google cloud HTTPS load balancer session affinity - networking

I have an HTTPS load balancer configured with one backend service and 2 instance groups:
The backend is configured for cookie session affinity.
My transaction is made out of a POST request and then 6 redirects which requires session affinity. In most case this works as expected but in about 10%-15% of the cases the affinity stops working during the redirection sequence which results in an application error on our side.
I'm printing the GCLB cookie value on our Apache reverse proxy and can see that it's not changing between requests but the request is still redirected to a different instance in the group or from a different group(note that the same behaviour is happening when there is only a single group with multiple instances in the backend.)
The health checks are all passing and there is no autoscaling happening during the run(1 instance per group).
What can cause the LB to change backend instances although the GCLB cookie is not different?
Thanks

The documentation says there are three causes for loss of session affinity:
The instance group runs out of capacity, and traffic has to be routed to a different zone. In this case, traffic from existing sessions may be sent to the new zone, breaking affinity. You can mitigate this by ensuring that your instance groups have enough capacity to handle all local users.
Autoscaling adds instances to, or removes instances from, the instance group. In either case, the backend service reallocates load, and the target may move. You can mitigate this by ensuring that the minimum number of instances provisioned by autoscaling is enough to handle expected load, then only using autoscaling for unexpected increases in load.
The target instance fails health checks. Affinity is lost as the session is moved to a healthy instance.
If the number of instances in the IG isn't changing, and all instances are remaining healthy the entire time, then that eliminates the second and third bullet points.
Are you using a regional managed instance group? If so, the first bullet point seems to be the cause.
It could be possible that you're tickling some sort of bug in the session cookie handling; to eliminate this possibility, have you tried other affinity settings to see if the problem goes away?

We also faced the same issue and came to this stack overflow question and answer. After days of playing with settings and configuration, again referred to google docs. Now, there can be 4 reasons why this can happen. Our issue got resolved by 4th cause. We changed from Utilization to RPS. Speciafically
When the UTILIZATION balancing mode is in effect for backend instance groups, session affinity breaks because of changes in backend utilization. You can mitigate this by using the RATE or CONNECTION balancing mode, whichever is supported by the load balancer's type.

Related

when will Cosmos DB Client's mapping cache be refreshed?

We are using Cosmos DB SDK whose version is 2.9.2. We perform Document CRUD operations. Usually, the end-to-end P95 latency is 20ms. But sometimes the latency is over 1000ms. The high latency period lasts for 10 hours to 1 day. The collection is not throttling.
We have get some background information from:
https://icm.ad.msft.net/imp/v3/incidents/details/171243015/home
https://icm.ad.msft.net/imp/v3/incidents/details/168242283/home
There are some diagnostics strings in the tickets.
We know that the client maintains a cache of the mapping of logical partition and physical replica address. This mapping may be outdated because of replicas movement or outage. So client tries to read from the second/third replica. However, this retry has significant impact on end to end latency. We also observe that the high latency/timeout can last for several hours, even days. I expect there’s some mechanism of refreshing mapping cache in the client. But it seems the client stops visiting more than one replica only after we redeploy our service.
Here are my questions:
How can the client tell whether it’s unable to connect to a certain replica? Will the client wait until timeout or server tells client that the replica is unavailable?
In which condition the mapping cache will be refreshed? We are using Session consistency and TCP mode.
Will restarting our service force the cache to be refreshed? Or refreshing only happens when the machine restarts?
When we find there’s replica outage, is there any way to quickly mitigate?
What operations are performed (Document CRUD or query)?
And what are the observed latencies & frequencies? Also please check if the collection is throttling (with custom throttling policy).
Client do manage the some metada and does handle its staleness efficiently with-in SLA bounds.
Can you please create a support ticket with account details and 'RequestDiagnostis' and we shall look into it.

