Curious if this is possible:
We have a web application that at MOST times, works just fine with our single small instance. However, when we get multiple customers running simultaneously intense queries (we are a cloud scheduling service); our instance bogs way down to near 80% cpu load and becomes pretty unresponsive.
Is there a way to have AWS fire up another small instance (or a few), quickly, only for the times that its operating under this intense load? BUT, the real question is how does this work when we have very frequent programming updates to our application? Do we have to manually create a new image everytime we upload a code change???
Thanks
You should never be running anything important on a single EC2 instance. Instances can--and do--go offline randomly. Always use an autoscaling (AS) group that spans multiple availability zones. An AS group will automatically bring new instances online when you hit a certain trigger (in your case, CPU utilization). And then it will scale down the instances when traffic subsides. Autoscaling is the heart and soul of AWS and if you're not using it, you might as well be using a cheaper (and more durable) VPS host.
No, you don't want to be creating a new AMI for each code release. Ideally you should use a base AMI (like one of Amazon's official ones) and then have it auto-provision at boot. You can use the "user data" field when you launch an AMI to bootstrap this process. It can be as simple as a bash script that pulls from your Git repo to as something as sophisticated as Puppet or Chef.
The only time I create custom AMI's is if the provisioning process just takes too long. However that can almost always be solved by storing the needed files in S3.
Related
I am new to AWS and recently set up a free t3.micro instance. My goal is to achieve a stable hosting of an Angular application with 2 spring boot services. I got everything working, but after a while, the spring boot services are not reachable anymore. When i redeploy the service it will run again. The spring boot services are packed as jar and after the deployment the process is started as a java process.
I thought AWS guarantees permanent availability out of the box. Do i need some more setup such as autoscaling to achieve the desired uptime of the services or is the t3.micro instance not suffienciently performant, so that i need to upgrade to a stronger instance to avoid the problem?
It depends :)
I think you did the right thing by starting with a small instance type and avoid over provisioning in the first place. T3 instance types are generally beneficial for 'burst' usage scenarios i.e. your application sporadically needs a compute spike but not a persistent one. T3 instance types usually work with credits based system, where you instance 'earns' credits when it is idle, and that buffer is always available in times of need (but only until consumed entirely). Then you need to wait for some time window again and earn the credits back.
For your current problem, I think first approach can be to get an idea of the current usage by going through the 'Monitoring' tab on the EC2 instance details page. This will help you understand if the needs are more compute related or i/o related and then you can choose an appropriate instance type from :
https://aws.amazon.com/ec2/instance-types
Next step could also be to profile your application and understand the memory, compute utilisation better. AWS does guarantee availability/durability of resources, but how you consume those resources is more of an application thing, which AWS does not guarantee/control
For your ideas around, autoscaling and availability, it again depends on what your needs are in terms of cost, outages in AWS data centres etc. To have a reliable production setup, you could consider them, but not something really important in the first place.
The core of my question is whether or not there are downsides to using an Amazon Machine Image + Micro Spot instances to run a task, vs using the Elastic Container Service (ECS).
Here's my situation: I have the need to run a task on demand that is triggered by a remote web hook.
There is the possibility this task can get triggered 10 times in a row, or go weeks w/o ever executing, so I definitely want a service that only runs (and bills) on demand.
My plan is to point the webhook to a Lambda function, but then the question is what to have the Lambda function do.
Tho it doesn't take very long, this task requires several different runtimes (Powershell Core, Python, PHP, Git) to get its job done, so Lambda isn't really a possibility as I'd hit the deployment package size limit. But I can use Lambda to kick off the job.
What I started doing was creating an AMI that has all the necessary runtimes and code, then using a Spot request to launch an instance, have it execute the operation via a startup script passed in via userdata, then shut itself down when it's done. I'd have to put in some rate control logic to prevent two from running at once, but that's a solvable problem.
I hesitated half way through developing this solution when I realized I could probably do this with a docker container on ECS using Fargate.
