Architecture and infrastructure

ALTO’s architecture ensures a scalable, secure and efficient platform that provides stability, scalability and continuous development. It implements strict security and access control measures to ensure privacy and information quality, thereby improving the accuracy and efficiency of its operations.

Architecture

https://gitlab.grupoalto.com/equipos/arquitectura/docs

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Infrastructure

To achieve this goal, a computationally correct platform is necessary, so ALTO Alliance is developed under a state-of-the-art computational architecture that combines the power of cloud computing (Google Cloud Platform (GCP)), the flexibility of microservices models and the scalability of Kubernetes technology on an analytical sheet developed on R and Python, then, the system architecture is presented. This architecture generates an ecosystem with a series of characteristics which are highlighted below:

1. Stability: System based on Load Balancing and Dockers, this allows better management of expected and unexpected processes, it also allows distributing user traffic across multiple instances and thus reduces the risk of experiencing performance problems. Scrum development methodology, which allows for better development management and risk mitigation. Hybrid database, which allows for efficient data management, both for transactional, columnar and multidimensional problems that we face within the smart data model.
2. Scalability: Microsite structure (microservices and micro front ends), this allows focused growth and a platform based on modules. Columnar database allows better response latency and therefore more explanatory information. Structure based on big data model to improve data frequency and/or volume.
3. Security: GDPR-based methodology for compliance with data management and privacy policies. Tokenization system based on Blockchain to ensure data security not only in the system. Encrypted database to ensure data security.
4. Technology: Continuous Development Model for better response in releases and the possibility of customized and staggered developments. Profiling scheme for a better model of customization of views and/or functionalities as well as a unique experience per user type. Data Cleaning is a technique focused on data quality which results in more accurate models and conclusions. Structure of functional (linear) and non-functional (deep learning, AI, etc) models for risk estimation and calculation of prescriptive actions allowing better estimation of models based on the data. Multidimensional data structure for better data interpretation and the possibility of real-time access to aggregated information.
5. Speed: Hybrid DBs to improve processing frequency or processing distribution. Multi-tenant schemes for better and greater user management. Lists and processes in elasticsearch for better performance.
6. Monitoring: system that provides visibility into performance, uptime and overall application status.

Physical and technological information security management

It is worth mentioning, within the system, its architecture based on a scalable and reliable infrastructure. Based on a cloud architecture strongly related to a microservices model both in the front-end and back-end, ALTO Group systems are scalable and high performance, as well as focused on information security based on different tools where it stands out; monitoring, user authentication and encryption and / or tokenization of information depending on the sensitivity of it. Our system controls access by role, account and store, restricting unauthorized access to information not related to your user, in addition, access to information is controlled at the user level and the connection to gcloud (servers and databases). Also, access to network devices is managed through a firewall, authentication is done with Cloud Identity and Access Management (Cloud IAM), which allows managing identity and access control by defining who (identity) has what access (role) to what resource. On the other hand, Alto has defined data privacy policies, which can be consulted in each application and must be accepted in order to use them, and each company collaborator and supplier has signed confidentiality agreements. In addition, the user of the system must know and accept the data privacy policies in order to make use of it.