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The Expertise Required for Effective Solution Architecture

1. Expertise in designing Restful apis and Microservices

  • Restful APIS are application programming interfaces that adhere to principles of representational state transfer, allowing different systems to communicate over HTTP. Mastery in designing them invoves understanding HTTPs method ( Get, Post, Put, Delete) status codes, and how to structure API endpoints effectively.
  • Microservices are an architectural style that structures an application as a collection of loosely coupled services. Each service is responsible for a specific function and can be developed, deployed, and scaled independently.

2. Solid Knowledge of Databases (SQL and NoSQL)

  • SQL( Structured query language) databases, like Mysql and PostgreSQL, are relational databases that use structured schemas and tables to organize data. Proficiency involves understanding how to design schemas write complex queries, and manage transactions.
  • NoSql databases, Like MongoDB and Cassandra, provide flexible schemas and are designed for unstructured or semi-structured data. Understanding their use cases, data models, and querying mechanisms is essential.

3. Understanding of cloud Computing (AWs, Azure,GCP)

  • Cloud computing refers to delivering various services over the internet, including storage, processing power, and applications. Familiarity with platforms like AWS(Amazon web services), Azure, and GCP( Google Cloud Platform) Involves knowing theirs core services. deployment models, and how to leverage them for scalable solutions.

4. Understanding of DevOps and CI/CD Practices

  • DevOps is a set of practices that combines software development(Dev) and It Operations(Ops) to shorten the systems development life cycle. Knowledge of CI/CD ( Continuous Integration/ Continuous deployment) involves automating the process of code intergration, testing, and deployment to improve software delivery efficiency and reliability

5. Mastery of distributed system design principles

  • Distributed systems are systems that run on multiple computers but appear as a single coherent system to users. Knowledge in this area inclucde understanding concepts like scalability, fault tolerance, load balancing, and data consistency in distributed evironments.

6. Knowledge of big data management and modern data processing

  • Big Data Management involves handling and analyzing large volumes of data that traditional databases cannot manage efficiently. Familiarity with technologies like Hadoop, Spark, And data lakes is essental for processing and extracting insights for big data

7. Understanding of software design pattern and architectures

  • Design Patterns are general reusable solutions to common problems in sofware design. Knowing various solutions to common problems in software design. Knowing various design patterns(e.g Singleton, Observer, Factory) help create scalableand maintainable code
  • Software architecture refers to the high-level structure of software systems. Understanding different architectural styles(e.g, monolithic, microservices, event-driven) is crucial for designing system that meet specific requirements

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