UPDATE: See the answer I've provided below for the solution I eventually got set up on AWS.
I'm currently experimenting with methods to implement a global load-balancing layer for my app servers on Digital Ocean and there's a few pieces I've yet to put together.
The Goal
Offer highly-available service to my users by routing all connections to the closest 'cluster' of servers in SFO, NYC, LON, and eventually Singapore.
Additionally, I would eventually like to automate the maintenance of this by writing a daemon that can monitor, scale, and heal any of the servers on the system. Or I'll combine various services to achieve the same automation goals. First I need to figure out how to do it manually.
The Stack
Ubuntu 14.04
Nginx 1.4.6
node.js
MongoDB from Compose.io (formerly MongoHQ)
Global Domain Breakdown
Once I rig everything up, my domain would look something like this:
**GLOBAL**
global-balancing-1.myapp.com
global-balancing-2.myapp.com
global-balancing-3.myapp.com
**NYC**
nyc-load-balancing-1.myapp.com
nyc-load-balancing-2.myapp.com
nyc-load-balancing-3.myapp.com
nyc-app-1.myapp.com
nyc-app-2.myapp.com
nyc-app-3.myapp.com
nyc-api-1.myapp.com
nyc-api-2.myapp.com
nyc-api-3.myapp.com
**SFO**
sfo-load-balancing-1.myapp.com
sfo-load-balancing-2.myapp.com
sfo-load-balancing-3.myapp.com
sfo-app-1.myapp.com
sfo-app-2.myapp.com
sfo-app-3.myapp.com
sfo-api-1.myapp.com
sfo-api-2.myapp.com
sfo-api-3.myapp.com
**LON**
lon-load-balancing-1.myapp.com
lon-load-balancing-2.myapp.com
lon-load-balancing-3.myapp.com
lon-app-1.myapp.com
lon-app-2.myapp.com
lon-app-3.myapp.com
lon-api-1.myapp.com
lon-api-2.myapp.com
lon-api-3.myapp.com
And then if there's any strain on any given layer, in any given region, I can just spin up a new droplet to help out: nyc-app-4.myapp.com, lon-load-balancing-5.myapp.com, etc…
Current Working Methodology
A (minimum) trio of global-balancing servers receive all traffic.
These servers are "DNS Round-Robin" balanced as illustrated in this
(frankly confusing) article: How To Configure DNS Round-Robin Load
Balancing.
Using the Nginx GeoIP
Module and
MaxMind GeoIP Data
the origin of any given request is determined down to the
$geoip_city_continent_code.
The global-balancing layer then routes the request to the least
connected server on the load-balancing layer of the appropriate
cluster: nyc-load-balancing-1, sfo-load-balancing-3,
lon-load-balancing-2, etc.. This layer is also a (minimum) trio of
droplets.
The regional load-balancing layer then routes the request to the
least connected server in the app or api layer: nyc-app-2,
sfo-api-1, lon-api-3, etc…
The details of the Nginx kung fu can be found in this tutorial:
Villiage Idiot: Setting up Nginx with GSLB/Reverse Proxy on
AWS. More general info about Nginx load-balancing is available
here
and
here.
Questions
Where do I put the global-balancing servers?
It strikes me as odd that I would put them either all in one place, or spread that layer out around the globe either. Say, for instance, I put them all in NYC. Then someone from France hits my domain. The request would go from France, to NYC, and then be routed back to LON. Or if I put one of each in SFO, NYC, and LON then isn't it still possible that a user from Toronto (Parkdale, represent) could send a request that ends up going to LON only to be routed back to NYC?
Do subsequent requests get routed to the same IP?
As in, if a user from Toronto sends a request that the global-balancing layer determines should be going to NYC, does the next request from that origin go directly to NYC, or is it still luck of the draw that it will hit the nearest global-balancing server (NYC in this case).
What about sessions?
I've configured Nginx to use the ip_hash; directive so it will direct the user to the same app or api endpoint (a node process, in my case) but how will global balancing affect this, if at all?
