What is LOC For?
Understand the purpose and vision behind LOC's design.
Data Integration
The primary purpose of LOC is to deploy and execute user's data processes or data pipelines. These pipelines can be triggered by a source (event-driven) or scheduled as batch jobs, run as a task and output a result, integrating new and legacy data systems across an organisation.
Related keywords:
- ETL (Extract, Transform, Load)
- Reversed ETL
- Data Streaming
Data Virtualisation
The data processes can also be referred as data products, one of the four principle of the Data Mesh architecture. The data processes can form a data middleware and data catalogue layer across the organisation, connecting all data islands and greatly reduce the cost to locate data.
Related Keywords:
- Data Fabric
- Data Catalogue
Logic Modularisation
A data process is consisted of a series of logic, a reusable code module for handling a specific part of a business logic. The logics serve as the building blocks of data processes, avoiding the additional development time for reinventing the wheel.
Anyone in the organisation can contribute their logic
Related Keywords:
- Modular Programming
- DDD (Domain-Driven Design)
Cloud Migration And Service Integration
LOC is a Kubernetes-based solution and can be deployed on many public or private clouds across physical or virtual servers. Compared to building a microservice architecture from the ground-up, it will be much easier to adopt LOC and quickly migrate business logic to the cloud - including as the cloud replacement for ESB (Enterprise Service Bus) hubs and SOA (Service-Oriented Architecture) services.
Related keywords:
- Container Orchestration
- Microservice Architecture
- ESB (Enterprise Service Bus)
Serverless and CI/CD-less Deployment
In many ways all LOC logic are deployed pretty similar to Amazon Lambda or Google Functions, although you do not need to spend dozen of minutes create and deploy a container for each of them. A data process can be deployed and executed in no time without setting up a CI/CD (Continuous Integration/Continuous Deployment) workflow.
LOC data processes do not have cold-start delays like FaaS. The only time required to wait is to compile each logic beforehand.
Related keywords:
- FaaS (Function as a Service)
- Self-serve Platform
Active Metadata Management
A data process is capable to log metadata on its own, which are valuable for generating data lineage and can be used for data auditing and data governance purposes.
Related keywords:
- Business or Descriptive Metadata
- Log- or Runtime-based Lineage