I just don't know if there is any benefit of putting in the additional development time of switching to a docker container, when I am not a docker pro and already have the AMI configured. Plus ECS/Fargate is actually more expensive than just running a micro instance.
Are these any concerns about spinning up short-lived (<5min) spot requests (t3a-micro) where there could be a dozen fired off in a single day? Are there rate limits about this? Will I get an angry email from AWS telling me to knock it off? Are there other reasons ECS is the only right answer? Something else entirely?
Your solution using spot instance and AMI is a valid one, though I've experienced slow times to get a spot instance in the past. You also incur the AMI startup time.
As mentioned in the comments, you will incur a minimum of 1 hour charge for the instance, so you should leave your instance up for the hour before terminating, in case more requests can come in the same hour.
IMHO you should build it all with lambda. By splitting the workload for each runtime into its own lambda you can make it work.
AWS supports python, powershell runtimes, and you can create a custom PHP one. Chain them together with your glue of choice, SNS, SQS, direct invocation, or Step Functions, and you have the most cost effective solution. You also get the benefits of better and independent maintenance for each function/runtime.
Put the initial lambda behind API gateway and you will get rate limiting capabiltiy too.
I have a very basic idea on servers. So far I have only worked with few Ubuntu VPS server which I can easily maintain, install a database, upload my code and run my projects. And to save static data like image/video I use local SSD storage of my server.
Now I got some projects where AWS is required to use. In the beginning, I thought it would be very similar to my normal Ubuntu based VPS server. But while I start researching/reading articles also their own docs I find out it has lots more cool features for server and at the same, it's little complicated for a beginner. I would be really glad if someone give his time and reply on these questions of mine to clear concept about AWS of mine and people like me
As my plan is to use one EC2 instance to run my project. But I can see many experts suggest to use Elastic Beanstalk and create EC2 instance inside that. While I can directly run my project with EC2 without taking help from Elastic Beanstalk. So why it's better / what other help do it(Elastic Beanstalk) provide?
When I am checking the pricing of EC2(On-demand > Linux Unix) it says ECU as Variable. What does that mean? And where does ECU work
Instance Storage (GB) as EBS only. Does that mean I can't have any storage with my server I must buy separately? But in my previous VPS server, I use to get fewer storages with my server. Because storage is required if I want to install new software like MySQL/Redis/Python each of them requires local storage. Also if I want to upload my code or few static images it requires storage.
Like storage do I also need to buy other instances for a database? Like if I want to use PostgreSQL as my database do I need to buy AWS RDS or I can install that inside my Linux system?
Lastly, what are the main differences of my normal VPS Linux server and in AWS EC2 Linux server?
Thanks in advance for giving time :)
Let me try to answer your questions inline.
As my plan is to use one EC2 instance to run my project. But I can
see many experts suggest to use Elastic Beanstalk and create EC2
instance inside that. While I can directly run my project with EC2
without taking help from Elastic Beanstalk. So why it's better /
what other help do it(Elastic Beanstalk) provide?
If you are planning to use a single server and a database going with EC2 and RDS would be straightforward. However, if you are planning to set up, autoscaling (automatically increasing the number of servers only when load increases and return back to one server), load balancing and DevOps support, you need to set them up which requires more knowledge on AWS platform. AWS Elastic Beanstalk does these for you automatically, also by giving you the options to select the technology of your application and simply upload the code.
When I am checking the pricing of EC2(On-demand > Linux Unix) it says ECU as Variable. What does that mean? And where does ECU work
ECU is simply a rough figure to compare the processing across multiple EC2 classes that are having the different levels processing power.
Instance Storage (GB) as EBS only. Does that mean I can't have any storage with my server I must buy separately? But in my previous VPS server, I use to get fewer storages with my server. Because storage is required if I want to install new software like MySQL/Redis/Python each of them requires local storage. Also if I want to upload my code or few static images it requires storage.
EBS storage is reliable storage (With internal redundancy) that will last beyond your instance lifetime. Which means, you can upgrade the EC2 class and install software, or store files, which will remain in the EBS volume unless you delete it.