Any DNS Examples?
I'm not exactly a DNS expert (I'm currently trying to figure out why my CNAME records aren't resolving) but I'm a quick study when provided with a solid example. Has anyone gone through this process before and can provide a sample of what the DNS records look like for a successful setup?
What about SSL/TLS?
Would I need a certificate for every server, or just for the three global-balancing servers since that's the only public-facing gateway?
If you read this whole thing then reward yourself with a cupcake. Thanks in advance for any help.
The Goal: Offer highly-available service to my users by routing all connections to the closest 'cluster' of servers in SFO, NYC, LON, and eventually Singapore.
The global-balancing layer then routes the request to theleast
connected server...
If I'm reading your configuration correctly, you're actually proxying from your global balancers to the balancers at each region. This does not meet your goal of routing users to the nearest region.
There are three ways that I know of to get what you're looking for:
30x Redirect Your global balancers receive the HTTP request and then redirect it to a server group in or near the region it thinks the request is coming from, based on IP address. This sounds like what you were trying to set up. This method has side effects for some applications, and also increases the time it takes for a user to get data since you're adding a ton of overhead. This only makes sense if the resources you're redirecting to are very large, and the local regional cluster will be able to serve much more efficiently.
Anycast (taking advantage of BGP routing) This is what the big players like Akamai use for their CDN. Basically, there are multiple servers out on the internet with the exact same routable IP address. Suppose I have servers in several regions, and they have the IP address of 192.0.2.1. If I'm in the US and try to connect to 192.0.2.1, and someone is in Europe that tries to connect to 192.0.2.1, it's likely that we'll be routed to the nearest server. This uses the internet's own routing to find the best path (based on network conditions) for the traffic. Unfortunately, you can't just use this method. You need your own AS number, and physical hardware. If you find a VPS provider that lets you have a chunk of their Anycast block, let me know!
Geo-DNS There are some DNS providers that provide a service often marketed as "Geo-DNS". They have a bunch of DNS servers hosted on anycast addresses which can route traffic to your nearest servers. If a client queries a European DNS server, it should return the address for your European region servers, vs. some in other regions. There are many variations on the Geo DNS services. Others simply maintain a geo-IP database and return the server for the region they think is closer, just like the redirect method but for DNS before the HTTP request is ever made. This is usually the good option, for price and ease of use.
Do subsequent requests get routed to the same IP?
Many load balancers have a "stickiness" option that says requests from the same network address should be routed to the same end server (provided that end server is still up and running).
What about sessions?
This is exactly why you would want that stickiness. When it comes to session data, you are going to have to find a way to keep all your servers up-to-date. Realistically, this isn't always guaranteed. How you handle it depends on your application. Can you keep a Redis instance or whatever out there for all your servers to reliably hit from around the world? Do you really need that session data in every region? Or can you have your main application servers dealing with session data in one location?
Any DNS Examples?
Post separate questions for these. Everyone's "successful setup" looks differently.
What about SSL/TLS?
If you're proxying data, only your global balancers need to handle HTTPS. If you're redirecting, then all the servers need to handle it.
A Working Solution
I've had a wild ride over the past few months figuring out the whole Global-HA setup. Tonnes of fun and I've finally settled with a rig that works very well, and is nothing like the one outlined in the above question.
I still plan on writing this up in tutorial form, but time is scarce as I head into the final sprint to get my app launched early next year, so here's a quick outline of the working rig I ended up with.
Overview
I ended up moving my entire deployment to AWS. I love Digital Ocean, but the frank reality is that AWS is light years ahead of them (and everyone, really) when it comes to the services offered under one roof. My monthly expenses went up slightly, but once I was done tweaking and streamlining I ended up with a solution that costs about $75/month per region for the most basic deployment (2 instances behind an ELB). And a new region can be spun up and deployed within about 30 minutes.
