amazon SageMaker
Bitbucket
Bugsnag
DigitalOcean
GitHub
GitLab
Heroku
New Relic
Shopify
Integrations Supported
Amazon Web Services (AWS)
Amazon SageMaker
Bitbucket
Bugsnag
DigitalOcean
GitHub
GitLab
Heroku
New Relic
Shopify
API Availability
Has API
API Availability
Has API
Pricing Information
$25 per month
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
SaaS.tech
Date Founded
2018
Company Location
United States
Company Website
deploybot.com
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
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