Since you are basically paying for the GBs, you can also create another EBS volume for static files and mount it to the EC2 instance if you want.
Like storage do I also need to buy other instances for a database? Like if I want to use PostgreSQL as my database do I need to buy AWS RDS or I can install that inside my Linux system?
It's not mandatory but recommended since you can even use a smaller instance for a web server and use another one for the DB. It's up to you. For example, the cost would be roughly similar if you use two small EC2 instances for a web server and DB server (Or use RDS) or use a single medium-size EC2 instance where both DB and web is running.
Lastly what are the main differences of my normal VPS Linux server and in AWS EC2 Linux server?
You will get more options in terms of selecting the hardware underneath since AWS provides different configuration options. In addition, EC2 instances are able to utilize the AWS ecosystem for Networking, Security, Load balancing & etc for better-optimized solution architectures in terms of reliability, security, performance & etc.
Q1) Beanstalk is a management application. AWS has several: CloudFormation, OpsWorks. Third party vendors have their own: Chef, Ansible, Terraform, etc. I really like Beanstalk and how it makes deploying code very easy for small sites (one command). I can scale up or scale down with a button push. I also use CloudFormation every day for just about everything.
Q2) ECU is a AWS Equivalent Compute Unit used to compare one instance with another. How does that translate to physical CPUs? Don't know as AWS does not publish its absolute meaning. Use is only to compare EC2 instances.
Q3) When you launch an EC2 instance, you will need storage. This is an additional cost (around $0.10 per GB per month). You will specify the size and type of storage (there are a number of types). There is also Instance Store Volumes. Stay away from these unless you really understand how to use them (they don't persist a shutdown so all data is lost). There are good use cases for Instance Store (AI, Big Data, Image processing), but a website is not one of them.
Q4) If your EC2 instance is big enough (2 GB of memory and larger), you can install PostgreSQL, MySQL, etc on your EC2 instance. Otherwise AWS has a number of database optios: DynamoDB, RDS, Aurora, etc.
Q5) Difficult to answer as each vendor offers its own set of features. EC2 instances are virtual machines. You have control over the raw power of that VM. Most VPS servers have management interfaces that EC2 does not. Usually EC2 is more expensive than VPS servers.
Watch a couple of AWS videos on YouTube. This will help you to understand AWS and why it is so successful in the cloud. Linux Academy, A Cloud Guru, etc. have very good training courses on AWS.
AWS Essentials: EC2 Basics
If you have further questions, open a new StackOverflow question per question. You will seldom get answers to long multi-question questions.
I have a site that I will be launching soon. Not entirely sure how heavy the traffic will get.
I am using Django+Nginx+Gunicorn+Mysql. There will be support for SSL/HTTPS.
As a starting point, I am thinking of having two micro instances balanced by Elastic Load Balancing.
The MySql database will be on one of the instances. If traffic gets heavy, I might move static files to a CDN. The micro instances serve as front-end servers responsible for only churning out HTML/JSON and serving static files. Static files are mainly CSS/js and several images (not many). I foresee database will be read-heavy and less writes.
Questions:
Assuming the traffic rises to 100k page views per day, will the 2 micro instances suffice?
Do I have to move the database to a separate instance? And what instance type would be good?
What if the traffic is only 1k page views per day?
How many gunicorn processes to run on a micro instance?
In general, what type of metrics will help me determine what kind and how many instances I would need? What is the methodology to decide what kind of architecture I would need?
Thanks a lot!
Completely dependant on how dynamic the site is planning to be. Do users generate content towards the service or is it mostly static? If the former you're going to get a lot from putting stuff like avatars, images etc. into S3 and putting that on Cloudfront. Same with your static files... keeping your servers stateless will allow you scale with ease.
At 100k page views a day you will definitely struggle with just micros... you really should only use those in a development environment and aren't meant to handle stuff like serving users. I'd use at a minimum a single small instance in-front of a Load Balancer, may sound strange but you will be able to throw in another instance when things get busy without having to mess with Route 53 or potentially having your site fail. The stateless stuff is quite important now as user-generated assets may only be reference able from one instance and not the other.