Global Balancing
I quickly found out (thanks to #Brad's answer above) that trying to spin up my own global balancing DNS layer is insane. It was a hell of a lot of fun figuring out how a layer like this works, but short of getting on a plane and scraping my knuckles installing millions of dollars worth of equipment around the world, it was not going to be possible to roll my own.
When I finally figured out what I was looking for, I found my new best friend: AWS Route 53. It offers a robust DNS network with about 50-odd nodes globally and the ability to do some really cool routing tricks like location-based routing, latency-based routing (which is kinda awesome), and AWS Alias records that 'automagically' route traffic to other AWS Services you'll be using (Like ELB for load balancing).
I ended up using latency-based routing that directs the global traffic to the closest regional Elastic Load Balancer, which has an Auto-Scaling Group attached to it in any given region.
I'll leave it up to you to do your homework on the other providers: www.f5.com, www.dyn.com, www.akamai.com, www.dnsmadeeasy.com. Depending on your needs, there may be a better solution for you, but this works very well for me.
Content Delivery Network
Route 53 integrates with AWS Cloudfront very nicely. I setup an S3 bucket that I'm using to store all the static media files that my users will upload, and I've configured a Cloudfront distribution to source from my media.myapp.com S3 bucket. There are other CDN providers, so do your shopping. But Cloudfront gets pretty good reviews and it's a snap to setup.
Load Balancing & SSL Termination
I'm currently using AWS Elastic Load Balancer to balance the load across my application instances, which live in an Auto-Scaling Group. The request is first received by ELB, at which point SSL is terminated and the request is passed through to an instance in the Auto-Scaling Group.
NOTE: One giant caveat for ELB is that, somewhat ironically, it doesn't handle massive spikes very well. It can take up to 15 minutes for an ELB to trigger a scale-up event for itself, creating 500/timeouts in the meantime. A steady, constant increase in traffic is supposedly handled quite well, but if you get hit with a spike it can fail you. If you know you're going to get hit, you can 'call ahead' and AWS will warm up your ELB for you, which is pretty ridiculous and anti-pattern to the essence of AWS, but I imaging they're either working on it, or ignoring it because it's not really that big of a problem. You can always spin up your own HAProxy or Nginx load-balancing layer if ELB doesn't work for you.
Auto-Scaling Group
Each region has an ASG which is programmed to scale when the load passes a certain metric:
IF CPU > 90% FOR 5 MINUTES: SCALEUP
IF CPU < 70% FOR 5 MINUTES: SCALEDN
I haven't yet put the ELB/ASG combo through its paces. That's a little way down my To-Do list, but I do know that there are many others using this setup and it doesn't seem to have any major performance issues.
The config for an Auto-Scaling Group is a little convoluted in my opinion. It's actually a three-step process:
Create an AMI configured to your liking.
Create a Launch Configuration that uses the AMI you've created.
Create an Auto-Scaling Group that uses the Launch Configuration you've created to determine what AMI and instance type to launch for any given SCALEUP event.
To handle config and app deployment when any instance launches, you use the "User Data" field to input a script that will run once any given instance launches. This is possibly the worst nomenclature in the history of time. How "User Data" describes a startup script only the author knows. Anyhow, that's where you stick the script that handles all your apt-gets, mkdirs, git clones, etc.
Instances & Internal Balancing
I've also added an additional 'internal balancing layer' using Nginx that allows me to 'flat-pack' all my Node.js apps (app.myapp.com, api.myapp.com, mobile.myapp.com, www.myapp.com, etc.myapp.com) on every instance. When an instance receives a request passed to it from ELB, Nginx handles routing the request to the correct Node.js port for any given application. Sort of like a poor-mans containerization. This has the added benefit that any time one of my apps needs to talk to the other (like when app. needs to send a request to api.) it's done via localhost:XXXX rather than having to go out across the AWS network, or the internet itself.
This setup also maximizes usage of my resources by eliminating any idle infrastructure if the app layer it hosts happens to be receiving light traffic. It also obviates the need to have and ELB/ASG combo for every app, saving more cash.
