SEDA Architecture (scalability)

SEDA - the scalability guarantee

The SEDA architecture removes all limitations to business growth, even when servers fail to cope with the required workload. SEDA resizes itself by incorporating execution units, subsystems and new servers, all working together, atomizing processes and distributing their executions.

All this happens unnoticed by the operator, since SEDA receives the requests, directing them to the most efficient execution units at all times, and returning the result in the format requested by the user.

The SEDA architecture applies to all current and future RD Sistemas applications, guaranteeing scalable growth to meet the client's business needs.

SEDA architecture was designed and developed by RD Sistemas to meet our clients’ scalability needs and reach the performance level they might require when operating contracted applications. Programmed in different programming languages, the stability, portability and performance of which make of this architecture the ideal scalability solution no matter the workload.

Through SEDA, process load is distributed among different machines to carry out the work, relieving thereby the machine from which processes were ordered.

The SEDA architecture comprises a platform for batch processes and an environment for interactive requests.

Interactive Process

• Programming languages: PowerBuilder, Java and Python.
• It comprises two object types: the dispatcher and interactive execution units.
• The dispatcher is responsible for monitoring execution units and sending work processes (tasks). It was developed with Python.
• The interactive execution units receive tasks and act accordingly. All business code is that used by our main applications, which makes them highly stable and reliable systems.

Batch

• Programming languages: Java and PowerBuilder.
• It comprises two object types: JSeda server and Batch execution units.
• The JSeda server is fully developed with Java. Its multi-threaded programming is suitable for processing large data volumes on demand. Its robustness, reliability and execution compatibility with multiple operating systems bear witness to its versatility.