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.