I am building a MySQL database with a web front end for a client. The client and their staff will use this webapp on a daily basis, creating anywhere from a few thousand, to possibly a few hundred thousand records annually. I just picked up a second client who wishes to have the same product and will probably be creating the same number of records annually, possibly more.
In the future I hope to pick up a few more clients. In the next few years I could have up to 5 databases & web front ends running for 5 distinct clients, all needing tight security while creating, likely, millions of records annually (cumulatively across all the databases).
I would like to run all of this with Amazon's EC2 service but am having difficulty deciding on what type of instance to run. I am not sure if I should have several distinct Linux instances, one per client, or run one "large" instance which would manage all the clients' databases and web front ends.
I know that hardware configuration is rather specific to the task at hand. The web front ends will be using JQuery to make MySQL queries "pretty" and I will likely be doing some graphing of data (again with JQuery). The front ends will be using SSL for security, which I understand can add some overhead to the network speed.
I'm looking for some of your thoughts on this situation.
Thanks
Use the tools that are available. The Amazon RDS service lets you run a MySQL database in the cloud with no extra effort. You can scale it up and down as you need - start small, and then as you hit your limits, add extra capacity (at extra cost).
Next, use Elastic Load Balancing (ELB) with an SSL certificate, so you offload the overhead of SSL decryption to an Amazon service.
If you're using Java for your webapp, you could use Elastic Beanstalk to handle the whole hosting process for you.
Don't be afraid to experiment - you can always resize instances with no data loss (if they boot from an EBS volume) and you can always create and delete instances. Scaling horizontally is often better than scaling vertically, as you can spread your instances across multiple Availability Zones.
Good luck!
Related
I have a huge Laravel application, it contitutes of a dashboard where users have many different complex cruds that are all saved in a database with more than 100 tables, it also have an api for mobile app that can reach a peack of 300 thousand requests per minute. As the app scales I'm having issues with performance, as all is in one single aws hosted ec2 server, by all I mean all app images, company logos etc, all the resources for the dashboard and all the api for mobile app. I need a solution for this problem, should I separate all in different machines? If so, how?
All the app is currently running PHP 7.2 and Laravel 5.5 on a aws ec2 12xlarge instance.
You are asking us some basic concept of scalability in the Cloud.
I will try to give one direction you could follow.
The current design is very bad for couple of reasons:
As you said, it cannot scale because everything hold in one server;
Because everything hold in one server, I hope you have automated backup in case your instance fails
The only thing you can do in this configuration is to scale vertically, instead of horizontally (using more instances instead of a big one)
Files are on the same disk, so you cannot scale
In term of application (Laravel), you are running with a monolith: everything in one app. I don't need to tell you that it doesn't scale well but it can.
Lets dive into to main topic: How to scale this big fat instance?
First of all, you should use a shared space for your images. There are NFS (expensive), S3 (cheap) and shared EBS (cheaper than NFS, but can only be used by a limited number of instances at a time). I would use S3.
We can skip the part where you need to refactor your monolith application to a micro-service architecture, with smaller parts. It can be done if you have time and money, but I would say it is not the priority to your scaling issue.
I don't know if the database is also on the same EBS or not. If it is, use RDS: it is an almost no management managed database. You can have multi-AZ for very high availability, or Multi-AZ DB Cluster (new) which will spread the load for reads into 2 shadow instances.
To go further with your application, you can also run mobile and web on separated instances, to avoid one impacting the other.
And...That's all! Laravel has a transparent configuration mechanism for the storage to easily switch from one to another.
When I say "That's all", I mean in term of way to improve the scaling.
You will have to migrate the data from the EC2 database to RDS, perform the transfer of your images from the EBS to S3, create an autoscaling group, create an IAM Instance role for your EC2 Autoscaling group to access S3, know when the application has peaks so you can do a predictive scaling, etc.
I would recommand using IaC for this, like CloudFormation or Terraform.
This is the tip of the iceberg, but I hope you can start building a more robust system with these tips.
I have a small web and mobile application partly running on a webserver written in PHP (Symfony). I have a few clients using the application, and slowly expanding to more clients.
My back-end architecture looks like this at the moment:
Database is Cloud SQL running on GCP (every client has it's own
database instance)
Files are stored on Cloud Storage (GCP) or S3 (AWS), depending on the client. (every client has it's own bucket)
PHP application is running in a Compute Engine VM (GCP), (every client has it's own VM)
Now the thing is, in the PHP code, the only thing client specific is a settings file with the database credentials and the Storage/S3 keys in it. All the other code is exactly the same for every client. And mostly the different VMs sit idle all day, waiting on a few hours usage per client.
I'm trying to find a way to avoid having to create and maintain a VM for every customer. How could I rearchitect my back-end so I can keep separate Databases and Storage Buckets per client, but only scale up my VM's when capacity is needed?
I'm hearing alot about Docker, was thinking about keeping db credentials and keys in a Redis DB or Cloud Datastore, was looking at Heroku, AppEngine, Elastic Beanstalk, ...
