I am a beginner in cloud computing and have read some documents about cloud computing in Amazon. I have a question about Xen and the art of virtualization implemented in Amazon web service. As we know cloud computing offers elasticity and scalablity for deploying applications. When we deploy a cloud app to Amazon, by the time the number of users of our app has been increased and I think Amazon will automatically generate a new virtual server to handle user request. At the first time, the cloud app runs on one virtual server and now it runs on two virtual servers.
Does anyone know how an application can run on two virtual servers on Amazon? How it synchronizes data, use of CPU resources,...?
Is there any document from Amazon point out this problem and virtualization implemention?
Thank you
When you create an instance on the Amazon EC2, they create a new virtual server(called as instance) for you to use it. They do not scale the number of instances based on the user requests. It is upto the user to create the instances for use.
The following link has an exhaustive explanation about how the distributed and scalable applications work
Related
Now I am working with our company product developed with spring boot , angular and PostgreSQL technologies where front end angular is communicating with 138 back end ReST API end points. And these 138 end points are from 35 different spring boot project. And all these end points need to separately deploy for 5 different tenant. Actually end point working is same.But databases are different for different tenant. And we decided to go with AWS cloud. And we are looking for cost effective deployment method from AWS.
Our Current Development/Test strategy - Current we are developing application(final stage of development) and testing our application using our On-premise server. Here we are using 5 ubuntu machines. And we created kubernetes cluster with 2 master nodes and 3 worker nodes.And from our SVN repository and Jenkins server we implemented CI/CD pipeline deployment to this 5 machines.
Proposed Cloud Solution - Now we are thinking with to use either EKS deployment method or any of CodeDeploy/CodePipeline method to implement this big project.
So by considering cost and control over infrastructure management which solution is better for my product? Now I am not that much experienced as solution architect and still in cloud learning curve. So can any one suggest/guide me to think properly to achieve my goal please?
Company consideration
Control over infrastructure
Cost effective
Easy management of aws services for multi-tenant deployment
Data security ( Installing database on ec2/ RDS)
Management of load balances
Control over infrastructure
it would be better to manage it on Github, Gitlab, and or AWS code build, or cloud build.
indeed AWS code build, and repo is great tools but again consider the limitation of extra users it allows only 5 users if your team is very big you might have to pay to compare to managing projects at the Github & GitLab level.
Cost effective
EKS would be a good option compared to ECS or others as it has limitations of we can not run the Daemon set or Privilege PODs.
If you are looking for running everything On POD and auto-scalable with little less flexibility and don't want to manage much ECS also a good idea, but again you have to derive the capacity and compare both pricing ECS vs EKS.
Note : EKS will also charge the per hour charges $0.10 for each cluster + worker nodes. it's not just worker nodes like in on-prem we run.
Data security ( Installing database on ec2/ RDS)
RDS would be better as it's managed service compare to managing the EC2 and database performance and encryption etc.
it would be better to use RDS and EKS so the K8s service can connect to RDS easily on a private network.
RDS would be a cost-effective option considering the management of DB over EC2.
Management of load balances
NLB or ALB will take care of that you can use any of them as per the requirement with EKS.
Cloud front could be also a great option with cloud storage to serve static assets, which will reduce calls, improve performance and be cost-effective also.
I have a webapp and database that aren't hosted on any cloud service, just on a regular hosting platform.
I need to build an API to read and write to that database and I want to use cloud functions to do so. Is it possible to connect to a remote databases from cloud functions (such as AWS Lambdas or Google cloud functions) even when they're not hosted that cloud service?
If so, can there be problems with doing so?
Cloud Functions are just Node.js code that runs in a managed environment. This means your code can do almost anything that Node.js scripts can do, as long as you stay within the restrictions of that environment.
I've seen people connect to many other database services, both within Google Cloud Platform and outside of it. The main restriction to be aware of there, is that you'll need to be on a paid plan in order to be able to call APIs that are not running on Google Cloud Platform.
Yes it's possible.
If so, can there be problems with doing so?
There could high latency if the database is in a different network. Also, long-lived database connection pools don't really work well in these environments due to the nature of the functions being created and destroyed constantly. Also, if your function reaches a high level of concurrency you may exhaust the number of available connections on your database server.
You could use FaaS the same as your web service hosted on any web server or cloud server.
You have to be careful with the duration of your call to DB because FasS functions are limited in time (15 min for AWS Lambda and 9 min on Google) and configure a firewall properly on your DB server.
A container of your lambda function could be reused, you could use some tricks with it - Best Practices for AWS Lambda Container Reuse
But you can't be sure that nothing changed during the work of your service.
You could read some good advice about it there - https://stackoverflow.com/a/37524237/182344
PS: Azure functions have always on setting, but I am not sure how pooling will work in this case.
Yes you can access on premise resources from Serverless products.
Please check this detailed tutorial where you can find 3 methods to achive your goal link:
Connecting using a VPN
Connecting using a Parner interconnect
Connecting using Interconnect solution
Sorry I'm new to web server. I want to deploy a cloud server for user data:
User can login using web, with verification code sent to user's phone.
User can manipulate his data (add/modify/remove) when login.
Android/iPhone client can manipulate user data when login.
Server should have a database for storage, SQLLite or others.
It would be good to use Amazon/Ali-cloud cloud service, provided it can speed up my deployment. I'm not sure if I need run into blobs such as H5, PHP/JSP, node.js or others. Can you provide a guide for me, web link or book?
