I started a project and I started to have a lot of web traffic, and at some point I felt insecure of how to scale the project to production in two issues:
How to perform updates without leaving my users without service?
How to correctly configure Node.js so that it consumes less memory?
I have microservices working with Hydra-express, and I have not been able to implement Hydra-router and I do it with Express.js; I also have NGINX as a proxy gateway.
I am programming in ES6, transpiling with BABEL and maintaining active microservices with PM2, some with fork and the most important in cluster mode.
I was thinking about using docker, but I have not found any tutorial on how to use it with CDN, upload files and serve them to the user.
It's impossible to give a definite answer to 2 since that is completely up to what the application does, there's no silver bullet configuration that you can apply.
This leaves the first point, which is around something called zero downtime.
So, in the context of having multiple servers returning content to users, e.g. http servers I guess it's fair to say that most production environments have something at the front that's not related to the business logic. This could be a load balancer (comes in many shapes and forms) or a reverse proxy. This is usually the spot where you point your DNS A record. This server should basically never be down.
Now, lets assume you have changed some business logic and want to deploy a new backend. What you normally do is to swap out the already running processes behind the load balancer (or reverse proxy), one by one. So if you have five node processes, you stop one, start up a new with the updated code, and repeat until all running have been swapped out.
You can also utilize this to swap out just one, run tests on that one, then proceed to swap out the rest.
To really make sure you don't disrupt any users, you should stop accepting new http requests on the old processes, so new http requests are routed to the updated processes. This will allow for http requests that are taking place to finish up. Then you stop the old processes.
Hopes this helps.
Adding to #ralphtheninja answer, I suggest you reading more about blue green deployments, as proposed by Martin Fowler; https://martinfowler.com/bliki/BlueGreenDeployment.html
One of the challenges with automating deployment is the cut-over itself, taking software from the final stage of testing to live production. You usually need to do this quickly in order to minimize downtime. The blue-green deployment approach does this by ensuring you have two production environments, as identical as possible. At any time one of them, let's say blue for the example, is live. As you prepare a new release of your software you do your final stage of testing in the green environment. Once the software is working in the green environment, you switch the router so that all incoming requests go to the green environment - the blue one is now idle.
Blue-green deployment also gives you a rapid way to rollback - if anything goes wrong you switch the router back to your blue environment.
I have no idea where your backend is running but there are some services that will do it for you, AWS ElasticBeanstalk for example will put your instances behind a load balancer and will manage deployment according to a policy. have a look; https://docs.aws.amazon.com/elasticbeanstalk/latest/dg/using-features.rolling-version-deploy.html.
Related
I'm developing an app and I want to be able to quickly iterate on versions (fixing bugs and adding features, etc) so the obvious route to do this was to develop a CI/CD workflow. The frontend is simple enough, just swap out the assets my server serves with new builds, and as people access the site these assets will be served. However, I'm not so sure on how to go about updating my production backend servers, which are powered by express and node. In development, I can easily restart the server to reflect new changes, however doing this while in a production environment can have detrimental consequences for those who are using my service at the time of the update.
Overall, my question is what is the best way to push new backend server updates to my production environment without downtime/interrupting usage?
Ideally, you'll want to run some sort of cluster of processes.
The first step behind this is ensuring your application is completely stateless and that you can have simultaneous copies of the express server running at the same time for load balancing.
If you do need to maintain some form of state, you can use an memory-based store such as Redis to share state amongst server instances.
Once you have such an architecture, you can direct and throttle traffic in a way that each server instance in the cluster gets a chance to restart with no traffic being directed towards it.
Say you have 4 instances running your server. You will turn instance 1 off, and your load balancing would send your traffic to 2, 3 and 4.
During this time, you can either hot reload or fully reload instance 1. You then turn instance 1 back on and repeat the process with 2, 3 and 4.
Such a process is called a "rolling update"
Creating a node.js application is simple enough.
var app = require('express')();
app.get('/',function(req,res){
res.send("Hello world!");
});
But suppose people became obsessed with your Hello World! application and exhausted your resources. How could this example be scaled up on practice? I don't understand it, because yes, you could open several node.js instance in different computers - but when someone access http://your_site.com/ it aims directly that specific machine, that specific port, that specific node process. So how?
