I have a basic docker image containing a python script that comes in under 100mb. I'm not sure what distro I'm going to use but preferably one that results in the smallest file size as possible.
The goal is to deploy a docker image on t2.nano ec2 instance but it must meet the following conditions:
from the time a customer requests access via URL, it should respond as quickly as possible, preferably under a few seconds.
the latency between the customer and newly deployed docker ec2 instance should be as small as possible, meaning ec2 on the closest availability region.
Is this possible?
It's not possible to deploy an EC2 instance in under a few seconds, especially not t2.nano type instances. EC2 instances follow the same rules as physical compute resources, thus larger instance types boot faster, and t2.nano is currently the smallest/least powerful/slowest instance size. That said, even the fastest instances would take a minute or so to be provisioned and fully booted.
It sounds like you should look into using AWS Lambda. It's their proprietary, managed, containerized compute resource service, and designed for the kind of workflow you are describing. You don't manage the containers themselves, but deploy the code (of which Python is a supported language) and its dependent libraries to the service, and it handles launching it in a container on demand, with overhead in the sub-second range.
Note that it is not designed for hosting "websites" directly, if that's your intention. Lambda functions are invoked by other AWS services, one of which is API Gateway, which would be the best route in providing a public interface to your Lambda functions. This could be used in conjunction with something like S3 static website hosting to provide the building blocks for a "serverless" web application.
As for your second question, Route 53 does support latency based routing, but I don't believe it supports API Gateway endpoints as targets yet. So if global latency is a big concern, your best bet may be to deploy a few full-time EC2 instances around the world and use latency based routing. If it's mainly static assets you're worried about, CloudFront can cache these at edge locations, as an alternative.
Related
When I select "scheduled job" while initiating resources, how is the process handled internally?
Can I verify the container in ECS? I guess it will use batch jobs for this option.
# copilot init
Note: It's best to run this command in the root of your Git repository.
Welcome to the Copilot CLI! We're going to walk you through some questions
to help you get set up with an application on ECS. An application is a collection of
containerized services that operate together.
Which workload type best represents your architecture? [Use arrows to move, type to filter, ? for more help]
> Load Balanced Web Service
Backend Service
Scheduled Job
What will be the charges if I select backend service or scheduled job?
Copilot uses Fargate containers under the hood; therefore, your charges for a backend service are based on the number of containers you have running and the CPU/memory size of those containers. The minimum container size is 0.25 vCPU and 512 GB of reserved memory.
For other service types, your pricing depends on a few more things.
Load Balanced Web Service
Fargate containers based on size and number (~$9/month for the smallest possible container)
Application Load Balancer (about $20/month depending on traffic)
Backend Service
Fargate containers based on size and number (~$9/month for the smallest possible container)
Scheduled Job
Fargate containers based on size, number, and invocation frequency and duration (ie you only pay for the minutes you use)
State Machine transitions The first 4000 transitions in a month are free, which corresponds to an invocation frequency of about once every 21 minutes assuming there are no retry transitions. Transitions after that limit are billed at a low rate.
Other notes
All Copilot-deployed resources are grouped with a number of resource tags. You can use those tags to understand billing activity, and even add your own tags via the --resource-tags flag in copilot svc deploy or copilot job deploy.
The tags we use to logically group resources are the following:
Tag Name
Value
copilot-application
name of the application this resource belongs to
copilot-environment
name of the environment this resource belongs to
copilot-service
name of the service or job this resource belongs to
The copilot-service tag is used for both jobs and services for legacy reasons.
Copilot refers to these entities as common cloud architectures [1].
I could not find an official document which outlines how these architectures are composed in detail. I guess it might be an implementation detail from the creators' perspective when you look at point one of the AWS Copilot CLI charter [2]:
Users think in terms of architecture, not of infrastructure. Developers creating a new microservice shouldn't have to specify VPCs, load balancer settings, or complex pipeline configuration. They may not know anything about other AWS services. They should be able to specify what "kind" of application it is and how it fits into their overall architecture; the infrastructure should be generated from that.
I have to agree that more sophisticated users always ask themselves how costs of a specific architecture will look like and I completely endorse the idea of having a special Copilot command such as copilot estimate costs service-xy which can be executed before creating the service.
There is some high-level documentation on the architecture types Load Balanced Web Service and Backend Service. [3]
It mentions the command copilot svc show in conjunction with the --resources flag [4]:
You can also provide an optional --resources flag to see all AWS resources associated with your service.
I think this gives you the ability to estimate costs right after bringing the services up and running.
A somehow more complicated approach which I frequently apply to understand complex constructs in the AWS CDK is to look at the source code. For example, you could open the corresponding Go file for the Load Balanced Web Service architecture: [5]. Digging into the code, you'll notice that they make it pretty clear that they are using Fargate containers instead of EC2 instances.
That is also what they tell us in the high-level service docs [4]:
You can select a Load Balanced Web Service and Copilot will provision an application load balancer, security groups, an ECS Service and run your service on Fargate.
More on Fargate: [6]
Btw, there is a really interesting comment in the issue section which outlines why they decided against supporting EC2 in the first place [7]:
What features have the team currently explicitly decided against?