And, what's the most popular programming interface between Android/IOS app and cloud server? http post/get or other wrapper ?
Surely you can speed up your deployment using Amazon Web Services. This is my recommendation:
For Webserver,
Amazon EC2: Launch an instance where you can install Apache/Nginx
here. You will need a RDS instance running parallel with your server
which will lower your need on server CPU/Mem, but will cost also.
For Database, you can have many approach ways here:
Amazon RDS: Launch an instance where you host your Database
(mysql/...). This one will provide you with Database Name, Hostname,
Users, ... which you can use to connect with your webserver in EC2.
Your Android/IOS application can use RDS information for the database
connection.
Amazon DynamoDB: Fast, Flexible for NoSQL (wonder if you want to use
traditional database or NoSQL?): https://aws.amazon.com/amplify/
For Mobile/Website access control,
AWS Cognito: Great for user-accounts, designed for real-time data
model: https://aws.amazon.com/cognito/?nc1=f_ls
For serverless if you want to GET/PUT API on your webserver for
easier,
AWS Lambda: https://aws.amazon.com/lambda/?nc1=f_ls
Taking into account that you are just starting with your application, I would suggest going with serverless architecture with AWS Lambda running your business logic.
Key benefits:
No server management = spend time on building your application vs on maintaining infrastructure
Flexible scaling = scale based on what you really need
Pay for value = don't pay for resources that you don't need
Automated high availability = serverless provides built-in availability and fault tolerance
To learn more on serverless, you may want to check Building Serverless Web Applications - 2017 AWS Online Tech Talks.
Now when it comes to going deep, I would suggest checking online trainings available from acloud.guru, cloud academy, udemy or linuxacademy for serverless and also for the development language you want to use (Node.js is often used for such scenarios).
Let's say a company has an application with a database hosted on AWS and also has a read replica on AWS. Then that same company wants to build out a data analytics infrastructure in Google Cloud -- to take advantage of data analysis and ML services in Google Cloud.
Is it necessary to create an additional read replica within the Google Cloud context? If not, is there an alternative strategy that is frequently used in this context to bridge the two cloud services?
While services like Amazon Relational Database Service (RDS) provides read-replica capabilities, it is only between managed database instances on AWS.
If you are replicating a database between providers, then you are probably running the database yourself on virtual machines rather than using a managed service. This means the databases appear just like any resource on the Internet, so you can connect them exactly the way you would connect two resources across the internet. However, you would be responsible for managing, monitoring, deploying, etc. This takes away from much of the benefit of using cloud services.
Replicating between storage services like Amazon S3 would be easier since it is just raw data rather than a running database. Also, Big Data is normally stored in raw format rather than being loaded into a database.
If the existing infrastructure is on a cloud provider, then try to perform the remaining activities on the same cloud provider.
I'm developing a prototype IoT application which does the following
Receive/Store data from sensors.
Web application with a web-based IDE for users to deploy simple JavaScript/Python scripts which gets executed in Docker Containers.
Data from the sensors gets streamed to these containers.
User programs can use this data to do analytics, monitoring etc.
The logs of these programs are outputted to the user on the webapp
Current Architecture and Services
Using one AWS EC2 instance. I chose EC2 because I was trying to figure out the architecture.
Stack is Node.js, RabbitMQ, Express, MySQl, MongoDB and Docker
I'm not interested in using AWS IoT services like AWS IoT and Greengrass
I've ruled out Heroku since I'm using other AWS services.
Questions and Concerns
My goal is prototype development for a Beta release to a set of 50 users
(hopefully someone else will help/work on a production release)
As far as possible, I don't want to spend a lot of time migrating between services since developing the product is key. Should I stick with EC2 or move to Beanstalk?
If I stick with EC2, what is the best way to handle small-medium traffic? Use one large EC2 machine or many small micro instances?
What is a good way to manage containers? Is it worth it use swarm and do container management? What if I have to use multiple instances?
I also have small scripts which have status of information of sensors which are needed by web app and other services. If I move to multiple instances, how can I make these scripts available to multiple machines?
The above question also holds good for servers, message buses, databases etc.
My goal is certainly not production release. I want to complete the product, show I have users who are interested and of course, show that the product works!
Any help in this regard will be really appreciated!
If you want to manage docker containers with least hassle in AWS, you can use Amazon ECS service to deploy your containers or else go with Beanstalk. Also you don't need to use Swarm in AWS, ECS will work for you.
Its always better to scale out rather scale up, using small to medium size EC2 instances. However the challenge you will face here is managing and scaling underlying EC2's as well as your docker containers. This leads you to use Large EC2 instances to keep EC2 scaling aside and focus on docker scaling(Which will add additional costs for you)
Another alternative you can use for the Web Application part is to use, AWS Lambda and API Gateway stack with Serverless Framework, which needs least operational overhead and comes with DevOps tools.
You may keep your web app on Heroku and run your IoT server in AWS EC2 or AWS Lambda. Heroku is on AWS itself, so this split setup will not affect performance. You may heal that inconvenience of "sitting on two chairs" by writing a Terraform script which provisions both EC2 instance and Heroku app and ties them together.
Alternatively, you can use Dockhero add-on to run your IoT server in a Docker container alongside your Heroku app.
ps: I'm a Dockhero maintainer