SeMA Deployment Architecture
Last updated
Last updated
Odoo follows a multi-tier architecture, and we can identify three main tiers: Data, Logic, and Presentation:
The Data tier is the lowest-level layer, and is responsible for data storage and persistence. Odoo relies on a PostgreSQL server for this. PostgreSQL is the only supported RDBMS, and this is a design choice. So, other databases such as MySQL are not supported. Binary files, such as attachments of documents or images, are usually stored in a filesystem.
The Logic tier is responsible for all the interactions with the data layer, and is handled by the Odoo server. As a general rule, the low-level database should only be accessed by this layer, since it is the only way to ensure security access control and data consistency. At the core of the Odoo server, we have the Object-Relational Mapping (ORM) engine for this interface. The ORM provides the application programming interface (API) used by the addon modules to interact with the data.
The Presentation tier is responsible for presenting data and interacting with the user. It is implemented by a client responsible for all the user experience. The client interacts with the ORM API to read, write, verify, or perform any other action, calling ORM API methods through remote procedure calls (RPCs). These are sent to the Odoo server for processing, and then the results are sent back to the client for further handling.
Ingress Controller: NGINX is web serving, reverse proxying, caching, load balancing, media streaming, and more. It started out as a web server designed for maximum performance and stability. In addition to its HTTP server capabilities, NGINX can also function as a proxy server for email (IMAP, POP3, and SMTP) and a reverse proxy and load balancer for HTTP, TCP, and UDP servers Redis Server: Redis , is a fast, open source, in-memory, key-value data store , All Redis data resides in memory, which enables low latency and high throughput data access. Unlike traditional databases, In-memory data stores don’t require a trip to disk, reducing engine latency to microseconds. Because of this, in-memory data stores can support an order of magnitude more operations and faster response times. The result is blazing-fast performance with average read and write operations taking less than a millisecond and support for millions of operations per second. BI Tool [ MetaBase - SuperSet ]: Business intelligence (BI) tools are types of application software which collect and process large amounts of unstructured data from internal and external systems, including books, journals, documents, health records, images, files, email, video and other business sources
Sizing for performance and load requirements is an iterative process that estimates the number of CPUs and corresponding memory required to support the services in the deployed system. When estimating the number of CPUs required to support a service, consider the following:
Use cases and corresponding usage analysis that apply to the service
System requirements determined during analysis for technical requirements
Past experience with the Odoo System components providing the service
The process of sizing for performance typically consists of the following steps. The ordering of these steps is not critical—it simply provides a way to consider the factors that affect the final result.
Determine a baseline CPU estimate for components identified as user entry points to the system.
Make adjustments to the CPU estimates to account for dependencies between components.
Make adjustments to the CPU estimates to reflect security, availability, scalability, and latent capacity requirements.