There are many many ways to deal with this, but it boils down to 2 things:
being able to use more cores per server
being able to scale beyond more than one server.
node-cluster
For the first option, you can user node-cluster or the same solution as for the seconde option. node-cluster (http://nodejs.org/api/cluster.html) essentially is a built in way to fork the node process into one master and multiple workers. Typically, you'd want 1 master and n-1 to n workers (n being your number of available cores).
load balancers
The second option is to use a load balancer that distributes the requests amongst multiple workers (on the same server, or across servers).
Here you have multiple options as well. Here are a few:
a node based option: Load balancing with node.js using http-proxy
nginx: Node.js + Nginx - What now? (using more than one upstream server)
apache: (no clearly helpful link I could use, but a valid option)
One more thing, once you start having multiple processes serving requests, you can no longer use memory to store state, you need an additional service to store shared states, Redis (http://redis.io) is a popular choice, but by no means the only one.
If you use services such as cloudfoundry, heroku, and others, they set it up for you so you only have to worry about your app's logic (and using a service to deal with shared state)
I've been working with node for quite some time but recently got the opportunity to try scaling my node apps and have been researching on the same topic for some time now and have come across following pre-requisites for scaling:
My app needs to be available on a distributed system each running multiple instances of node
Each system should have a load balancer that helps distribute traffic across the node instances.
There should be a master load balancer that should distribute traffic across the node instances on distributed systems.
The master balancer should always be running OR should have a dependable restart mechanism to keep the app stable.
For the above requisites I've come across the following:
Use modules like cluster to start multiple instances of node in a system.
Use nginx always. It's one of the most simplest mechanism for creating a load balancer i've came across so far
Use HAProxy to act as a master load balancer. A few pointers on how to use it and keep it forever running.
Useful resources:
Horizontal scaling node.js and websockets.
Using cluster to take advantages of multiple cores.
I'll keep updating this answer as I progress.
The basic way to use multiple machines is to put them behind a load balancer, and point all your traffic to the load balancer. That way, someone going to http://my_domain.com, and it will point at the load balancer machine. The sole purpose (for this example anyways; in theory more could be done) of the load balancer is to delegate the traffic to a given machine running your application. This means that you can have x number of machines running your application, however an external machine (in this case a browser) can go to the load balancer address and get to one of them. The client doesn't (and doesn't have to) know what machine is actually handling its request. If you are using AWS, it's pretty easy to set up and manage this. Note that Pascal's answer has more detail about your options here.
With Node specifically, you may want to look at the Node Cluster module. I don't really have alot of experience with this module, however it should allow you to spawn multiple process of your application on one machine all sharing the same port. Also node that it's still experimental and I'm not sure how reliably it will be.
I'd recommend to take a look to http://senecajs.org, a microservices toolkit for Node.js. That is a good start point for beginners and to start thinking in "services" instead of monolitic applications.
Having said that, building distributed applcations is hard, take time to learn, take LOT of time to master it, and usually you will face a lot trade-off between performance, reliability, manteinance, etc.
Is it possible to create one or several azure VMs on my local machine? I want to create a web app and load test it locally, without the need of putting it in the cloud. I'm thinking at the following scenario: I have a local VM running a IIS server with my web app; I use a tool to generate a lot of load; I need to deploy the second VM containing the same things as the first VM. The downtime of the web app should be equal to 0(hopefully).
Clarification(update):
I want to achieve the following: create a web app and a monitoring app(CPU,Memory) and deploy them on one VM. On a load test, if the VM cannot handle it(e.g. CPU goes above 80%), I want to programmatically deploy a new VM(with the same configuration, having both the web app and the monitoring app), such that no downtime occurs.
Azure has several ways for you to host sites.
Virtual Machines is just that, normal VMs. You can create them locally and upload them, but everything is up to you, including how to handle upgrades. If that is what you need to do then I don't know how you would handle upgrades with no down time; though, you can add multiple VMs to a load balancer and then upgrade them one at a time.
It sounds like what you really want to explore is Cloud Services. You can run one or more VMs locally in the emulator, upgrade with no down time once in the cloud, implement auto scaling (you will have to use a tool or write some code).
Alternatively you may want to look at Azure Web sites, but that is a completely different concept and you can't really test load and load balancing locally the same way.