EC2 comes to mind. I think we could have built a really nice experience ontop of EC2 instances - but I think there's a difference between building an "abstraction" around ECS / Fargate and building an "illusion" around ECS / EC2. What I mean by that is that if we created the illusion of a fully hands off EC2 experience, customers might be surprised that they are expected to be in charge of patching and security maintenance of those instances. This isn't something that Copilot, a CLI can really automate for people (realistically). We're still trying to figure out a good way to expose EC2 to folks - but we definitely see Fargate as the future.
I cannot seem to find any evidence that supports whether this is a true statement or not. I want to know if AWS Beanstalk deploys are faster with more expensive instance types. Any thoughts are welcomed! My assumption is that it shouldn't matter, but my deploys are incredibly slow and I want to see how this can be improved.
The underlying EC2 instance definitely matters when it comes to the speed of deployment. Elastic Beanstalk is just an API service that receives and processes API calls, and provisions the underlying infrastructure. However, all the installation and configurations are done on the instances at the end of the day. Beanstalk runs a bunch of wrapper scripts in addition to user data on the instance and this is where the compute power comes into play. Moreover, some instances spin up faster than the others.
Having said that, this is definitely not the only factor. Your source bundle size, what region you are deploying to and a few other factors also play a role.
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.
We are currently runs in-house hardware that we would like to potentially move to AWS. Our main application uses MySQL on a Linux machine (200GB Disk, 32GB RAM, 4 Cores) serving content to customers through a hardware load balancer (around 1 million unique users per month).
We also use a 500 GB CDN hosted by a third party that we would like to move to AWS potentially. What AWS services would you recommend we look at to achieve comparable functionality and would you have a rough monthly cost estimate?
The main reason we would like to move to AWS would be for cost reduction in hardware and better backup strategies.
Thanks!
1.You can host your application using two or more EC2 instances and you can use elastic load balancer to distribute load amongst these EC2 instances.
2.You could use amazon aurora MySQL(server less) which offers you pay as you go service which will allow to get maximum benefits minimising your cost.It is the very best option for your MySQL database as your users are very high and so as the load on the database.
3.For CDN you could go for aws cloudfront and s3. it offers higher availability to your application and it also has less costing.You just need to make some proper configuration and you are ready to go.
AWS is the best cloud option for you as it provides service for your each problem so can use services according to your use and make most of it.
It also provides very good costing options whcih makes your tasks easy.
Please go through aws docs and costing before you choose aws.
Comparable functionality would be to use AWS RDS to replace your MySQL database, one or more EC2 instances to run your application, and then AWS Load Balancer to distribute the load amongst those EC2 web instances. A combination of S3 and Cloudfront to use as a CDN.
Cost is going to depend on how many ec2 instances you use, and the size and options you use for RDS database(s) plus storage and bandwidth - impossible for me to estimate for you
But you can do your own estimates here: https://awstcocalculator.com/
I am about to launch an iOS app that will be communicating with my custom REST API. Right now I am running a single EC2 t2.micro instance running an Apache web server with MySQLi. Before I go ahead and launch it for the public, I want to hear what proper steps should be taken regarding the following.
Should I run two separate EC2 instances? One only for the web server and the other to handle only the database?
How should I approach setting up the database? Should I still use MySQLi or should I start using Amazon's RDS?
In relationship to number two, when the database and/or web server runs out of space, how is this issue handled so that it seamlessly adds space to allow the database/web server to continue growth? I also read something regarding auto-scale.
I will be expecting many requests per minute to my web server and want to take precaution.
The answer to these questions largely depends on the requirements of your application, your budget, and on what you decide to manage vs. what you'd prefer to allow AWS to manage. However, I'll answer these as best I can.
1) Yes. Separating the database from the web server (that is, 2 different EC2 instances) makes sense for a lot of reasons. This will allow you to tailor resources like memory, CPU, etc. to each layer of your application separately. You do not want your web and database competing for the same resources. Additionally, an issue that forces you to take down one (web or database) will not force you to also take down the other. If your database lives on one of the web servers and you need to perform maintenance, your app will effectively become offline, since down goes your database as you perform updates. Also, ideally you would protect your database server within a private subnet in your VPC. If you have the web and database on the same server, they will both be in a public subnet, since you're web will require access to an internet gateway.
2) Depends. If you want to maintain total control of the database server, than use an EC2 instance where you retain operating system control. If you want to take advantage of features like Multi-AZ for high availability or allowing AWS to manage things like updates for you, RDS can be a great option. Cost also plays a role. For things like read-replicas and Multi-AZ, you will pay more, but you are purchasing performance and high availability. Thus, depends on your requirements. You can find the features of RDS here: RDS Product Details
3) For anything running on an EC2 instance (database or web) or if you decide to use RDS, you may provision and attach additional storage volumes as necessary. The type of storage you select will depend on the performance requirements, your budget, and the kind of workload you expect your database to face. Amazon provides the storage options available to you as well as a section for adding more storage here: RDS Storage Options
If you are worried about too many requests overwhelming your EC2 t2.micro instance, consider creating an ELB load balancer and setting up an auto-scaling group which will allow you to expand your capacity as necessary while distributing traffic such that no one server gets overwhelmed.