Implementação de uma arquitetura de microsserviços para telemetría agrícola - Fiorese, Edinei (2025)
Telemetry in agricultural machinery plays an important role in data collection. With the growth in the transmission of this information, monolithic architectures face challenges such as high latency and significant scalability constraints. With this in mind, this work sought to investigate these limitations and validate an architecture based on microservices and message queues. To this end, Amazon SOS was used for message queue orchestration and asynchronous communication, AWS Lambda for scalable serverless processing, and Amazon RDS and Amazon S3 for efficient and durable data persistence. The methodology adopted is applied research, with a mixed-methods approach (quantitative and qualitative), and a case study. The investigation process unfolded in five phases: diagnosis of the legacy system, proposal of the new architecture, development of a proof of concept, performance evaluation and testing, and deployment in a production environment. Quantitative results demonstrated a reduction in processing latency, with the average complete cycle time for alarm messages dropping from approximately 394 seconds in the monolithic architecture to about 21 seconds in the microservices solution. Cost analysis revealed the economic viability of the solution, reinforced by AWS's pay-as-you-go pricing model, which optimized spending on microservices such as SOS and Lambda. Qualitative validation, conducted through interviews and questionnaires with key system users, confirmed the perception of a significant improvement in reliability, data accuracy, and a reduction in operational complaints. Thus, it was found that the new microservices-based architecture improved latency, enabled scalability, and identified an improvement in users' perception of telemetry systems.