Based on your statement that you essentially want to auto-scale your application you want to look at Cloud Services with Auto Scaling. However, you can't fully test this in the cloud emulator - but you can test your logic.
Background
Azure Cloud Services is designed for this kind of thing; You don't really work with VMs in the way you may be used to, instead you create a package that Azure then deploys to as many servers as you like. Once up and running, you can manually go into the management console and increase or decrease the number of active servers simply by moving a slider. Of course, you want to do this automatically, so you have a few options.
There is a management API you can use to change the number of servers. So, it would be quite simple to write a bit of code that you spin up in another thread from WebRole.Start and that simply sits and monitors the CPU on the machine and then calls the management API to spin up a new server instance if your CPU goes over a certain treshold. Okay, locally you can only test that the call to the management API is made, you won't actually see the new server coming up. But, if you grab your free trial of Azure and just try it you will see that you really don't need to test that part - it just works.
However, in practice there is an awful lot more to auto scaling. Here are some of the things you need to consider;
Even relatively idle web servers will often spike briefly to 100% so just having a simple treshold is unlikely to be good enough; You need to decide on how long the server needs to be over a certain treshold before you spin up another server instance.
What happens when you have more than one server? And, on Azure, you should always have at least two servers to ensure you have resilience. Note that the idea with Cloud Services really is to have many small servers rather than a few big servers. You pay per core, not per number of servers.
Imagine you currently have three servers and one is really busy for some reason and the other two are idle. Do you want to spin up a fourth server?
Imagine you currently have two servers and they are both quite busy. Do you really want them both to start a new server so you end up with four servers running?
There are several ways to handle these challenges. For starters, rather than having monitor programs running locally on each server, you are better of moving that monitoring outside; Azure comes with the ability to dump performance metrics to table storage at whatever interval you choose. You can then run an external program that retrieves the performance data over time from all your current servers and then reason about the overall workload before deciding to spin up or shut down additional servers. Now, you can of course host that external monitor program in a separate thread on each of your webroles to give your monitoring resilience - but the key point is that the monitoring program doesn't monitor the server it runs on, it monitors all the servers. You will, of course, still have to deal with stopping multiple monitoring program instances from all starting and stopping servers. One way to do is to place stop/start commands onto an Azure "message queue" (there are a few different types) and use the built-in "de-duper" which will automatically delete identical commands that are put on the queue within a certain time window (I am over simplyfing but you get the idea).
The actual answer
Really, though, you want to look at the Auto Scaling Application Block which will do most of this for you. I guess that is the real answer to your question, but I wanted to provide a bit of context first.
Again, I recognise you asked for how to test this locally - but I believe that that question doesn't really make sense in the context of Azure and I hope the above information helps.
I'm pretty sure you can't do that and it wouldn't make sense anyway. If you want load testing, you need to run that in an environment as similar to production as possible and that means you have to run your application is Azure cloud. How else do you know that the load will actually be processed fine on real cloud?
I want to try out heroku, but am not quite sure if I understand all terms correctly.
I have an app with node.js and redis & my main focus is scaling and speed.
In a traditional environment I would have two servers in front of a load balancer; both servers are totally independent, share the same code and have an own redis instance. Both servers don't know of each other (the data is synched by a third party server, but that is not of interest for that case).
I would then push a load balancer in front of them. Know I could easily scale, as both instances are not aware of each other and I could just add more instances if I wish.
Can I mirror that environment in a dyno or can't I attach a redis instance to a dyno?
If something is unclear, please ask, as I'm new to paas!
As I understand it: I would have a dyno for my node-app and would just add another instance of it. That's cool, but would they share the same redis or can I make them independent?
You better forget traditional architectures and try to think it this way:
A dyno is a process processing HTTP requests, the absolute minimum of an app instance on heroku.
For one application instance you can have as many dynos you want and
it is totally transparent . No need to think about servers, load
balancing, etc... everything is taken care.
A redis instance is a basically a service used by the application
instance and therefore by one or more dynos. Again, servers, load
balancing, etc all is taken care.
Maybe you want to review the How it works on heroku.com now again.
You can have as many dynos for one URL as you want - you just change the value in the controller. This is actually one of the best features of Heroku - you don't care about servers, you increase the number of dynos and by this increase the number of requests which can be processed simultaneously.
