Frontend architecture, navigation, state management, and design system diagrams map out the client-side experience. Below is an exhaustive guide explaining each frontend diagram along with visual examples and specific use cases. Part 1: Component Architecture & Structure (Arquitetura e Estrutura de Componentes) 1. Component Tree Diagram (Diagrama de Árvore de Componentes) Explanation: A hierarchical layout...Read More
Database architecture and design diagrams are categorized into performance mapping, query structures, data flows, conceptual/logical models, physical layouts, and NoSQL models. Below is an exhaustive guide explaining each database diagram along with visual examples and specific use cases. Part 1: Execution & Performance Mapping (Mapeamento de Execução e Performance) 1. Execution Plan / Query Tree...Read More
Unified Modeling Language (UML) is a standardized general-purpose modeling language in the field of software engineering. UML diagrams are divided into two main categories: Structural Diagrams (representing the static aspect of the system) and Behavioral Diagrams (representing the dynamic aspect of the system). Below is a complete guide to all structural and behavioral UML diagrams,...Read More
In Jira, requirements and work items are structured within a hierarchical model designed to break down high-level business goals into manageable, executable developer tasks. Yes, an Epic is typically the largest standard entity in Jira’s default hierarchy, and the breakdown flows down to Tasks (and further down to sub-tasks). Here is the complete hierarchy from...Read More
In this post we’re going to compare human manual coding with AI generated code for the same problem. We’re going to use the platform Codility as the vendor of the problem. Here’s the link of the problem that we’re going to solve: https://app.codility.com/programmers/lessons/1-iterations/ 1. Human generated code // you can write to stdout for debugging...Read More
The primary service you would use for periodic, automated execution of an ML workflow within the SageMaker ecosystem is SageMaker Pipelines or, for simpler scheduling, a combination of Amazon EventBridge (the scheduler) and SageMaker Processing Jobs or Training Jobs (the executor). Here is a breakdown of the three best ways to achieve this, from simplest...Read More
Amazon SageMaker is a powerful, fully managed service provided by Amazon Web Services (AWS) that is designed to help data scientists and developers quickly and easily build, train, and deploy machine learning (ML) models at scale. It essentially simplifies and automates many of the labor-intensive tasks throughout the entire ML lifecycle, from data preparation all...Read More
SOAP (Simple Object Access Protocol):💡 Description: A protocol for exchanging structured information in web services. It relies on XML for message format and usually operates over HTTP or SMTP.🔦 Use Cases: Enterprise-level applications requiring high security and transactions, such as banking and payment processing.REST (Representational State Transfer):💡Description: An architectural style that uses HTTP requests to...Read More
Building scalable microservices requires the right set of tools to ensure seamless communication, security, and deployment. This guide covers the core technologies used in microservices architecture.1. DatabasesSQL databases like MySQL and PostgreSQL ensure structured data management, while NoSQL options like MongoDB and Cassandra offer scalability for unstructured data.2. Message BrokersKafka, RabbitMQ, and Amazon SQS enable...Read More
1. Orchestration: Think of this as the conductor of an orchestra. It’s all about centralized control and coordination, perfect for managing complex, distributed systems.2. CQRS (Command Query Responsibility Segregation): This one’s a mouthful! It’s about separating how you read data from how you write it. Great for performance optimization.3. Layered (n-tier): The classic approach. It’s...Read More
