The hottest Fault Tolerance Substack posts right now

Learn about using Async communication and messaging patterns
Understand how AWS services like SQS, SNS, and EventBridge aid in system recovery and design
Discover AWS WAF's role in error prevention and coding patterns for fault tolerance

Use Dead Letter Queue (DLQ) to recover from failures and get notified in fault tolerant systems.
Set up DLQ with two queues - Original for processing messages and DLQ to capture failed messages for retries.
Implement monitoring for DLQ growth to alert on-call engineers and prevent issues from affecting customers.

Avoid having gatekeepers in your release cycle to reduce costs and improve organizational efficiency.
Challenge bad processes and strive for daily value delivery to engineers and users.
Embrace DevOps principles like automation, collaboration, and continuous testing for faster, high-quality software delivery.

Consider using FIFO queues in AWS for order processing to ensure messages are processed in the right order and avoid duplicates.
Re-design solutions to leverage asynchronous communication over synchronous for a more resilient system.
Implement retry mechanisms and explore Dead Letter Queues to handle failures and define thresholds for message processing.

Building reliable systems in an unreliable world is crucial for the success of products and services.
Failures in distributed systems can lead to challenges like duplicate transactions, but idempotent APIs can help ensure consistency.
Idempotent APIs are key in guaranteeing data integrity, simplifying error handling, and enhancing fault tolerance in distributed systems.

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A distributed system is a collection of components on multiple computers that appear as a single, unified system to users. They are commonly used in database and file systems.
Key characteristics of distributed systems include concurrency, scalability, fault tolerance, and decentralization, enabling efficient operation across multiple machines.
In distributed systems, concepts like fault tolerance, recovery & durability, the CAP theorem, and quorums & consensus are crucial for maintaining reliability, consistency, and coordination among nodes.