This is my ideal scenario as I see it now
An incoming request is done, hits a load balancer
From the request, determine which client the request is for
Find the correct settings file, or credentials from a DB
Inject the settings file in an unused "container"
Handle the request
Make the container idle again
And somewhere in there, determine based on the the amount of incoming requests or traffic, if I need to spin up or spin down containers to handle the extra or reduced (temporary) load.
All this information overload has me stuck, I have no idea what direction to choose, and I fail seeing how implementing any of the above technologies will actually fix my problem.
There are several ways do it with minimum efforts:
Rewrite loading of config file depending from customer
Make several back-end web sites on one VM (best choice i think)
For the first time I am developing an app that requires quite a bit of scaling, I have never had an application need to run on multiple instances before.
How is this normally achieved? Do I cluster SQL servers then mirror the programming across all servers and use load balancing?
Or do I separate out the functionality to run some on one server some on another?
Also how do I push out code to all my EC2 windows instances?
This will depend on the requirements you have. But as a general guideline (I am assuming a website) I would separate db, webserver, caching server etc to different instance(s) and use s3(+cloudfont) for static assets. I would also make sure that some proper rate limiting is in place so that only legitimate load is on the infrastructure.
For RDBMS server I might setup a master-slave db setup (RDS makes this easier), use db sharding etc. DB cluster solutions also exists which will be more complex to setup but simplifies database access for the application programmer. I would also check all the db queries and the tune db/sql queries accordingly. In some cases pure NoSQL type databases might be better than RDBMS or a mix of both where the application switches between them depending on the data required.
For webserver I will setup a loadbalancer and then use autoscaling on the webserver instance(s) behind the loadbalancer. Something similar will apply for app server if any. I will also tune the web servers settings.
Caching server will also be separated into its on cluster of instance(s). ElastiCache seems like a nice service. Redis has comparable performance to memcache but has more features(like lists, sets etc) which might come in handy when scaling.
Disclaimer - I'm not going to mention any Windows specifics because I have always worked on Unix machines. These guidelines are fairly generic.
This is a subjective question and everyone would tailor one's own system in a unique style. Here are a few guidelines I follow.
If it's a web application, separate the presentation (front-end), middleware (APIs) and database layers. A sliced architecture scales the best as compared to a monolithic application.
Database - Amazon provides excellent and highly available services (unless you are on us-east availability zone) for SQL and NoSQL data stores. You might want to check out RDS for Relational databases and DynamoDb for NoSQL. Both scale well and you need not worry about managing and load sharding/clustering your data stores once you launch them.
Middleware APIs - This is a crucial part. It is important to have a set of APIs (preferably REST, but you could pretty much use anything here) which expose your back-end functionality as a service. A service oriented architecture can be scaled very easily to cater multiple front-facing clients such as web, mobile, desktop, third-party widgets, etc. Middleware APIs should typically NOT be where your business logic is processed, most of it (or all of it) should be translated to database lookups/queries for higher performance. These services could be load balanced for high availability. Amazon's Elastic Load Balancers (ELB) are good for starters. If you want to get into some more customization like blocking traffic for certain set of IP addresses, performing Blue/Green deployments, then maybe you should consider HAProxy load balancers deployed to separate instances.
Front-end - This is where your presentation layer should reside. It should avoid any direct database queries except for the ones which are limited to the scope of the front-end e.g.: a simple Redis call to get the latest cache keys for front-end fragments. Here is where you could pretty much perform a lot of caching, right from the service calls to the front-end fragments. You could use AWS CloudFront for static assets delivery and AWS ElastiCache for your cache store. ElastiCache is nothing but a managed memcached cluster. You should even consider load balancing the front-end nodes behind an ELB.
All this can be bundled and deployed with AutoScaling using AWS Elastic Beanstalk. It currently supports ASP .NET, PHP, Python, Java and Ruby containers. AWS Elastic Beanstalk still has it's own limitations but is a very cool way to manage your infrastructure with the least hassle for monitoring, scaling and load balancing.
Tip: Identifying the read and write intensive areas of your application helps a lot. You could then go ahead and slice your infrastructure accordingly and perform required optimizations with a read or write focus at a time.
To sum it all, Amazon AWS has pretty much everything you could possibly use to craft your server topology. It's upon you to choose components.
Hope this helps!
The way I would do it would be, to have 1 server as the DB server with mysql running on it. All my data on memcached, which can span across multiple servers and my clients with a simple "if not on memcached, read from db, put it on memcached and return".
Memcached is very easy to scale, as compared to a DB. A db scaling takes a lot of administrative effort. Its a pain to get it right and working. So I choose memcached. Infact I have extra memcached servers up, just to manage downtime (if any of my memcached) servers.
My data is mostly read, and few writes. And when writes happen, I push the data to memcached too. All in all this works better for me, code, administrative, fallback, failover, loadbalancing way. All win. You just need to code a "little" bit better.
Clustering mysql is more tempting, as it seems more easy to code, deploy, maintain and keep up and performing. Remember mysql is harddisk based, and memcached is memory based, so by nature its much more faster (10 times atleast). And since it takes over all the read load from the db, your db config can be REALLY simple.
I really hope someone points to a contrary argument here, I would love to hear it.