Same thing with redis - it basically doesn't work that you add instances, you just switch to a more performant plan, see https://addons.heroku.com/redistogo. Again, forget about servers.
UPDATE 2009-05-21
I've been testing the #2 method of using a single network share. It is resulting in some issues with Windows Server 2003 under load:
http://support.microsoft.com/kb/810886
end update
I've received a proposal for an ASP.NET website that works as follows:
Hardware load-balancer -> 4 IIS6 web servers -> SQL Server DB with failover cluster
Here's the problem...
We are choosing where to store the web files (aspx, html, css, images). Two options have been proposed:
1) Create identical copies of the web files on each of the 4 IIS servers.
2) Put a single copy of the web files on a network share accessible by the 4 web servers. The webroots on the 4 IIS servers will be mapped to the single network share.
Which is the better solution?
Option 2 obviously is simpler for deployments since it requires copying files to only a single location. However, I wonder if there will be scalability issues since four web servers are all accessing a single set of files. Will IIS cache these files locally? Would it hit the network share on every client request?
Also, will access to a network share always be slower than getting a file on a local hard drive?
Does the load on the network share become substantially worse if more IIS servers are added?
To give perspective, this is for a web site that currently receives ~20 million hits per month. At recent peak, it was receiving about 200 hits per second.
Please let me know if you have particular experience with such a setup. Thanks for the input.
UPDATE 2009-03-05
To clarify my situation - the "deployments" in this system are far more frequent than a typical web application. The web site is the front end for a back office CMS. Each time content is published in the CMS, new pages (aspx, html, etc) are automatically pushed to the live site. The deployments are basically "on demand". Theoretically, this push could happen several times within a minute or more. So I'm not sure it would be practical to deploy one web server at time. Thoughts?
I'd share the load between the 4 servers. It's not that many.
You don't want that single point of contention either when deploying nor that single point of failure in production.
When deploying, you can do them 1 at a time. Your deployment tools should automate this by notifying the load balancer that the server shouldn't be used, deploying the code, any pre-compilation work needed, and finally notifying the load balancer that the server is ready.
We used this strategy in a 200+ web server farm and it worked nicely for deploying without service interruption.
If your main concern is performance, which I assume it is since you're spending all this money on hardware, then it doesn't really make sense to share a network filesystem just for convenience sake. Even if the network drives are extremely high performing, they won't perform as well as native drives.
Deploying your web assets are automated anyway (right?) so doing it in multiples isn't really much of an inconvenience.
If it is more complicated than you're letting on, then maybe something like DeltaCopy would be useful to keep those disks in sync.
One reason the central share is bad is because it makes the NIC on the share server the bottleneck for the whole farm and creates a single point of failure.
With IIS6 and 7, the scenario of using a network single share across N attached web/app server machines is explicitly supported. MS did a ton of perf testing to make sure this scenario works well. Yes, caching is used. With a dual-NIC server, one for the public internet and one for the private network, you'll get really good performance. The deployment is bulletproof.
It's worth taking the time to benchmark it.
You can also evaluate a ASP.NET Virtual Path Provider, which would allow you to deploy a single ZIP file for the entire app. Or, with a CMS, you could serve content right out of a content database, rather than a filesystem. This presents some really nice options for versioning.
VPP For ZIP via #ZipLib.
VPP for ZIP via DotNetZip.
In an ideal high-availability situation, there should be no single point of failure.
That means a single box with the web pages on it is a no-no. Having done HA work for a major Telco, I would initially propose the following:
Each of the four servers has it's own copy of the data.
At a quiet time, bring two of the servers off-line (i.e., modify the HA balancer to remove them).
Update the two off-line servers.
Modify the HA balancer to start using the two new servers and not the two old servers.
Test that to ensure correctness.
Update the two other servers then bring them online.
That's how you can do it without extra hardware. In the anal-retentive world of the Telco I worked for, here's what we would have done:
We would have had eight servers (at the time, we had more money than you could poke a stick at). When the time came for transition, the four offline servers would be set up with the new data.
Then the HA balancer would be modified to use the four new servers and stop using the old servers. This made switchover (and, more importantly, switchback if we stuffed up) a very fast and painless process.
Only when the new servers had been running for a while would we consider the next switchover. Up until that point, the four old servers were kept off-line but ready, just in case.
