Fair: A Go library for serving resources fairly
1–10 of 44 posts
Re: Fair: A Go library for serving resources fairly
#2Very interesting and looking forward to trying this. I am a big fan of SFB for this type of stuff but haven't seen anything in distributed space that's beyond a science project. Would be great if I can use it on my 10k+ user web site.
Re: Fair: A Go library for serving resources fairly
#3Extremely interesting and valuable
Re: Fair: A Go library for serving resources fairly
#4Does anyone have some real-world use cases for something like this? The algorithm is cool but I'm struggling to see where this is applicable.
Re: Fair: A Go library for serving resources fairly
#5Why would you learn and use this over typical load-balancing solutions like K8S? Honest question.
Re: Fair: A Go library for serving resources fairly
#6> Since the state is stored in a multi-level Bloom Filter style data structure, the memory needed is constant and does not scale with the number of clients.
Constant memory, but those hashes will take up CPU cycles. If you're running a workload that completes sub 20 milliseconds, these cycles spent hashing may not be worth it over, say, a constant-time admission control like token bucket.
Re: Fair: A Go library for serving resources fairly
#7Does anyone have some real-world use cases for something like this? The algorithm is cool but I'm struggling to see where this is applicable.
Thinking this could be useful in a multi tenants service where you need to fairly allocate job processing capacity across tenants to a number of background workers (like data export api requests, encoding requests etc.)
Re: Fair: A Go library for serving resources fairly
#8Does anyone have some real-world use cases for something like this? The algorithm is cool but I'm struggling to see where this is applicable.
Thinking this could be useful in a multi tenants service where you need to fairly allocate job processing capacity across tenants to a number of background workers (like data export api requests, encoding requests etc.)
That was my first thought as well. However, in a lot of real world cases, what matters is not the frequency of requests, but the duration of the jobs. For instance, one client might request a job that takes minutes or hours to complete, while another may only have requests that take a couple of seconds to complete. I don't think this library handles such cases.
Re: Fair: A Go library for serving resources fairly
#9Why would you learn and use this over typical load-balancing solutions like K8S? Honest question.
In a multi-tenant system, you might have one customer who drops a big job that creates a huge number of tasks. We'd like to process this as fast as possible, but not block the tasks of small jobs from other customers, which should normally be completed very quickly.
Re: Fair: A Go library for serving resources fairly
#10Earlier quoted context omitted.
Thinking this could be useful in a multi tenants service where you need to fairly allocate job processing capacity across tenants to a number of background workers (like data export api requests, encoding requests etc.)
That was my first thought as well. However, in a lot of real world cases, what matters is not the frequency of requests, but the duration of the jobs. For instance, one client might request a job that takes minutes or hours to complete, while another may only have requests that take a couple of seconds to complete. I don't think this library handles such cases.
defining a unit of processing like duration or quantity and then feeding the algorithm with the equivalent of units consumed (pre or post processing a request) might help.