Explore the role of error handling in software development, impacting end-users, system integrity, and engineers alike.

We will discuss best practices for building robust error management mechanisms across various system boundaries—from web and API services to background processes and integrations. We will touch on concepts like “fail fast” with practical code examples, common pitfalls to avoid, and security implications.

This presentation will uncover strategies for handling checked and unchecked errors, ensuring resilience in multi-threaded environments and API interactions. As a guest, you will gain insights into error management through real-world examples of preventing potential catastrophes in production systems.

Error Handling Practices:

1. Importance and impact on end-users, system stability, and developers.
2. Strategies for robust error management in web, API, background services, and integrations.

Fail Fast Concept:

1. Practical implementation in error handling.
2. Benefits in improving system reliability and maintenance.

Common Errors and Pitfalls:

1. Understanding and avoiding typical mistakes in error handling.
2. Security implications and best practices.

Checked vs. Unchecked Errors:

1. Handling strategies and implications.
2. Mitigating risks in multi-threaded environments.

Strategies for API Error Handling:

1. Custom errors, throttling, and rate limiting techniques.
2. Ensuring reliability and performance in API interactions.

Error Handling in distributed systems:

1. Best practices and architectural considerations.
2. Real-world scenarios and preventive measures.

Logging for Diagnostics:

1. Role and importance in software error diagnosis.
2. Choosing logging levels (FATAL, ERROR, WARN, INFO, DEBUG, TRACE) and their significance.

Tools and Frameworks:

1. Overview of logging frameworks and tools for distributed systems.
2. Importance of correlation IDs in distributed system logging.

Performance and User Experience Impact:

1. Balancing logging impact on performance and user experience.
2. Strategies to minimize negative effects.

Security Considerations:

1. GDPR compliance and sensitive data redaction techniques in logging.
2. Ensuring data anonymization and avoiding sensitive information leaks.

Event Store and Logging:

1. Concept of event store for maintaining execution paths in logs.
2. Benefits and considerations for long-term solution quality.

Data Mining and Process Optimization:

1. Leveraging log data for process optimization and insights.
2. Practical experiences and strategies for continuous improvement.