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What is Opsera?

Choose the tools that align perfectly with your requirements, and we will take care of the rest. Design a customized CI/CD stack that meets your organization's goals without concerns about vendor lock-in. By removing the necessity for manual scripts and intricate toolchain automation, your engineers can focus on core business functions. Our pipeline workflows embrace a declarative methodology, which allows you to emphasize critical tasks rather than the techniques needed to complete them, addressing components such as software builds, security evaluations, unit tests, and deployment procedures. With the integration of Blueprints, you can easily diagnose issues directly within Opsera, aided by comprehensive console output for each stage of your pipeline's performance. Obtain a complete perspective on your CI/CD process with in-depth software delivery analytics that monitor metrics like Lead Time, Change Failure Rate, Deployment Frequency, and Time to Restore. Moreover, enjoy the advantages of contextualized logs that enable faster problem-solving while improving auditing and compliance practices, ensuring your operations stay effective and transparent. This efficient strategy not only fosters enhanced productivity but also encourages teams to explore innovative solutions without constraints, ultimately driving greater success for your organization.

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

Amazon Web Services (AWS)
Amazon EKS
Amazon Elastic Container Service (Amazon ECS)
Anchore
Ansible
Apache ZooKeeper
Bamboo
Bitbucket
Cypress
Fluentd
Grafana
IBM Instana
Jira Service Management
Kibana
Kubernetes
Mattermost
Microsoft Azure
Rancher
Sysdig Secure
Travis CI

Integrations Supported

Amazon Web Services (AWS)
Amazon EKS
Amazon Elastic Container Service (Amazon ECS)
Anchore
Ansible
Apache ZooKeeper
Bamboo
Bitbucket
Cypress
Fluentd
Grafana
IBM Instana
Jira Service Management
Kibana
Kubernetes
Mattermost
Microsoft Azure
Rancher
Sysdig Secure
Travis CI

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

Opsera

Date Founded

2020

Company Location

United States

Company Website

www.opsera.io

Company Facts

Organization Name

Amazon

Date Founded

2006

Company Location

United States

Company Website

aws.amazon.com/sagemaker/pipelines/

Categories and 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

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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