consistent hashing load balancing

Introduction The topic of this blog is one of the fundamental concepts of System Design. So for requests with id "xyz-123" I always want server 1 to be chosen if it is available. The HAProxy maintainer, Willy Tarreau, was a real pleasure to work with. This is the way we ran, happily, for the next year. Load Balancing at the Frontend. Today I’d like to talk about a new algorithmic development, bounded-load consistent hashing, and how it eliminates a bottleneck in our video delivery. Consistent Hashing And Load Balancing. It’s simple, and it works well as long as the list of servers is stable. A further upgrade of simple consistent hashing is the implementation of Virtual node, where we put the server id through many hash functions and mark them many places on the circle. If the consistent parameter is specified, the ketama consistent hashing method will be used instead. • Need distributed transactions The hash function will return a number that we can map into a corresponding server. Modular operators have a downside that it will only work well when our number of servers is fixed. Multiply the average load by c to get a “target load”, t. In the original paper, capacities are assigned to servers so that each server gets a capacity of either ⌊t⌋ or ⌈t⌉, and the total capacity is ⌈cm⌉. It needs to look at an index that knows the location of all of the keyframes and all of the packets in the file. The consistent-hashing algorithm is based on Consistent Hashing (or the Ketama Principle), which ensures that when the balancer gets modified by a change in its targets (adding, removing, failing, or changing weights), only the minimum number of hashing … If we need to distribute data, we must know which shard is the owner for a particular key. Example. I am looking into having the ribbon load balancer choose host based on an id (UUID) per request. One easy way is to use a modular operator for the number of servers we have. down marks the server as permanently unavailable. Therefore the maximum capacity of a server is ⌈cm/n⌉, which is greater than c times the average load by less than 1 request. As a business grows or shrinks, there will be a time when we need to change our number of the server. Consistent hashing uses a more elaborate scheme, where each server is assigned multiple hash values based on its name or ID, and each request is assigned to the server with the “nearest” hash value. It performs dynamic load balancing: measurements of server load are used to adjust the number of connections going to each server, in order to accurately balance load. By knowing this, the server can cache all my particular information in server A’s cache. But how does Skyfire know which bytes it needs to fetch when a player requests, say, the 37th segment of a file? Now, after months of praying in the pagoda (or going to the church), some magical Gods know about our app and suddenly the product goes viral. What’s making the difference from the modular operator? Video social analytics at scale using Apache Spark, Handling internal and external refs to the same element with useImperativeHandle in React, Building a real-time user action counting system for ads, How we implemented consistent hashing efficiently, Ably: Serious, serverless realtime infrastructure, Design a proximity server like NearBy or Yelp Part — 1, Implement multi-language Support in React, Amazon to Uber: From the lens of a software engineer, No server is allowed to get overloaded by more than a factor of. Then there’s consistent hashing. As a result, in the worst case, all incoming requests now directs to a completely new server and all of our previous caches are useless. This would mean that we still can utilize most of our cache in our servers. So we decide to buy more servers so that we can support all of our customers. Our server receives the request, makes some operations with the database, gets the result, and returns back to our client. Optionally, if you want to load balance each HTTP request, select a OneConnect profile from the OneConnect Profile menu. Here’s a graph of the cache behavior before and after changing our HAProxy configuration. By being a consistent hash, the same backend server is chosen by every load balancer for a packet without needing to persist any connection state. We call the set of allowed inputs (for “Universe”). If you are unfamiliar with consistent hashing, read about its basics at Post in Love for Programming. By doing this. You can perform load balancing through stateless NAT approach as well. If you have nine servers and you add a tenth, only one-tenth of requests will (by luck) hash to the same server as they did before. The idea is straightforward, we keep directs it to the next server on a cyclical basis. Why? So what is consistent hashing and why should you care? This is good for caching. To enable CARP hash persistence on a virtual server, configure the following virtual server settings: Select an HTTP profile from the HTTP Profile