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Average Ratings 0 Ratings
Description
Conductor serves as a cloud-based workflow orchestration engine designed to assist Netflix in managing process flows that rely on microservices. It boasts a number of key features, including an efficient distributed server ecosystem that maintains workflow state information. Users can create business processes where individual tasks may be handled by either the same or different microservices. The system utilizes a Directed Acyclic Graph (DAG) for workflow definitions, ensuring that these definitions remain separate from the actual service implementations. It also offers enhanced visibility and traceability for the various process flows involved. A user-friendly interface facilitates the connection of workers responsible for executing tasks within these workflows. Notably, workers are language-agnostic, meaning each microservice can be developed in the programming language best suited for its purposes. Conductor grants users total operational control over workflows, allowing them to pause, resume, restart, retry, or terminate processes as needed. Ultimately, it promotes the reuse of existing microservices, making the onboarding process significantly more straightforward and efficient for developers.
Description
Microservices architecture enables efficient streaming and batch data processing specifically designed for platforms like Cloud Foundry and Kubernetes. By utilizing Spring Cloud Data Flow, users can effectively design intricate topologies for their data pipelines, which feature Spring Boot applications developed with the Spring Cloud Stream or Spring Cloud Task frameworks. This powerful tool caters to a variety of data processing needs, encompassing areas such as ETL, data import/export, event streaming, and predictive analytics. The Spring Cloud Data Flow server leverages Spring Cloud Deployer to facilitate the deployment of these data pipelines, which consist of Spring Cloud Stream or Spring Cloud Task applications, onto contemporary infrastructures like Cloud Foundry and Kubernetes. Additionally, a curated selection of pre-built starter applications for streaming and batch tasks supports diverse data integration and processing scenarios, aiding users in their learning and experimentation endeavors. Furthermore, developers have the flexibility to create custom stream and task applications tailored to specific middleware or data services, all while adhering to the user-friendly Spring Boot programming model. This adaptability makes Spring Cloud Data Flow a valuable asset for organizations looking to optimize their data workflows.
API Access
Has API
Yes
API Access
Has API
No
Integrations
Apache Tomcat
No
Cloud Foundry
No
Kubernetes
No
Mariner Financial Wellness
No
Spring Framework
No
VMware Cloud
No
Integrations
Apache Tomcat
Yes
Cloud Foundry
Yes
Kubernetes
Yes
Mariner Financial Wellness
Yes
Spring Framework
Yes
VMware Cloud
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
No
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)
Yes
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)
No
In Person
No
Vendor Details
Company Name
Netflix
Website
github.com/netflix/conductor
Vendor Details
Company Name
Spring
Website
spring.io/projects/spring-cloud-dataflow