There's no gotchas or caveats that I've run into using this sort of setup, but there is one work-around that needs to be in place with regard to health-checking (see below).
There's also a nice benefit in that all instances have an IAM role which means that your AWS creds are 'baked in' to each instance upon birth and accessible via your ENV vars. And AWS 'automagically' rotates your creds for you. Very secure, very cool.
Health Checks
If you go the route of the above setup, flat-packing all your apps on one box and running an internal load-balancer, then you need to create a little utility to handle the ELB Health Checks. What I did was create an additional app called ping.myapp.com. And then I configured my ELB Health Checks to send any health checks to the port that my ping app is running on, like so:
Ping Protocol: HTTP
Ping Port: XXXX
Ping Path: /ping
This sends all health checks to my little ping helper, which in turn hits localhost:XXXX/ping on all the apps residing on the instance. If they all return a 200 response, my ping app then returns a 200 response to the ELB health check and the instances gets to live for another 30 seconds.
NOTE: Do not use Auto-Scaling Health Checks if you're using an ELB. Use the ELB health checks. It's kinda confusing, I thought they were the same thing, they're not. You have the option to enable one or the other. Go with ELB.
The Data Layer
One thing that is glaringly absent from my setup is the data layer. I use Compose.io as my managed data-layer provider and I deploy on AWS so I get very low latency between my app layers and my data layer. I've done some prelim investigation on how I would roll my data layer out globally and found that it's very complex — and very expensive — so I've kicked it down my list as a problem that doesn't yet need to be solved. Worst case is that I'll be running my data layer in US-East only and beefing up the hardware. This isn't the worst thing in the world since my API is strictly JSON data on the wire so the average response is relatively tiny. But I can see this becoming a bottleneck at very large, global scale — if I ever get there. If anyone has any input on this layer I'd love to hear what you have to say.
Ta-Da!
Global High Availability On A Beer Budget. Only took me 6 months to figure it out.
Love to hear any input or ideas from anyone that happens to read this.
You can use Anycast for your webservice for free if using Cloudflare free plan.
Digital Ocean now supports Load Balancing of servers itself. It is extremely easy to set up and works great! Saves you having to add in unnecessary components such as nginx (if you only want to use for load balancing).
We were having issues using SSL file uploads with nginx on a digital ocean server, however since the Digital Ocean update, we have removed nginx and now use Digital Ocean's load balancing feature and it works just as we need it to!
Related
I've been using web scraping services for a bit but I need such a high volume that I can't pay for those services anymore.
I was thinking to build my own proxy pool to mimic these services for myself but didn't know how to do it.
My solutions:
My first thought was to use kali linux's proxychain to get the same result but I don't know if that would work since I can't find the list or proxies in the code.
I also thought that I could create a server config with Ansible, and use Terraform to spin cloud servers either on demand or until blacklisted but I'm not sure it'll be fast and reliable or if cloud providers could block me.
Lastly, I thought about using VMs or Containers since you can attribute them random IPs and bridge networked VMs have random IPs so if it gets banned just delete it and spin up a new one.
Does someone know which way between the three makes the most sense to achieve what I'm looking for ?
I don't know what is required to get a pool so reliable that some companies have created business of offering them for webscraping such as ScrapingBee but just on the reliable proxy pool side, because all the free proxy pools online are not really good.
I imagine that if it was public knowledge, those companies wouldn't exist, but I'm sure I'm missing something there.
Thank you.
I was recently reading this article from the Figma engineering blog: https://www.figma.com/blog/rust-in-production-at-figma/ and was curious about their NGINX setup for multiplayer routing. This is how it looks:
Where they have M number of servers, and where each server has W number of workers. Figma lets users collaborate on design documents in real-time, and each document (i.e. the logic that takes care of the real-time multiplayer processing for each doc) always lives in one specific worker.
I’m wondering how they manage to always route users to the machine that has the worker for the document being worked on, and then to the specific process that actually has the doc.
They do this with NGINX, but my question is how?