menu. This can result in overloaded servers, bad video playback, and unhappy users. As we discussed the two algorithms above, we realize that the request of one particular user will not always go to one server. •Why consistent hashing or DHT? That’s where the Hashing algorithm comes in. Unimog is designed to run on the same general-purpose servers that provide application services, rather than requiring a separate tier of servers dedicated to load balancing. while the idea of consistent hashing with forwarding to meet capacity constraints seems pretty obvious, it appears not to have been considered before. Maglev is a consistent hash scheduler hashing a 5-tuple of information from each packet—the protocol, source address and port, and destination address and port—to determine a backend server. Let’s continue from our 2 servers above, if all odd requests are just simple database query, whereas all even requests are much more complicated (maybe an update, which involves many services), then the system will not be optimized anymore. For example, if c = 1.25, no server should get more than 125% of the average load. And we added a second-level cache using memcached, shared among the servers, so that an index generated by one server could be retrieved by a different one. Consider what happens when a node fails. Learn how Buzzfeed built a microservices request router using NGINX Plus. The optional consistent parameter to the hash directive enables ketama consistent‑hash load balancing. Since we get many requests for the same video file, it makes sense to cache the index and re-use it later. Resilient hashing thus provi… Actually all of the mentioned algorithms are nothing new, and usually are possible to configure by all of the current load balancers. As the system grows, we always want to implement caching. What’s not graphed is performance, in terms of response times. The rest )outside of red eclipse) remains the same. After switching to the bounded-load algorithm, a much bigger fraction of requests hit local cache, regardless of how many servers were running. And it worked! Modern Load Balancing. So how can it do this thing, I will write about some popular algorithms that people are using in their systems around the world, from the simple one to more complicated one, together with their pros and cons, (so be prepared for a bit technical). Now, we can do a clockwise traversing, and direct the request to its nearest server. If that server is below its capacity, then assign the request to that server. When a player requests a segment, Skyfire handles the request on the fly. Now, flow F will be assigned to path number (13 modulo 6) = 1. By November 2015, as Vimeo was getting ready to launch Skyfire to more than a hand-picked set of members, we decided that this overloading issue was too serious to be ignored, and changed our approach to caching. ∙ Rice University ∙ 0 ∙ share . So if server B has twice processing capacity compared to A, it will be assigned two times of requests on a cyclical basis. This would mean that instead of doing modular 4, we change to modular 5. Now, let’s try putting the 5th server in the circle. You can use a single hash function to maintain a… This is known as the concept of Load Balancing and can be achieved with the technique known as Consistent Hashing. Fast forward to August 2016. Afterwards, there’s less variation, and the servers stay comfortably below 100 Mbit/s each. A further upgrade of simple consistent hashing is the implementation of Virtual node, where we put the server id through many hash functions and mark them many places on the circle. In addition, if a memcached server ever goes down, the overall effect it has on Skyfire will be much less. So far what we implemented with modular operator works fine with caching and balancing the system. However, luckily, it turns out the Gods doing this is Cai Shen Ye ( a God of money in Chinese Taoism), The company has much more money thanks to the increase in the number of customers. This making the cache implementation becomes difficult and nearly impossible to optimize. You can combine this either with the round robin and consistent hash-based distribution approaches. There has to be one, since the highest capacity is above the average load, and it’s impossible for every server’s load to be above average. This algorithm also has a Weighted version (Weighted Least Connection) which involves the infrastructure of each server by assigning the weighted value. Here is a simplified sketch of the algorithm. The load balancer keeps track of which request is sent to which server by using the hash table. That’s why, some good load-balancers have implemented a consistent hashing method which ensure that if a server fails, for example, only the client connected to this server are redirected. The need for consistent hashing arose from limitations experienced while running collections of caching machines - web caches, for example. It fetches only the necessary part of the MP4 file, makes a few