What approaches and methods are used to increase system throughput and resilience under high load?

Several approaches are used to increase system throughput and stability under high load:

• Scaling: horizontal (adding new servers) and vertical (increasing resources of a single server).
• Asynchronous processing: using message queues (e.g., RabbitMQ, Kafka) to offload synchronous operations.
• Caching: storing frequently requested data in memory (Redis, Memcached) to reduce database load.
• Load balancing: distributing requests among multiple application instances.
• Code and query optimization: reducing response time through efficient algorithms and database indexes.
• Using connection pools for databases and other resources.

Example in Python using asynchronous approach and queue:

import asyncio
from aio_pika import connect_robust, Message

async def send_message():
    connection = await connect_robust("amqp://guest:guest@localhost/")
    channel = await connection.channel()
    await channel.default_exchange.publish(
        Message(b"Hello World!"), routing_key="task_queue")
    await connection.close()

asyncio.run(send_message())