I know that NGINX has round-robin and ip_hash methods to load balance, but that’s not granular enough to achieve what they do.
Related question:
Route traffic to multiple node servers based on a condition
You should be able to use a cookie to associate a user with the downstream node: https://docs.nginx.com/nginx/admin-guide/load-balancer/http-load-balancer/#enabling-session-persistence
I have built a distributed HTTP scraper solution that uses different "exit addresses" addresses by design in order to balance the network load.
The solution supports IPv4, IPv6 and HTTP proxy to route the traffic.
Each processor was responsible to define the most efficient route to balance the traffic and it was temporarily implemented manually for prototyping. Currently, the solution grows and with the number of processors as the complexity of the load balancing task get higher, that's why I need a way to create a component dedicated to it.
I did some rather extensive research, but seem to have failed in finding a solution for load balancing traffic between IPv6, IPv4 (thousands of local addresses) and public HTTP proxies. The solution needs to support weights, app-level response checks and cool-down periods.
Does anyone know a solution that already solves this problem? Before I start developing a custom one.
Thanks for your help!
If you search for load balancing proxy you'll discover the Cache Array Routing Protocol (CARP). This CARP might not be what you're searching for and there exists servers only for the proxy-cache what I never knew till now.
Nevertheless those servers have own load balancers too, and perhaps that's a detail where it's worth it to search more.
I found a presentation mentioning CARP as outstanding solution too: https://cs.nyu.edu/artg/internet/Spring2004/lectures/lec_8b.pdf
Example: for proxy-arrays in Netra Proxy Cache Server: https://docs.oracle.com/cd/E19957-01/805-3512-10/6j3bg665f/index.html
Also there exist several concepts for load-balancing (https://link.springer.com/article/10.1023/A:1020943021842):
The three proposed methods can broadly be divided into centralized and decentralized
approaches. The centralized history (CH) method makes use of the transfer rate of each
request to decide which proxy can provide the fastest turnaround time for the next job.
The route transfer pattern (RTP) method learns from the past history to build a virtual
map of traffic flow conditions of the major routes on the Internet at different times of the
day. The map information is then used to predict the best path for a request at a particular time of the day. The two methods require a central executive to collate information
and route requests to proxies. Experimental results show that self-organization can be
achieved (Tsui et al., 2001). The drawback of the centralized approach is that a bottleneck and a single point of failure is created by the central executive. The decentralized
approach—the decentralized history (DH) method—attempts to overcome this problem
by removing the central executive and put a decision maker in every proxy (Kaiser et al.,
2000b) regarding whether it should fetch a requested object or forward the request to another
proxy.
As you use public proxy-servers probably you won't use decentralized history (DH) but centralized history (CH) OR the route transfer pattern (RTP).
Perhaps it would be even useful to replace your own solution completely, i.e. by this: https://github.blog/2018-08-08-glb-director-open-source-load-balancer/. I've no reason for this special example, it's just random by search results I found.
As I'm not working with proxy-servers this post is just a collection of findings, but perhaps there is a usable detail for you. If not, don't mind - probably you know most or all already and it's never adding anything new for you. Also I never mention any concrete solution.
Have you checked this project? https://Traefik.io which supports http/2 and tcp load balancing. The project is open source and available on github. It is build using Go. I'm using it now as my reverse proxy with load balancing for almost everything.
I also wrote a small blog post on docker and Go where I showcase the usage of Traefik. That also might help you in your search. https://marcofranssen.nl/docker-tips-and-tricks-for-your-go-projects/
In the traefik code base you might find your answer, or you might decide to utilize traefik to achieve your goal instead of home grown solution.
See here for a nice explanation on the soon to be arriving Traefik 2.0 with TCP support.
https://blog.containo.us/back-to-traefik-2-0-2f9aa17be305
Twilio and other HTTP-driven web services have the concept of a fallback URL, where the web services sends a GET or POST to a URL of your choice if the main URL times out or otherwise fails. In the case of Twilio, they will not retry the request if the fallback URL also fails. I'd like the fallback URL to be hosted on a separate machine so that the error doesn't get lost in the ether if the primary server is down or unreachable.
