Apologies in advance for my little knowledge of AWS
I'm trying to draw parallels between my current setup on Heroku to a move to AWS. I've run into some memory issues on Heroku because of some machine learning models I'm running and Heroku seems too expensive for my needs.
I was recommenced to move to aws using fargate which would be a better fit for my app. Below is my whole architecture, I'm hoping for some guidance on my direction of what I have and where I plan to go.
A django application running on heroku.
The base of functionality is the user uploads a video from their mobile device and uploads it to s3. A message from SNS is sent to my Heroku server that the upload is completed. The server kicks off a celery task that downloads the video from s3 and uses a machine learning model to do some natural language processing, then saves the results to my postresql database. Obviously this is very compute intensive, so I've run into some memory issues and can for-see scaling issues to come.
After lots of tweaking and attempts to no avail, I've decided to move over to AWS and leverage some of the cost benefits that I've seen in comparison to heroku of running more memory intensive tasks.
I should also mention there is a web interface involved with this django project and it isn't just a REST Api.
As far as AWS goes, I'm looking for a bit of direction. Possibly just a rough outline of the architecture I should look deeper into.
My first plan is to dockerize my application and go from there...but I'm a bit stuck on how my application fits (website, rest api, worker threads) into the AWS ecosystem.
AWS is a great fit for the application you describe. AWS Fargate / RDS will host your Django application. You have the option of using AWS Batch to handle your processing. One huge advantage is the ability to scale according to the needs of your application.
This image is one possible way to structure your application. It's a lot of work to get to this point, but AWS offers a lot of power and flexibility for reasonable costs IMO.
Related
I am trying to find the best way to architect a low cost solution to provide an on-demand web server for a certain amount of time.
The context is as follows: I have some large amount of data sitting on S3. From time to time, users will want to consult that data. I've written a Flask app that can display the data in a nice way for them. Beign poorly written, it really only accepts a single user session at the time. Currently therefore they have to download the Flask app and run it on their own machine.
I would like to find a way for users to request a cloud-based web server that would run the Flask app (through a docker container for example) on-demand, and give them access to it quickly, without having to do much if anything on their own machine.
Every user wanting to view the data would have their own web server created on demand (to avoid multiple users sharing the same web server, which wouldn't work with my Flask app)
Critically, and in order to avoid cost, the web server would terminate itself automatically after some (configurable) idle time (possibly with the Flask app informing the user that it's about to shut down, so that they can "renew" the lease).
Initially I thought that maybe AWS Fargate would be good: it can run docker instances, is quite configurable in terms of CPU/disk it can get (my Flask app is resource-hungry), and at least on paper could be used in a way that there is zero cost when users are not consulting the data (bar S3 costs naturally). But it's when it comes to the detail that I'm not sure...
How to ensure that every new user gets their own Fargate instance?
How to shut-down the instance automatically after idle time?
Is Fargate quick enough in terms of boot time?
The closest I can think is AWS App Runner. It's built on top of Fargate and it provides an intelligent scale out mechanism (probably you are not interested in this) as well as a scale to (almost) 0 capability. The way it works is that when the endpoint is solicited and it's doing work you pay for the entire fargate task (cpu/memory) you have selected in the configuration. If the endpoint is doing nothing you only pay for the memory (note the memory cost is roughly 20% of the entire cost so it's not scale to 0 but "quasi"). Checkout the pricing examples at the bottom of this page.
Please note you can further optimize costs by pausing/starting the endpoint (when it's paused you pay nothing) but in that case you need to create the logic that pauses/restarts it.
Another option you may want to explore is using Lambda this way (which would allow you to use the same container image and benefit from the intrinsic scale to 0 of Lambda). But given your comment "Lambda doesn’t have enough power, and the timeout is not flexible" may be a show stopper.
I have worked mostly with monolithic web applications over the years and have not spent very much time looking at Django high-availability scaling solutions.
There are plenty of NGINX/Postgres/Django/Docker builds on hub.docker.com but not one that I could find that would be a good starting point for a scalable Django web application.
Ideally the Docker project would include:
A web container configuration that easily allows adding new web containers to web app
A database container configuration that easily allows adding new database shards
Django microservice examples would also be a plus
Unfortunately, I do not have very much experience with Kubernetes and Docker swarms.
If there are none, I may make this my next github.com project.
Thank you in advance.
That is a very broad request. It depends on many factors:
What is the performance requirement?
Make sure, you really need that kind of scaling. In most cases, a single good server with docker-compose can handle your needs. If you want to reduce risk of downtime, create 2 servers, add a load balancer in between them and extract shared services like DB or Caching into another Service and have both server instances use them.
How do you want to run your applications?
Docker-Compose:
Checkout https://github.com/pydanny/cookiecutter-django on how to do it with docker-compose on a single server.
Kubernetes:
Django is quite good to run in Kubernetes, I am running several applications on Kubernetes. The issue with that is, you need to setup all other services properly (redis, DB, ElasticSearch, etc.). Each of those services run independently of your main Django app and need to be connected through libraries like haystack or python-redis.
Heroku & others
There are also providers like Heroku that offer a lot the auto scaling for a price. If price is less of a concern, go with these solutions because they are very easy to setup and maintain.
How scalable should your DB be?
If you are trying to setup your own DB cluster across different servers/regions, you will spend a lot of time building and maintaining it. I would recommend, use DB services like AWS RDS. They do this for you with easy setup and maintenance. You can configure how scalable it should be. It costs some money, but it's the least effort solution.
Django advises on using a Redis or Memcached cache for high traffic sites, to cut down on the work done by the server.
Apps running on Amazon Lambda via Zappa have fantastic horizontal scale-ability. There does not seem to be the need to minimise the processing efforts of a server when another server can be fired up easily and very cheaply.
