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Publication
Monitorização e análise de logs, alerta de erros e apresentação de métricas de negócio
| Name: | Description: | Size: | Format: | |
|---|---|---|---|---|
| 5.37 MB | Adobe PDF |
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Abstract(s)
Esta dissertação aborda o desenvolvimento de uma solução focada na monitorização, análise e geração de alertas para logs empresariais, com o objetivo de otimizar a gestão de eventos críticos em sistemas de informação. O projeto surge da necessidade de métodos mais eficientes e centralizados para lidar com grandes volumes de dados, superando as limitações das abordagens tradicionais, que muitas vezes são lentas e dependem de intervenções manuais. A solução proposta traz uma abordagem inovadora, voltada para monitorizar logs e extrair métricas de negócio que possam facilitar a tomada de decisões e agilizar a resolução de
problemas. Para isso, será utilizada uma ferramenta de monitorização escalável e flexível, capaz de integrar dados provenientes de diversas fontes e automatizar alertas em tempo real. Entre as funcionalidades principais estão a criação de pipelines para processar e analisar logs, a extração de métricas relevantes e a configuração de alertas automáticos para eventos críticos. Ao longo do projeto vão ser executados testado iterativos para garantir a eficácia na identificação de problemas e na redução do tempo de resposta. Os testes envolverão dados simulados e a recolha de feedback dos utilizadores por meio de um formulário, permitindo avaliar tanto a precisão quanto a utilidade da solução. Além disso, essas avaliações contribuirão com pontos de melhoria para futuras evoluções. Assim, esta dissertação propõe contribuir com uma solução robusta e escalável para a gestão de logs,
promovendo maior eficiência operacional e reforçando a segurança em sistemas empresariais complexos.
This dissertation addresses the development of a solution focused on monitoring, analyzing and generating alerts for corporate logs, with the aim of optimizing the management of critical events in information systems. The project arises from the need for more efficient and centralized methods for dealing with large volumes of data, overcoming the limitations of traditional approaches, which are often slow and rely on manual interventions. The proposed solution brings an innovative approach, aimed at monitoring logs and extracting business metrics that can facilitate decision-making and speed up problem-solving. To do this, a scalable and flexible monitoring tool will be used, capable of integrating data from various sources and automating alerts in real time. Key features include creating pipelines to process and analyze logs, extracting relevant metrics and setting up automatic alerts for critical events. After implementation, the project will be tested and adjusted to ensure its effectiveness in identifying problems and reducing response times. The tests will involve simulated data and user feedback, making it possible to assess both the accuracy and usefulness of the solution. In addition, these evaluations will contribute points of improvement for future developments. Thus, this dissertation proposes to contribute with a robust and scalable solution for log management, promoting greater operational efficiency and reinforcing security in complex business systems.
This dissertation addresses the development of a solution focused on monitoring, analyzing and generating alerts for corporate logs, with the aim of optimizing the management of critical events in information systems. The project arises from the need for more efficient and centralized methods for dealing with large volumes of data, overcoming the limitations of traditional approaches, which are often slow and rely on manual interventions. The proposed solution brings an innovative approach, aimed at monitoring logs and extracting business metrics that can facilitate decision-making and speed up problem-solving. To do this, a scalable and flexible monitoring tool will be used, capable of integrating data from various sources and automating alerts in real time. Key features include creating pipelines to process and analyze logs, extracting relevant metrics and setting up automatic alerts for critical events. After implementation, the project will be tested and adjusted to ensure its effectiveness in identifying problems and reducing response times. The tests will involve simulated data and user feedback, making it possible to assess both the accuracy and usefulness of the solution. In addition, these evaluations will contribute points of improvement for future developments. Thus, this dissertation proposes to contribute with a robust and scalable solution for log management, promoting greater operational efficiency and reinforcing security in complex business systems.
Description
Keywords
Log monitoring Automation Data analysis Scalability Operational Efficiency Real-time alerts Monitorização de logs Automação Análise de dados Escalabilidade Eficiência operacional Alertas em tempo real