🍔🧠 How AWS Lambda Serves Trillions on Requests a Month

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📚 Software Engineering Articles

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🗞️ Tech and AI Trends

• Chinese AI agent Manus sparks global debate

• OpenAI's new API revolutionizes AI agent development

• AirPods to feature real-time translation

👨🏻‍💻 Coding Tip

• Use the __slots__ attribute in Python

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How AWS Lambda processes trillions of requests per month ⚡

AWS Lambda processes tens of trillions of monthly invocations across 1.5M+ active customers. The service has evolved sophisticated techniques to handle massive scale while maintaining performance and isolation between tenants.

The challenge:
Managing billions of asynchronous requests while preventing noisy neighbors from impacting other tenants and maintaining system stability during traffic spikes and component failures.

Implementation highlights:

• Uses shuffle-sharding to distribute tenants across multiple queues, minimizing the blast radius of noisy neighbors

• Implements proactive detection and automated isolation of high-traffic tenants to dedicated queues

• Maintains resilience through processing backlogs during outages and controlled recovery with load shedding

• Provides detailed observability through metrics like AsyncEventAge and AsyncEventDropped for monitoring

Results & Learnings:

• Shuffle-sharding with 100 queues and 2 queues per tenant creates 4,950 unique combinations, giving only a 0.02% chance of tenant overlap

• The system automatically detects and isolates traffic spikes to dedicated queues while maintaining overall stability

• Load shedding during recovery ensures fair resource allocation and improves mean time to recovery

Pro tip: Monitor key metrics and configure failure handling through destinations/DLQs to avoid data loss 😉

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🤖 Manus: China's New AI Agent Goes Viral, Sparking Global Debate (3 min)

Brief: Manus, a new autonomous AI agent from China, is impressing early testers with its ability to complete complex tasks rapidly, raising questions about AI leadership and the future of human-machine collaboration.

💻 Claude Code: A Fun Yet Pricey Experiment in Coding (3 min)

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🤖 OpenAI Unveils New Developer API to Enhance AI Agent Capabilities (3 min)

Brief: OpenAI launches the Responses API to empower developers in creating autonomous AI agents, aiming to fulfill the vision of AI joining the workforce by 2025.

🤖 Google Unveils Gemini Robotics for General Purpose Robots (3 min)

Brief: Google introduces Gemini Robotics, aiming to create general purpose robots that can adapt, interact, and perform complex tasks using advanced AI models.

🎧 Apple Introduces Live Translation Feature for AirPods in iOS 19 (2 min)

Brief: Apple is set to launch live translation for AirPods with iOS 19, enabling real-time conversation translations, a feature already available in Google's Pixel Buds since 2017.

This week’s coding challenge:

This week’s tip:

In Python, the __slots__ attribute can be used to explicitly declare data members in a class, which can significantly reduce memory usage and improve attribute access speed. By using __slots__, you prevent the creation of a __dict__ for each instance, which is especially beneficial when dealing with a large number of instances.

Wen?

• Memory Optimization: Ideal for classes that will have a large number of instances, as it reduces the memory footprint by preventing the creation of a __dict__ for each instance.

• Performance Improvement: Useful in scenarios where attribute access speed is critical, as __slots__ provides faster attribute access compared to the default __dict__-based attribute lookup.

• Immutable Data Structures: Beneficial when you want to enforce a fixed set of attributes, preventing the dynamic addition of new attributes at runtime, which can help in maintaining a more predictable and controlled class structure.

“When one door of happiness closes, another opens, but often we look so long at the closed door that we do not see the one that has been opened for us."
Helen Keller

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