I'm newbie on AWS, and it has so many products (EC2, Load Balancer, EBS, S3, SimpleDB etc.), and so many docs, that I can't figure out where I must start from.
My goal is to be ready for scalability.
Suppose I want to set up a simple webserver, which access a database in mongolab. I suppose I need one EC2 instance to run it. At this point, do I need something more (EBS, S3, etc.)?
At some point of time, my app has reached enough traffic and I must scale it. I was thinking of starting a new copy (instance) of my EC2 machine. But then it will have another IP. So, how traffic is distributed between both EC2 instances? Is that did automatically? Must I hire a Load Balancer service to distribute the traffic? And then will I have to pay for 2 EC2 instances and 1 LB? At this point, do I need something more (e.g.: Elastic IP)?
Welcome to the club Sony Santos,
AWS is a very powerfull architecture, but with this power comes responsibility. I and presumably many others have learned the hard way building applications using AWS's services.
You ask, where do I start? This is actually a very good question, but you probably won't like my answer. You need to read and do research about all the technologies offered by amazon and even other providers such as Rackspace, GoGrid, Google's Cloud and Azure. Amazon is not easy to get going but its not meant to be really, its focus is more about being very customizable and have a very extensive api. But lets get back to your question.
To run a simple webserver you would need to start an EC2 instance this instance by default runs on a diskdrive called EBS. Essentially an EBS drive is a normal harddrive except that you can do lots of other cool stuff with it like take it off one server and move it to another. S3 is really more of a file storage system its more useful if you have a bunch of images or if you want to store a lot of backups of your databases etc, but its not a requirement for a simple webserver. Just running an EC2 instance is all you need, everything else will happen behind the scenes.
If you app reaches a lot of traffic you have two options. You can scale your machine up by shutting it off and starting it with a larger instance. Generally speaking this is the easiest thing to do, but you'll get to a point where you either cannot handle all the traffic with 1 instance even at the larger size and you'll decide you need two OR you'll want a more fault tolerant application that will still be online in the event of a failure or update.
If you create a second instance you will need to do some form of loadbalancing. I recommend using amazons Elastic Load Balancer as its easy to configure and its integration with the cloud is better than using Round Robin DNS or a application like haproxy. Elastic Load Balancers are not expensive, I believe they cost around $18 / month + data that's passed between the loadbalancer.
But no, you don't need anything else to do scale up your site. 2 EC2 instances and a ELB will do the trick.
Additional questions you didn't ask but probably should have.
How often does an EC2 instance experience hardware failure and crash my server. What can I do if this happens?
It happens frequently, usually in batches. Sometimes I go months without any problems then I will get a few servers crash at a time. But its defiantly something you should plan for I didn't in the beginning and I paid for it. Make sure you create scripts and have backups and a backup plan ready incase your server fails. Be ok with it being down or have a load balanced solution from day 1.
Whats the hardest part about scalabilty?
Testing testing testing testing... Don't ever assume anything. Also be prepared for sudden spikes in your traffic. You have to be prepared for anything if you page goes from 1 to 1000 people over night are you prepared to handle it? Have you tested what you "think" will happen?
Best of luck and have fun... I know I have :)
I've been tasked with determining if Amazon EC2 is something we should move our ecommerce site to. We currently use Amazon S3 for a lot of images and files. The cost would go up by about $20/mo for our host costs, but we could sell our server for a few thousand dollars. This all came up because right now there are no procedures in place if something happened to our server.
How reliable is Amazon EC2? Is the redundancy good, I don't see anything about this in the FAQ and it's a problem on our current system I'm looking to solve.
Are elastic IPs beneficial? It sounds like you could point DNS to that IP and then on Amazon's end, reroute that IP address to any EC2 instance so you could easily get another instance up and running if the first one failed.
I'm aware of scalability, it's the redundancy and reliability that I'm asking about.
At work, I've had something like 20-40 instances running at all times for over a year. I think we've had 1-3 alert emails come from amazon suggesting that we terminate and boot another instance (presumably because they are detecting possible failure in the underlying hardware). We've never had an instance go down suddenly, which seems rather good.
Elastic IP's are amazing and are part of the solution. The other part is being able to rapidly bring up new instances. I've learned that you shouldn't care about instances going down, that it's more important to use proper load balancing and be able to bring up commodity instances quickly.
Yes, it's very good. If you aren't able to put together a concurrent redundancy (where you have multiple servers fulfilling requests simultaneously), using the elastic IP to quickly redirect to another EC2 instance would be a way to minimize downtime.
Yeah I think moving from inhouse server to Amazon will definitely make a lot of sense economically. EBS backed instances ensure that even if the machine gets rebooted, the transient memory is not lost. And if you have a clear separation between your application and data layer and can have them on different machines, then you can build even better redundancy for your data.
For ex, if you use mysql, then you can consider using Amazon RDS service - which gives you a highly available and reliable MySQL instance, fully managed (patches and all). The application layer then can be made more resilient by having more smaller instances rather than one larger instance, through load balancing.
The cost you will save on is really hardware maintenance and the cost you would have to incur to build in disaster recovery.