Are Caches such as Memcached and Redis redundant when using server-less architectures?
UPDATE: having CDN (eg cloudfront) infront of your app is still adviseable (eg by Zappa).
I think that a serverless architecture might change the equation a bit when it comes to application caches. It does solve some of the things that a cache helps with.
One very important thing that it doesn't solve, though, is database load, which will probably be the bottleneck in a serverless architecture. (It might even make it worse, due to the difficulty of connection pooling.)
So I expect that serverless applications will still make full use of the application cache.
I want to host a scalable blog or application of this sort in nodeJS on AWS making use of AWS technologies. The idea here is to have a small EC2 server that is not responsible for serving the website, but only for running the CMS/admin panel. While these operations could be serverless as well, I think having a dedicated small VM EC2 instance could be more efficient, and works better with existing frameworks, etc.
In my diagram above, you can see there's two type of users audiences and admin/writers. Admin CRUD operations also cause lambda to run. Lambda generates the static site after Admin changes, which is delivered to S3. Users are directed to the static site hosted in S3. Only admins/writers have access to the server-connecting part of the site.
I think this is a good design for an extremely scalable and relatively cheap site, as long as the user-facing side is all static. An alternative to this is a CDN, but then I have to deal with cache invalidation issues, a site that updates slower, and a larger server.
This seems like a win-win to me. Feedback?
This ought to be a comment rather than an answer, but as I don't have enough points...
There are a couple of other considerations for this architecture. Lambda functions are great for scaling out microservices horizontally with each small function being executed in parallel tens or hundreds of times. Generation of a static site is typically a single threaded operation so you may not see the gains you expect, you'll also need to watch the timeout period (maximum 300 seconds currently) and make sure that you can generate the site in that time. Of course if you are not running Lambda code you are not getting charged.
For your admin frontend I would suggest ElasticBeanstalk, even if you peg it at a single instance, it gives you lots of great features like rolling updates.
Good luck with the project.
I have a web app running on php, mysql, apache on a virtual windows server. I want to redesign it so it is scalable (for fun so I can learn new things) on AWS.
I can see how to setup an EC2 and dump it all in there but I want to make it scalable and take advantage of all the cool features on AWS.
I've tried googling but just can't find a simple guide (note - I have no command line experience of Linux)
Can anyone direct me to detailed resources that can lead me through the steps and teach me? Or alternatively, summarise the steps in an answer so I can research based on what you say.
Thanks
AWS is growing and changing all the time, so there aren't a lot of books to help. Amazon offers training that's excellent. I took their three day class on Architecting with AWS that seems to be just what you're looking for.
Of course, not everyone can afford to spend the travel time and money to attend a class. The AWS re:Invent conference in November 2012 had a lot of sessions related to what you want, and most (maybe all) of the sessions have videos available online for free. Building Web Scale Applications With AWS is probably relevant (slides and video available), as is Dissecting an Internet-Scale Application (slides and video available).
A great way to understand these options better is by fiddling with your existing application on AWS. It will be easy to just move it to an EC2 instance in AWS, then start taking more advantage of what's available. The first thing I'd do is get rid of the MySql server on your own machine and use one offered with RDS. Once that's stable, create one or more read replicas in RDS, and change your application to read from them for most operations, reading from the main (writable) database only when you need completely current results.
Does your application keep any data on the web server, other than in the database? If so, get rid of all local storage by moving that data off the EC2 instance. Some of it might go to the database, some (like big files) might be suitable for S3. DynamoDB is a good place for things like session data.
All of the above reduces the load on the web server to just your application code, which helps with scalability. And now that you keep no state on the web server, you can use ELB and Auto-scaling to automatically run multiple web servers (and even automatically launch more as needed) to handle greater load.
Does the application have any long running, intensive operations that you now perform on demand from a web request? Consider not performing the operation when asked, but instead queueing the request using SQS, and just telling the user you'll get to it. Now have long running processes (or cron jobs or scheduled tasks) check the queue regularly, run the requested operation, and email the result (using SES) back to the user. To really scale up, you can move those jobs off your web server to dedicated machines, and again use auto-scaling if needed.
Do you need bigger machines, or perhaps can live with smaller ones? CloudWatch metrics can show you how much IO, memory, and CPU are used over time. You can use provisioned IOPS with EC2 or RDS instances to improve performance (at a cost) as needed, and use difference size instances for more memory or CPU.
All this AWS setup and configuration can be done with the AWS web console, or command-line tools, or SDKs available in many languages (Python's boto library is great). After learning the basics, look into CloudFormation to automate it better (I've written a couple of posts about that so far).
That's a bit of the 10,000 foot high view of one approach. You'll need to discover the details of each AWS service when you try to use them. AWS has good documentation about all of them.
Depending on how you look at it, this is more of a comment than it is an answer, but it was too long to write as a comment.
What you're asking for really can't be answered on SO--it's a huge, complex question. You're basically asking is "How to I design a highly-scalable, durable application that can be deployed on a cloud-based platform?" The answer depends largely on:
The specifics of your application--what does it do and how does it work?
Your tolerance for downtime balanced against your budget
Your present development and deployment workflow
The resources/skill sets you have on-staff to support the application
What your launch time frame looks like.
I run a software consulting company that specializes in consulting on Amazon Web Services architecture. About 80% of our business is investigating and answering these questions for our clients. It's a multi-week long project each time.
However, to get you pointed in the right direction, I'd recommend that you look at Elastic Beanstalk. It's a PaaS-like service that abstracts away the underlying AWS resources, making AWS easier to use for developers who don't have a lot of sysadmin experience. Think of it as "training wheels" for designing an autoscaling application on AWS.