To get the same effect with less financial outlay, you could have extra disks rather than whole extra servers. Recovery wouldn't be quite as quick since you'd have to power down a server to put the old disk back in, but it would still be faster than a restore operation.
Use a deployment tool, with a process that deploys one at a time and the rest of the system keeps working (as Mufaka said). This is a tried process that will work with both content files and any compiled piece of the application (which deploy causes a recycle of the asp.net process).
Regarding the rate of updates this is something you can control. Have the updates go through a queue, and have a single deployment process that controls when to deploy each item. Notice this doesn't mean you process each update separately, as you can grab the current updates in the queue and deploy them together. Further updates will arrive to the queue, and will be picked up once the current set of updates is over.
Update: About the questions in the comment. This is a custom solution based on my experience with heavy/long processes which needs their rate of updates controlled. I haven't had the need to use this approach for deployment scenarios, as for such dynamic content I usually go with a combination of DB and cache at different levels.
The queue doesn't need to hold the full information, it just need to have the appropriate info (ids/paths) that will let your process pass the info to start the publishing process with an external tool. As it is custom code, you can have it join the information to be published, so you don't have to deal with that in the publishing process/tool.
The DB changes would be done during the publishing process, again you just need to know where the info for the required changes is and let the publishing process/tool handle it. Regarding what to use for the queue, the main ones I have used is msmq and a custom implementation with info in sql server. The queue is just there to control the rate of the updates, so you don't need anything specially targeted at deployments.
Update 2: make sure your DB changes are backwards compatible. This is really important, when you are pushing changes live to different servers.
I was in charge of development for a game website that had 60 million hits a month. The way we did it was option #1. User did have the ability to upload images and such and those were put on a NAS that was shared between the servers. It worked out pretty well. I'm assuming that you are also doing page caching and so on, on the application side of the house. I would also deploy on demand, the new pages to all servers simultaneously.
What you gain on NLB with the 4IIS you loose it with the BottleNeck with the app server.
For scalability I'll recommend the applications on the front end web servers.
Here in my company we are implementing that solution. The .NET app in the front ends and an APP server for Sharepoint + a SQL 2008 Cluster.
Hope it helps!
regards!
We have a similar situation to you and our solution is to use a publisher/subscriber model. Our CMS app stores the actual files in a database and notifies a publishing service when a file has been created or updated. This publisher then notifies all the subscribing web applications and they then go and get the file from the database and place it on their file systems.
We have the subscribers set in a config file on the publisher but you could go the whole hog and have the web app do the subscription itself on app startup to make it even easier to manage.
You could use a UNC for the storage, we chose a DB for convenience and portability between or production and test environments (we simply copy the DB back and we have all the live site files as well as the data).
A very simple method of deploying to multiple servers (once the nodes are set up correctly) is to use robocopy.
Preferably you'd have a small staging server for testing and then you'd 'robocopy' to all deployment servers (instead of using a network share).
robocopy is included in the MS ResourceKit - use it with the /MIR switch.
To give you some food for thought you could look at something like Microsoft's Live Mesh
. I'm not saying it's the answer for you but the storage model it uses may be.
With the Mesh you download a small Windows Service onto each Windows machine you want in your Mesh and then nominate folders on your system that are part of the mesh. When you copy a file into a Live Mesh folder - which is the exact same operation as copying to any other foler on your system - the service takes care of syncing that file to all your other participating devices.
As an example I keep all my code source files in a Mesh folder and have them synced between work and home. I don't have to do anything at all to keep them in sync the action of saving a file in VS.Net, notepad or any other app initiates the update.
If you have a web site with frequently changing files that need to go to multiple servers, and presumably mutliple authors for those changes, then you could put the Mesh service on each web server and as authors added, changed or removed files the updates would be pushed automatically. As far as the authors go they would just be saving their files to a normal old folder on their computer.
Assuming your IIS servers are running Windows Server 2003 R2 or better, definitely look into DFS Replication. Each server has it's own copy of the files which eliminates a shared network bottleneck like many others have warned against. Deployment is as simple as copying your changes to any one of the servers in the replication group (assuming a full mesh topology). Replication takes care of the rest automatically including using remote differential compression to only send the deltas of files that have changed.
We're pretty happy using 4 web servers each with a local copy of the pages and a SQL Server with a fail over cluster.