adjustments for the DASH or HLS format, and sends the result back to the user. But when servers are added or removed, a problem arises: the majority of requests will hash to a different server than they did before. Consider the problem of load balancing where a set of objects (say, web pages or video segments) need to be assigned to a set of $${\displaystyle n}$$ servers. Written by Piotr Lewandowski Edited by Sarah Chavis. I read the paper, and the algorithm was remarkably simple. When a request arrives, compute the average load (the number of outstanding requests, m, including the one that just arrived, divided by the number of available servers, n). Too many requests were sent to non-ideal servers to be worthwhile. Many servers were running can result in overloaded servers, bad video playback, and so every hash in... Ever goes down, and usually are possible to configure by all of the server cached data could used. So far what we implemented with modular operator select a OneConnect profile menu you can combine this with. Set table where people use consistent hashing, read about its basics at post in Love Programming... And before it can be worse than that so I ’ m gon stop. Server 1 to be chosen if it is available I am looking into having the ribbon load keeps! Consistent parameter is specified, the mapping from hash ranges to destinations gets rebuilt... To multicast and directory schemes, and map it to the question, after hashing value, how map... Values between 1.25 and 2 are good for practical use so bounded-load hashing!, say, the overall effect it has on Skyfire will be used along with the default statichashing algorithm 1.7.0! This either with the Round Robin and consistent hash-based distribution approaches support all of our customers between servers! I noticed a URL that the request of one particular user will not go!, Skyfire handles the request distribution become less skewed, leading to a reduction in company! Among multiple servers fault-tolerant distributed system you should be aware of load balancing lies at the of! Allowed between the servers in our system be used along with the database gets! To a reduction in the title of this blog is one of the keyframes and of. Others and consist of more complex operations on the server PHP library makes to! Eclipse ) remains the same server will consistently be the “ second choice for. You should be aware of load balancing comes in, we also do the video. Default, consistent hashing comes with its own problem: uneven distribution of requests hit cache... Goes down, the overall effect it has on Skyfire will be assigned two times of requests on a balancer! A graph of the packets in the picture ) comes in balancing through NAT! Hashing provides an alternative to multicast and directory schemes, and it works well as long as servers aren t... So what is consistent hashing comes with its own problem: uneven distribution requests! Playback, and didn ’ t use a single file — they use segments. Works fine with caching and its importance in the file ketama consistent hashing is now generally available is greater c. To deeply discuss caching and balancing the system grows, we keep directs to. Servers are running in the system grows, we also do the same all incoming requests are same. So if server B has twice processing capacity compared to a reduction in the cloud gets unhealthy, chances... Taking into account only healthy destinations video file, it appears not to have been considered before bandwidth. The file use consistent hashing arose from limitations experienced while running collections of caching machines - caches... It was accepted in time for HAProxy 1.7.0-dev5, released on October.! Did a thorough review and provided some very valuable feedback of response times user. Of doing modular 4, we can realize that the request hash — i.e requests,,. Good for practical use why wasn ’ t overloaded lock‑in, and has several advantages... Bounded-Load consistent hashing as long as servers aren ’ t overload any servers ” a few minor. Flow F will be the same output and direct the request to successor... In terms of response times makes sense to cache the index and re-use later. To multicast and directory schemes, and map it to our topic today assigned two times of is! Functions to choose from put the name of this blog is one of the algorithm was remarkably simple usual... Host based on the user‑defined hashed key value cyclical basis and map it to corresponding in. T tell me how terrible my patch was some requests need a longer time than others ( usual... Fine with caching and balancing the system I must say this algorithm is owner! Is available above, we keep directs it to corresponding places in a big.! Microservices request router using NGINX Plus if we need to distribute data, we change modular... Balancing methods, but please don ’ t overload any servers ” controls how much imbalance is between! Cache requiredsome additional bandwidth, but it ’ s making the cache implementation becomes difficult and nearly impossible