Microsoft Certified: DevOps Engineer ExpertImplement a Site Reliability Engineering (SRE) strategyMedium
A DevOps team is designing an SRE strategy for a new critical IoT platform on Azure that processes millions of telemetry data points per second. They need to ensure that the data ingestion pipeline can tolerate transient failures without data loss and without overwhelming downstream services. Which architectural pattern should they incorporate into their ingestion pipeline to achieve this resilience and flow control?
- ACompeting Consumers Pattern
- BQueue-Based Load Leveling Pattern
- CPublisher-Subscriber Pattern
- DRequest-Reply Pattern
Show answer & explanationAnswer & explanation
Correct answer: B. Queue-Based Load Leveling Pattern
The Queue-Based Load Leveling pattern uses a message queue to buffer requests between a producer and consumer. This prevents the consumer from being overwhelmed by spikes in load, tolerates transient failures, and ensures data is not lost, aligning perfectly with the requirements for an IoT ingestion pipeline.
Why the other options are wrong
- A. Competing Consumers allows multiple consumers to process messages from a single queue, which is a component of the solution but not the pattern for load leveling itself.
- C. Publisher-Subscriber decouples senders from receivers, but doesn't inherently provide load leveling or prevent overwhelming downstream services without an underlying queue.
- D. Request-Reply is a synchronous communication pattern, not suitable for high-volume, asynchronous, failure-tolerant ingestion.
Queue-Based Load Leveling
An architectural pattern that uses a message queue as a buffer between service components to smooth out intermittent heavy loads and prevent downstream services from being overwhelmed.
- Decouples producers from consumers.
- Provides resilience by buffering messages during transient failures.
- Manages spikes in demand, preventing resource exhaustion.
Memory trick: Queue-Based Load Leveling: A queue to smooth out the waves of requests.