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Kafka's parallel processing depends on partitions, not just consumers or threads.

Connection pooling reuses database connections but can cause issues if misconfigured.

Distributed locks ensure only one server performs a task, avoiding duplication.

Kafka consumers can use multiple threads to speed up message processing, but it complicates ordering and offset management.

Consistency models determine what data reads in distributed systems can see.

Synchronous replication waits for confirmation from replicas, while asynchronous allows faster writes without waiting.

The retry pattern helps systems recover from temporary failures but can cause overload if misused.

Kafka can help ensure messages are processed once, but requires careful design.

In distributed systems, timestamps don't always reflect the true order of events.

Message queues allow services to communicate asynchronously, improving scalability and reliability.

The Transactional Outbox Pattern ensures database updates and event publishing are synchronized to avoid losing events.

Cache breakdowns can overwhelm databases, but request coalescing solves this issue.

Queues distribute tasks to one consumer, while Pub/Sub broadcasts events to multiple subscribers.

Jitter helps spread out client retries to avoid traffic spikes.

Backpressure helps manage message flow in Kafka during traffic spikes.

The USE Method helps find and analyze infrastructure bottlenecks in software systems.

Distributed backpressure helps manage the flow of work between services to prevent overload.

Availability is about access; reliability is about correct performance.

Choosing the right distributed lock depends on your system's needs and existing tools.

Token Bucket allows burst traffic, while Leaky Bucket smooths out traffic flow.

Microservices can communicate using five key patterns based on their needs.

Exponential backoff helps manage retries by increasing wait times to reduce system overload.

The Bulkhead Pattern isolates resources to protect critical workloads from failures.