At 1k page views I'd still use a small for web serving and another small for MySQL. You can look into RDS which is great if you're doing this solo, forget about needing to upgrade versions and stuff like maintenance, backups etc.
You will also be able to one-click spin up read replicas for peak. Look into the Amazon CLI as well to help automate those tasks. Cronjobs will make it a cinch if you're time stressed otherwise Opsworks, Cloudformation and Auto-Scaling will all help with the above.
Oh and just as a comparison, an Application server of mine running Apache, PHP with APC to serve our users starts to struggle with about 80 concurrent users. Runs on a small EC2 Instance with a Small RDS (which sits at about 15% at the same time as the Application Server is going downhill)
Probably not. Micro instances are not designed for heavy production loads. They use a burstable CPU profile. They can run at 2 ECU for a couple of minutes, and then they get locked at 0.1-0.2 ECU. I tend to like c1.medium, but small may be enough for you.
Maybe, as long as they are spread out during the day and not all in a short window.
1-2 per core. Micro only has 1 core.
Every application is different. The best thing to do is run your own benchmarks using tools like ab (Apache Bench)
Following the AWS best practices architecture diagram is always a good start.
http://media.amazonwebservices.com/architecturecenter/AWS_ac_ra_web_01.pdf
I strongly advise you to store all your files on Amazon S3, and use a Route 53 DNS (or any other DNS if you want) in front of it to distribute the files, because later on if you decide to use CloudFront CDN it will be very easy to change. And, just to mention using CloudFront as CDN will increase your cost only a little bit, not a huge thing.
Doesn't matter the scenario, if we're talking a about production, you should definitely go for separate instances, at least 1 EC2 for web and 1 EC2/RDS for database.
If you are geek and like to get into the nitty gritty details, create your own infrastructure and feel free to use any automation tool (puppet, chef) or not. Or if you just want to collect the profit, or have scarce resources to take care of everything, you should try Elastic Beanstalk (http://docs.aws.amazon.com/elasticbeanstalk/latest/dg/create_deploy_Python_django.html)
Anyway, going to create your own infrastructure or choose elastic beanstalk, always execute stress tests to have a better overview of your capacity planning needs. After you choose your initial environment, stress it using apache bench, siege or whatever other tool you may like.
Hope this helps.
I would suggest to use small instances instead of micro as micro instances often stop responding on heavy load and then it requires a stop-start. Use s3 for static files which helps in faster loading and have a look over cloud front.
The region for instance also helps in serving requests and if you target any specific region, create the instance selecting that region.
Create the database in new instance and attach ebs volume to that instance. Automate backup script to copy database files and store in ebs to avoid any issues. The instance selected here can be iops for faster processing over standard. Aws services provide lot of flexibility but you need to have scripts running to scale up and down the servers as per the timings.
Spot instance can help in future as they come cheap in case you are scaling up.
I have an Amazon EC2 Micro instance running using EBS storage. This more than meets my needs 99.9% of the time, however I need to perform a very intensive database operation as a once off which kills the Micro instance.
Is there a simple way to restart the exact same instance but with lots more power for a temporary period, and then revert back to the Micro instance when I'm done? I thought this seemed more than possible under the cloud based model Amazon uses but it doesn't appear to simply be a matter of shutting down and restarting with more power as I first thought it might be.
If you are manually running the database operation, then you can just create the image of the server, launch a small or a high cpu instance using the same image, run the database operation and then create the image and launch it again as a micro instance. You can also automate this process by writing scripts using AWS APIs.
In case you're using an EBS-backed AMI you don't have to create a new image and launch it. Just stop the machine and issue a simple EC2 API command to change the instance type:
ec2-modify-instance-attribute --instance-type <instance_type> <instance_id>
Keep in mind that not all instance types work for every AMI. The applicable instance types depend on the machine itself and the kernel. You can find a list of available instance types here: http://aws.amazon.com/ec2/instance-types/