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How We Built a Distributed System for Handling Billions of Requests Per Day(hyperscale.io)

320 points by sysadmin64 1 year ago | flag | hide | 16 comments

  • john_doe 1 year ago | next

    Great post! I've been wondering how these high-traffic systems handle such a large volume of requests. Looking forward to the details.

    • admin 1 year ago | next

      Hi John, glad you found the post interesting! We'll be answering some FAQs and explaining the architecture decisions and technologies we used.

      • user111 1 year ago | next

        In general, what programming languages and tools did you use in building the system?

        • admin 1 year ago | next

          Our system is built on a combination of Go, Prometheus, and etcd with Kubernetes for container orchestration.

    • jane_does 1 year ago | prev | next

      How do you ensure that the system remains stable and fault-tolerant under such extreme traffic?

      • admin 1 year ago | next

        We implemented health checks, load balancers, and auto-scaling to manage load and reduce the chance of failure.

      • john_doe 1 year ago | prev | next

        That's interesting, could you elaborate more on load balancing strategies used?

        • admin 1 year ago | next

          Of course! We use round-robin and IP-hash algorithms to distribute requests among multiple servers based on available resources.

    • jane_does 1 year ago | prev | next

      Thanks for sharing your experience. I appreciate all the details on how you built this system!

  • user222 1 year ago | prev | next

    I'd love to know more about how your caching layer works and why you picked that technology.

    • admin 1 year ago | next

      We use Redis as our caching layer for its performance and ease of use. It helps reduce latency and improve our ability to handle requests.

    • user111 1 year ago | prev | next

      This is helpful insight, thanks for your answers!

  • jane_does 1 year ago | prev | next

    How do you monitor your system for potential issues and performance tuning?

    • admin 1 year ago | next

      We use Prometheus and Grafana for monitoring and visualizing key performance indicators and improving our system.

  • user333 1 year ago | prev | next

    What's your approach when it comes to data consistency and availability trade-offs?

    • admin 1 year ago | next

      We prioritize eventual consistency over strong consistency, which allows for availability and faster read times while keeping data updates within an acceptable delay.