Application Component Checklist

A detailed reference checklist to ensure every critical aspect of an application is designed, built, and maintained effectively.

Core Application Components (Detailed)

  1. User Interface (UI)
    • Description: The UI is the layer through which users interact with the system, combining layout, design, and interaction flows.
    • Applications: Web portals, mobile apps, dashboards, kiosks, and embedded device interfaces.
    • Best Practices: Responsive design, accessibility (WCAG 2.1), consistent navigation, intuitive icons, and clear visual hierarchy.
    • Challenges: Balancing aesthetics and usability, ensuring accessibility for all users, managing cross-device consistency, and maintaining performance with complex visuals.
    • Tools & Techniques: Figma, Sketch, Adobe XD, React/Vue UI frameworks, Bootstrap, Tailwind CSS, ARIA for accessibility, usability testing.
  2. Authentication & Authorization
    • Description: Mechanisms to verify identity (authentication) and assign permissions (authorization).
    • Applications: Secure login for apps, access restrictions in enterprise systems, API key validation, cloud IAM services.
    • Best Practices: Use strong password hashing (bcrypt/Argon2), implement MFA, adopt RBAC/ABAC, session management with JWT or OAuth 2.0.
    • Challenges: Preventing brute force attacks, managing session expiration, ensuring smooth user experience while enforcing strict security.
    • Tools & Techniques: Auth0, Okta, Firebase Auth, Keycloak, JWT libraries, OAuth 2.0, OpenID Connect, PAM for enterprise systems.
  3. API Layer
    • Description: A communication bridge that exposes application functionalities to external or internal consumers.
    • Applications: REST/GraphQL APIs for web/mobile apps, microservices communication, public APIs for third-party integration.
    • Best Practices: Version APIs, provide OpenAPI/Swagger documentation, enforce throttling and rate limiting, secure with API keys or OAuth.
    • Challenges: Handling backward compatibility, preventing misuse (API abuse/DDoS), monitoring usage and scaling.
    • Tools & Techniques: Postman, Swagger/OpenAPI, GraphQL, Kong API Gateway, Apigee, rate limiting libraries, API monitoring tools.
  4. Data Layer
    • Description: The storage and retrieval component for structured, semi-structured, or unstructured data.
    • Applications: Relational databases (MySQL, PostgreSQL), NoSQL (MongoDB, Redis), file storage, data lakes.
    • Best Practices: Normalize where appropriate, use indexing for performance, enable encryption at rest and in transit, implement regular backups.
    • Challenges: Ensuring scalability for large datasets, handling distributed data consistency, avoiding single points of failure.
    • Tools & Techniques: MySQL, PostgreSQL, MongoDB, Redis, Cassandra, Hadoop, Spark, backup & replication tools, database monitoring (Percona, pgAdmin).
  5. Business Logic
    • Description: The core rules and workflows that drive how the application processes data and delivers value.
    • Applications: E-commerce cart calculations, banking transaction validation, workflow automation in enterprise apps.
    • Best Practices: Keep business logic isolated, use design patterns (Strategy, Factory, Observer), write comprehensive test coverage, document workflows.
    • Challenges: Avoiding code duplication, keeping logic adaptable to business changes, ensuring maintainability in large codebases.
    • Tools & Techniques: UML diagrams, BPMN modeling tools, unit/integration testing frameworks (JUnit, PyTest), design pattern libraries, workflow engines like Camunda or Zeebe.
  6. Logging & Monitoring
    • Description: Processes that capture application events, errors, and performance metrics for visibility and troubleshooting.
    • Applications: Centralized logging with ELK, monitoring uptime with Prometheus/Grafana, alerting via Datadog or PagerDuty.
    • Best Practices: Use structured logs, correlate logs with request IDs, set up automated alerts for anomalies, monitor SLAs.
    • Challenges: Handling log volume at scale, ensuring privacy in logs (masking sensitive data), preventing alert fatigue.
    • Tools & Techniques: ELK Stack (Elasticsearch, Logstash, Kibana), Graylog, Prometheus, Grafana, Datadog, Splunk, structured logging libraries (Winston, Log4j).
  7. Security
    • Description: Safeguards that protect the application, data, and users from threats and vulnerabilities.
    • Applications: Web application firewalls (WAF), penetration testing, vulnerability scanning, SSL/TLS encryption.
    • Best Practices: Follow OWASP guidelines, apply principle of least privilege, enforce secure coding practices, run regular audits.
    • Challenges: Staying updated against evolving threats, dependency vulnerabilities, balancing security with usability.
    • Tools & Techniques: OWASP ZAP, Burp Suite, Nessus, Qualys, WAFs (AWS WAF, Cloudflare), static code analyzers, SSL/TLS libraries.
  8. Deployment & CI/CD
    • Description: Processes and pipelines that automate building, testing, and releasing applications.
    • Applications: Jenkins, GitHub Actions, GitLab CI, cloud-native pipelines on AWS, Azure, or GCP.
    • Best Practices: Automate builds/tests, use infrastructure as code (Terraform, Ansible), adopt canary/blue-green deployments, ensure rollback mechanisms.
    • Challenges: Managing environment consistency (dev/staging/prod), minimizing downtime, handling failed deployments safely.
    • Tools & Techniques: Jenkins, GitHub Actions, GitLab CI/CD, CircleCI, Travis CI, Docker, Kubernetes, Terraform, Ansible, Helm charts.