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World Congress 2023 • Oct 23, 2023

From 0 to 1.000.000: How to build a serverless raffle service for hyperscale

Marco Plaul , Martin Sakowski

Synchronous serverless APIs fail during extreme traffic spikes. Learn how a store-first architecture decoupling API Gateway and SQS effortlessly scales past 100,000 requests per second without upfront provisioning.

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#1 about 4 min

Overcoming traffic burst challenges in hyperscale web applications

Unexpected traffic spikes require robust architectures capable of processing millions of concurrent user registrations seamlessly.

#2 about 6 min

Analyzing concurrency bottlenecks in standard serverless architectures

Synchronous architecture patterns struggle to scale instantly due to default account quotas and burst concurrency limitations.

#3 about 2 min

Addressing synchronous invocation flaws between API Gateway and Lambda

One-to-one synchronous lambda invocations for initial requests rapidly exhaust account concurrency and reduce database write efficiency.

#4 about 3 min

Decoupling frontend requests using Amazon SQS integrations

Direct service integrations capture high-volume API requests into a buffer queue to prevent immediate backend overload.

#5 about 2 min

Processing queue messages efficiently with event source mapping

Batching queue messages into single lambda invocations drastically minimizes compute concurrency and optimizes database write operations.

#6 about 5 min

Configuring distributed load testing for serverless applications

Leveraging distributed functions to simulate extreme traffic scenarios helps validate upstream infrastructure configurations prior to launch.

#7 about 5 min

Monitoring backend ingestion during a simulated traffic burst

Live telemetry dashboards reveal how queueing mechanisms effectively absorb millions of incoming requests without dropping data.

#8 about 2 min

Best practices for implementing durable hyperscale serverless systems

Building asynchronous workflows and proactively managing resource quotas ensures reliable application stability during critical high-traffic business events.

#9 about 5 min

Navigating caching and downstream throttling in event-driven setups

Accommodating immediate client feedback requirements necessitates fast caching layers while exponential backoff configurations safeguard vulnerable legacy downstream components.

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