This document briefly describes various deployment methods for you to choose from.
FineDataLink has a built-in HyperSQL database (HSQLDB). The HSQLDB cannot be accessed by multiple threads and may become unstable in a cluster environment with large amounts of data. It is suitable for a local trial of product functionality.
For details, see External Database Configuration.
Containerized Deployment
Standalone/Cluster
★★★★★
Advantages:
Cost-efficient deployment: You can deploy the whole project including the FineDataLink project node, the load balancer, the state server, the file server, the external database, and the data pipeline with Apache Kafka (and other high-availability components you prepared for deploying a high-availability cluster) with one click.
Cost-efficient startup: Startup parameters are added by default after successful deployment, requiring no manual configuration.
Limited impact of issues: For containerized projects, any anomalies are confined to their respective environments, limiting the impact scope.
Cost-efficient O&M: Containerized projects are deployed via FineOps, which supports the monitoring and alerting of servers, FineDataLink applications, and component services.
Traditional Deployment
Standalone
Manual Independent Deployment of FDL on Tomcat
Deployment of FDL on a China Homegrown Operating System
Independent Deployment of FDL on WebLogic with a WAR Package
Independent Deployment of FDL on WebLogic with a Folder
Independent Deployment of FDL on WebSphere
No restriction is posed on the middleware or server architecture.
Limitations:
Except for Tomcat deployment, other deployment methods require the JDK environment and the middleware to be deployed in advance.
You should prepare the FineDataLink project package in advance.
You need to set parameters manually after deployment to ensure stable system operation.
Prompt monitoring and alerting of the system operation is impossible.
Cluster
Manual Deployment of a FDL Cluster on Linux
Manual Deployment of a FDL Cluster on Windows
Compared with standalone projects, projects in a cluster communicate and share data and tasks with each other. They can also provide higher extensibility and performance, improve the load-bearing capacity and availability of the system, and ensure system stability and consistency.
You need to manually deploy and serially/parallel connect project nodes, the load balancer, the state server, the file server, the configuration database, and the service registry, and modify their configurations.
You need to manually set parameters after deployment to ensure stable system operation.
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