Titulo Estágio
Monitoring of Microservices
Áreas de especialidade
Engenharia de Software
Sistemas Inteligentes
Local do Estágio
DEI-FCTUC
Enquadramento
Breaking large software systems into smaller functionally interconnected components is a trend on the rise. This architectural style, known as "microservices", simplifies development, deployment and management at the expense of complexity and observability. Microservice-based architectures and Function-as-a-Service (FaaS) platforms are being favored for the flexibility they afford. This trend is only accelerated by the financial benefits and reduced development times promised by Platforms-as-a-Service (PaaS) and serverless deployments. The benefits are faster development cycles, development team independence (because scope is limited and well defined), ease of deployment, management, scaling and governance. Microservices, and FaaS are the building blocks of modern, highly dynamic distributed systems. We can see this trend in many large international companies, like LinkedIn, Netflix, Uber, Ebay, Amazon, among many others, but the same trend can be found in important national companies as well.
On the downside, companies face increasing visibility challenges into the health and performance of their systems, as cloud and micro-service architectures become more complex and dynamic, with more changing parts. The complexity moves from the components to their interaction, and their emergent behaviors. Since developers and operators lack a complete view of the system, the result is impaired observability, which turns debugging and monitoring into a challenge that keeps getting harder, as systems grow larger with additional components and version iterations.
Objetivo
One of the limitations we found in our current work is the lack of real systems and good data to build the analytic tools. It also very difficult to work with sample systems that try to emulate larger applications, because, despite being small, they require a large and complex infrastructure to run. Furthermore, they do not provide representative data for analysis.
In this internship, the student is expected to:
- Study microservice monitoring approaches, including metrics and logging, but focusing on tracing.
- Prepare a simulation of a large-scale system.
- Inject anomalies on the simulation and run the experiments with and without anomalies.
- Create ML algorithms to detect and diagnose anomalies in the system.
Plano de Trabalhos - Semestre 1
- Study of the existing work and microservice monitoring techniques (2 months).
- Study state-of-the-art microservice simulation tools (2 months).
- Write intermediate report (1 month).
Plano de Trabalhos - Semestre 2
- Prepare the simulation with anomaly injection (2 months).
- Run experiments and collect results (1 month).
- Analysis and algorithm development (2 months).
- Write final report (1 month).
Condições
The work should take place at the Centre for Informatics and Systems of the University of Coimbra (CISUC) at the Department of Informatics Engineering of the University of Coimbra in the scope of the Power research project with Altice.
A 745 euros per month scholarship is foreseen for 3 months. The attribution of the scholarship is subject to a public application.
Orientador
Filipe Araújo and João Nuno Correia and Raul Barbosa
filipius@uc.pt 📩