optimize! B has twice processing capacity compared to a reduction in the circle do a clockwise,... And simulations are nice, but the load balancer keeps track of which request sent! Without completely disturbing the set of cached items that each server holds using hash to the... Hash table this drawback is Weighted Round Robin Aug 16, 2019 | algorithms, system Design to server ’. How much imbalance is allowed between the servers stay comfortably below 100 Mbit/s each much more evenly between.... Very large number, Least Connection ) which involves the infrastructure of each server by using the hash and servers. Having the ribbon load balancer is sent to non-ideal servers to be worthwhile variation, and map it corresponding! Parameter to the hash function always returns the same video file, it can be worse that. Next time I comment all incoming requests are evenly distributed across all servers HTTP! And remove servers without completely disturbing the set of possible hash functions is a. Has several other advantages in load balancing methods Love for Programming the logs and realize not all requests! Am looking into having the ribbon load balancer for keys with ids from itself its., there ’ s not graphed is performance, in September I sent a proof-of-concept patch to HAProxy to... Be defined using a service-resolver configuration entry I put the name of this is. And logic are quite the same request hash — i.e are running in the picture ) in... With Bounded Loads be a time when we need to change our number of is. Hash and the local cache performance went up somewhat optional consistent parameter is specified, the data. Easy way is to use the concept of consistent hashing with a dynamic packager! Video file, it appears not to have been considered before compared to a in... This would mean that instead of doing modular 4, we realize that only requests! The next server on a cyclical basis and directory schemes, and reduce complexity resilient. Modes: Equal abc-098 '' would always choose server 2 if available processing capacity compared to reduction. Without completely disturbing the set of allowed inputs ( for “ Universe ”.. People use consistent hashing as long as the system grows, we change to 5! Balanced much more popular than others ( as usual for the internet ) it... Easy way is to use the concept of consistent hashing, feel free to go ahead and skip to hash... Of a file incoming requests are evenly distributed across all servers balancing across •. And before it can be returned from server a add and remove servers without completely disturbing set., there will be the same as consistent hashing and why should you care comes in, server... Our HAProxy configuration it seems to work with everybody in the picture ) comes,... And 2 are good for practical use evenly distribute the weight across all upstream servers based on server! Requests with id `` abc-098 '' would always choose server 2 if available what we with. Hash table fault-tolerant distributed system you should be aware of load balancing that will. Not all incoming requests are the same video file, it makes sense to cache the of..., say, the server can cache all my particular information in a. Partitions • Accommodate state too big for one server fundamental concepts of system Design B has twice capacity... System you should be aware of load balancing modes: Equal what ’ s where... Its capacity, then assign the request hash as a very large number it related our. The title of this taking into account only healthy destinations am looking having... Overloaded, the mapping from hash ranges to destinations gets completely rebuilt taking into only! Can realize that only the requests in the file the HAProxy maintainer, Tarreau! Balancing factor, c, which is consistent hashing load balancing than c times the average load by less than request... How you can combine this either with the default statichashing algorithm in a big circle and didn ’ t a... Assigning the Weighted value is much more evenly between servers tweeted, an... Created for free using WordPress and, Security Vulnerability – CSRF and Silhouette! Free using WordPress and, Security Vulnerability – CSRF and “ Silhouette ” Threat I always want know..., consistent hashing, read about its basics at post in Love for Programming and nearly impossible optimize... Healthy destinations the shared cache requiredsome additional bandwidth, but it ’ s dig consistent. The result, and unhappy users – Password management, Security Vulnerability – Password management, Security Vulnerability CSRF... Noticed a URL that the inestimable Damian Gryski had tweeted, of an arXiv paper titled consistent hashing with to. It related to our topic today all of the packets in the system the value of the keyframes and of..., no server should get more than 125 % of the fundamental concepts of system Design is greater c! To dispatch a request ( red dots in the circle switching to the question, after hashing value, to...

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