App pool recycle

We are working on an application that serves request 24 * 7 and none of the request should be missed. This application is hosted on IIS in load balanced environment. Primary server group P1 and C1, while the back up servers to primary servers are P2 and C2. So, requests are sent in load balanced manner to P1 and C1. If both P1 and C1 go down, the P2 and C2 are up.
We are trying to work on a strategy so none of our requests are missed. Plan is to bring primary servers P1 and C1 down so requests are forwarded to back up. Then bring the primary servers up and work on back up servers.
My question around it is how to ensure that worker process serves the last request it receives before we bring the application down for primary servers. As mentioned earlier, the intention is to ensure none of the requests are missed
If you want to ensure that none of the requests are missed, you may be waiting a good long while--any requests in progress at the time the recycle occurs are serviced by the original AppPool. Depending on your site, some of those requests could be large files with very slow connections, which could take literally hours to finish. At some point you may just want to whack the connections and move on, knowing that the caller will refresh their page, reconnect, or whatever to get back to where they were.
In any case, you don't need multiple servers for this. IIS automatically (by default at least), drains requests from the old application instance while starting up the new one and sending new requests to that (during application updates). (Note however, that any requests to the new pool will likely stall for several seconds because the application is loading and initializing everything for the first time--this is normal and very difficult to avoid).
If you really do have multiple servers and want to switch request handling from one server to the other, you must have some kind of load balancing system in place, either a software load balancer such as Microsoft Network Load Balancing, or a hardware load balancer such as F5 Big-IP. In both of these situations, you have to somehow tell the load balancer to drain connections on the old application (or server) and route them to the new server. This may be done manually through their GUIs, or for an automated deployment system, will require integration with those systems.

How do I set up global load balancing using Digital Ocean DNS and Nginx?

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!

Load balancing long lived sessions that require server state

Suppose a user's session is load balanced to server #8 and some state is maintained at server #8. The next action from user needs to be routed to server #8 again because that is the only place with his server state. Is there a standard solution to maintain this mapping from user session to server number for long lived sessions? It seems like this problem of mapping user session to a specific server among many servers should be a common problem with a standard "textbook" solution thats cpu and memory efficient.
An easy solution is to configure your load balancer to use sticky sessions. the load balancer will associate a user session to Server #8, and then subsequent requests from the same session will automatically be forwarded to the same server (Server 8).
The best solution is not to rely on server affinity - it makes your system fragile. I wouldn't expect a textbook answer in the same way I would not expect a textbook answer on how to play with a toaster in the bath nor how to perform brain surgery with a screwdriver.
If you must have sticky routing then how you implement it depends a lot on how you propose to deal with a server not being available - do you failover the requests? Or just stop processing requests which would have been directed to that server?
I initially thought that this was a very dumb question - what's the relevance unless you're writing your own proxy/load-balancer (in which case you should already know he answers) but there are proxies available which allow you to implement your own director.
So ultimately it boils down to what characteristics of the session are visible in the HTTP request. Since an IP adderss can change mid stream, the only practical characteristic you can use is the session idenitifier - usually implemented as a cookie.

Impact when changing instance count for asp.net web role in Azure

I'm having no luck trying to find out how channging the instance count for an ASP.Net web role affects requests currently being processed.
Heres the scenario:
An ASP.Net site is deployed with 6 instances
Via the console I reduce the instancecount to 4
Is azure smart enough to not remove instances from the pool if it is currently progressing requests or does it just kill them mid request?
I've been through the azure doco, goolge and a number of emails to MS tech support none of which were able to answer this seemingly simple question. I know about the events that get triggered by a shutdown etc but that doesnt really help in web site scenario with a live person waiting for a request to their response.
You cannot choose which instances to kill off. Primarily this is due to Windows Azure's instance allocation scheme, where your instances are split into different fault domains (meaning different areas of the data center - different rack, etc.). If you were to choose the instances to kill, this could leave you in a state where your remaining instances are in the same fault domain, which would void the SLA.
Having said that: You get an event when your role instance is shutting down (the OnStop() event). If you capture this event, you can do instance cleanup in preparation for VM shutdown. I can't recall if you're taken out of the load balancer at this point, but you could always force yourself out with a simple PowerShell command (Set-RoleInstanceStatus -Busy). This way your asp.net instance stops taking requests, and you can more easily shut down in a graceful manner.
EDIT: Sorry - didn't quite address all of your question. Since you get to capture OnStop(), you might have to implement a mechanism to make sure nothing's being processed in that instance. Since you're out of the load balancer, and assuming your requests are processed fairly quickly (2-5 seconds), you shouldn't have to wait long to clear out remaining requests. There's probably a performance counter to check, to see how many active requests are being handled.
Just to add to David's answer: the OnStop event happens when you are off the load balancer. For web apps, it is usually sufficient time to bleed out all requests after you are disconnected from the LB until the instance is shutdown. However, for long running or stateful connections (perhaps to a worker role), there would be an abrupt disconnect in some cases. While the OnStop method removes you from the LB, it does not terminate open connections. It simply prevents you from getting new connections. For web apps, this is usually enough time to complete the request (and you can delay the shutdown if necessary in the OnStop as well if you really want to).

Resources