Version 1.0 | Date: 03-01-24
The Software Development Lifecycle (SDLC) is a systematic process for planning, creating, testing, deploying, and maintaining software applications. In the Engineering department of your technology/software company, the SDLC is likely to involve several key phases:
By adopting these methodologies and following the SDLC phases, your Engineering department can efficiently deliver high-quality software while being adaptable to changing requirements. Regular communication and collaboration are crucial to the success of this process.
Version 1.0 | Date: 03-01-24
Design patterns are reusable solutions to common problems encountered in software design. They represent best practices and provide a way to design flexible and maintainable software systems. These patterns help developers communicate, understand, and leverage proven solutions to recurring design challenges.
This document presents a simple overview of five fundamental design patterns in Java. Each pattern is accompanied by a brief explanation of its purpose, benefits, common use cases, and a basic example in Java. While these examples offer a glimpse into the world of design patterns, it's important to note that design patterns are extensive, and their application can vary based on the context of a specific problem.
Design patterns categorise solutions to problems based on the relationships between objects, emphasising flexibility, scalability, and maintainability. Developers often use a combination of design patterns to address different aspects of a software system, making it more robust and adaptable to change.
This introductory guide aims to inspire curiosity and encourage further exploration into the rich landscape of design patterns. For an in-depth understanding, consider referring to the classic book "Design Patterns: Elements of Reusable Object-Oriented Software" by Erich Gamma, Richard Helm, Ralph Johnson, and John Vlissides, often referred to as the "Gang of Four" (GoF) book.
Purpose: Ensures a class has only one instance and provides a global point of access to it.
Benefits: Efficient resource utilisation, centralised instance management.
Common Use Cases: Database connections, logging systems.
public class Singleton {
private static Singleton instance;
private Singleton() {}
public static Singleton getInstance() {
if (instance == null) {
instance = new Singleton();
}
return instance;
}
}
Source: Singleton Design Pattern in Java
Purpose: Defines an interface for creating an object but leaves the choice of its type to the subclasses.
Benefits: Encapsulates object creation, promotes code flexibility.
Common Use Cases: GUI frameworks, document processing libraries.
interface Product {
void operation();
}
class ConcreteProduct implements Product {
@Override
public void operation() {
System.out.println("ConcreteProduct operation");
}
}
Source: Factory Method Design Pattern in Java
Purpose: Defines a one-to-many dependency between objects so that when one object changes state, all its dependents are notified.
Benefits: Promotes decoupling, enhances maintainability.
Common Use Cases: Event handling systems, GUI frameworks.
import java.util.HashSet;
import java.util.Set;
interface Observer {
void update();
}
Source: Observer Design Pattern in Java
Purpose: Attaches additional responsibilities to an object dynamically without altering its structure.
Benefits: Enhances flexibility, supports open/closed principle.
Common Use Cases: Input/output stream processing, GUI components.
interface Component {
void operation();
}
class ConcreteComponent implements Component {
@Override
public void operation() {
System.out.println("ConcreteComponent operation");
}
}
Source: Decorator Design Pattern in Java
Purpose: Defines a family of algorithms, encapsulates each one, and makes them interchangeable.
Benefits: Promotes code flexibility, enhances maintainability.
Common Use Cases: Sorting algorithms, payment processing strategies.
interface Strategy {
void execute();
}
class ConcreteStrategyA implements Strategy {
@Override
public void execute() {
System.out.println("ConcreteStrategyA execution");
}
}
Source: Strategy Design Pattern in Java
Version 1.0 | Date: 03-01-24
This troubleshooting guide aims to assist developers in identifying and resolving common issues encountered in the codebase. It covers a range of problems, from build failures to runtime errors and integration issues.
Before diving into troubleshooting, ensure that you have:
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This troubleshooting guide serves as a comprehensive resource for resolving common codebase issues. Following the outlined steps and best practices will help developers diagnose and address issues efficiently, contributing to a more stable and reliable codebase. Regularly update this guide to include new issues and solutions as the codebase evolves.
Version 1.0 | Date: 03-01-24
Logging and monitoring are integral components of our engineering codebase, providing insights into system behavior, identifying errors, and ensuring optimal performance. This documentation outlines the practices, tools, and guidelines for implementing effective logging and monitoring strategies.
Our codebase implements various logging levels (e.g., DEBUG, INFO, WARN, ERROR) to categorise log messages based on their importance and severity.
Consistent log formatting ensures readability and ease of analysis. Standardised formats include timestamp, log level, and relevant contextual information.
Incorporating contextual information in logs, such as user IDs or transaction IDs, aids in tracing and debugging.
All exceptions are logged with detailed information, including stack traces and relevant variables.
We utilise [Logging Framework] for structured and efficient log management. Key aspects include configuration, codebase integration, and log storage with rotation policies.
Performance metrics include response time, throughput, resource utilisation, and database query performance.
We track availability through endpoint monitoring, ensuring timely alerts for downtime or degraded performance.
Security events, such as login failures or unauthorised access attempts, are monitored to safeguard against potential threats.
We use [Performance Monitoring Tool] to capture, analyse, and visualise key performance metrics. Configuration involves specifying metrics, setting sampling intervals, and integrating with the codebase.
[Availability Monitoring Tool] helps in real-time endpoint monitoring, downtime detection, and notification setup for rapid response.
Our security monitoring tool analyses logs for suspicious activities, triggers alerts, and facilitates incident response planning.
Regularly review common log entries to identify patterns and potential issues.
Efficiently pinpoint errors and warnings by leveraging log levels and contextual information.
Use performance metrics to identify bottlenecks and optimise system efficiency.
Define critical events and configure alerts for immediate attention.
Implement threshold-based alerts for performance metrics and availability checks.
Integrate with communication channels like Email, Slack, or PagerDuty for timely notifications.
Conduct regular reviews to identify improvements and address emerging issues.
Ensure collaboration between development and operations teams for comprehensive monitoring and issue resolution.
Adopt a mindset of continuous improvement, updating logging and monitoring strategies as the application evolves.
Address common logging issues, such as misconfigurations or inconsistent log formats.
Refine monitoring thresholds to reduce false positives and optimise alerting.
Scale logging and monitoring systems as the application grows, considering increased data volume and system complexity.
Effective logging and monitoring are essential for maintaining a robust and reliable system. Regularly review and optimise these practices to ensure the continued success of our engineering codebase.
As our codebase evolves, continue to optimise and adapt logging and monitoring strategies to meet changing requirements and challenges.