As part of this project, it is necessary to implement a scalable architecture based on a NoSQL storage solution. The main focus should be on the features of building a fault-tolerant cluster infrastructure, replication and sharding mechanisms, as well as the possibilities of integrating the solution into an infrastructure with high availability and horizontal scalability requirements. The document should contain both technical implementation details and an overview of application scenarios.
1. Architecture
1.1 Architectural Diagram and Description
The diagram of the current architecture of the solution is presented with explanations of the key components.
1.2 Configuration Features
1.2.1 CAP Theorem
Analysis of trade-offs between availability, consistency, and partition tolerance.
1.2.2 Cluster
Description of the clustering logic and the goals of the chosen configuration.
1.2.3 Nodes
Justification of the number of nodes and their role in ensuring fault tolerance.
1.2.4 Sharding
Approach to horizontal data distribution and segmentation logic.
1.2.5 Replication
Mechanisms for backup and synchronous/asynchronous replication.
1.2.6 Data Preservation
Working with long-term storage and ensuring integrity in case of failures.
1.2.7 Data Distribution
Overview of data routing algorithms and interactions between nodes.
1.2.8 Security
Aspects of authorization, authentication, and perimeter protection.
2. Functional Solution
2.1 Structure
Description of the organizational structure of the project and the logic of component placement.
2.2 Installation
Step-by-step instructions for deployment and automation using Docker and docker-compose.
3. Application Scenarios and Case Studies
Three case studies demonstrate the practical application of the solution: from analytics to working with large volumes of streaming data.
4. Advantages and Limitations
A brief technical and strategic analysis of the platform's capabilities compared to alternatives.
5. Additional Features
Unique aspects of implementation that distinguish the project from standard solutions are considered.
6. Data
Description of three datasets used for testing and analysis. One of the datasets contains over 5,000 records, allowing for scalability testing.
7. Queries
A collection of 30 advanced queries addressing real tasks: aggregation, filtering, working with time series, and nested structures.
8. Conclusion
Overview of achieved results, potential scaling directions, and limitations of the current approach.
9. Resources
A list of technical and methodological sources used in the implementation.
10. Attachments