I'd like some way for the secondary to:
Store requests to the fallback URL
Replay the requests to a slightly different URL on the primary server
Retry #2 until success, then delete the request from the queue/database
Is there some existing piece of software that can do this? I can build something myself if need be, I just figured this would be something someone would have already done. I'm not familiar enough with HTTP and the surrounding tools (proxies, reverse proxies, etc.) to know the right buzzword to search for.
There are couple of possibilities.
One option is to use Common Address Redundancy Protocol or carp. Brief description from the man page follows.
"carp allows multiple hosts on the same local network to share a set of IP addresses. Its primary purpose is to ensure that these addresses are always available, but in some configurations carp can also provide load balancing functionality."
It should be possible be configure IP balancing such that when a primary or master http service fails, the secondary or backup http service becomes the master. carp is host oriented as opposed to application service. So when the http service goes down, it should also take down the network interface for carp to do its thing. This means you would need more than one IP address in order to log into the machine and do maintenance. You would need a script to do the follow-up actions once the original service comes back online.
The second option is to use nginx. This is probably better suited to what you are trying to do.
Many years ago I needed something similar to what are trying to do and I ended up hacking together something that did it. Essentially it was a switch. When 'A' fails, switch over to 'B'. Re-sync process was to take time stamped logs from 'B' and play them back to 'A', once 'A' was back online.
I am building a service which requires me to dynamically launch and close servers at many locations around the world, (for example using AWS). When a user visits my domain they need to be assigned to a local server with the lowest latency.
By assignment, I mean that for example the client makes an ajax call to example.com/getData, it should go directly to one particular server that is has been assigned to. Different servers will be doing different computation, so it is not sufficient to have some kind of general load balancing.
What general mechanisms/technology would allow me to 1) Assess the latency between a particular client and any server under my control? 2) Assign a particular client to a particular server? I cannot use just the IP addresses for example, since javascript has domain name based restrictions.
Thanks
Note: I do not have enough reputation to link all the technologies in the response, therefore sometimes you will see the links copied in plain text.
1) Assign users to a local server with the lowest latency is not always possible.
Sometimes the geographically closest server to a user is unexpectedly the one with the highest latency.
To find the lowest latency between your (running) servers and the users is not an easy task.
There might be many different hops (routers) between the client and the server, and any of them at any time can have problems, routes update, packet congestions and so on.
The quickest way to assess the latency is a ping, but it can be that the firewalls block this.
So the best way to achieve this is to use the anycast
All the major CDN providers implement this method. Some use the TCP anycast, which seems to be not recommended, and others UDP anycast. It is an open debate.
Anyway in order to implement anycast you need to be able to peer with the ISP routers, and normally this is not possible. Additionally there are good peers and bad peers.
Finally All this requires a deep knowledge of the routing protocols and the TCP/IP stack.
A quick and dirty solution could be to use BIND with the GEO-IP patch.
So you can define specific dns query responses per country.
What I mean is that, for instance, if you have a server in UK and one in US you can configure BIND to respond to users coming from europe to hit the UK server and users coming from US to hit the US server.
2) To assign a particular client to a particular server you can use the technique I described on the point 1 or you can use a proxy and sticky sessions.
HA-Proxy is a good product to achieve this. (the URL: xy.1wt.eu )
3) if you use the point 1, you will not have problems with cross domain ajax calls. In fact it is completely transparant for the client. For instance for the same domain example.com a user coming from US will resolve it to 1.1.1.1 whereas a user coming from Germany will resolve example.com to 2.2.2.2 (ip addresses are fake and used just as an example).
On a side note, a solution to do cross domain ajax call is JSON-P which has though some drawbacks, like the lack of support for POST.
If I were you I would go with the BIND and GEO-IP, because it would solve all three problems in once. (a part for the latency because is not always true that the geographically closest server is the one with the lowest latency.)