SQS queue Staging to Prod - amazon-web-services

I have a small staging and Production setup in AWS for a workflow service where I am trying to implement SQS service. I have created a queue for staging that works fine and similarly another queue for production that seems to be working fine. The challenge is that for now we create an image of the staging server after patches and update and then use that as the base image in production autoscaling. Problem with this approach is that application still points to staging queue. Is there a way to update queue settings on the runtime or through startup configuration file etc. so it points to the right queue or a better way to implement this (without deploying a full ci/cd pipline etc)? I don't have dev background so any help will be appreciated.

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Node is not able to connect to Hub, keep sending registration event

Objective: UI test execution takes quite a time and we have a lot of UI test cases, currently we have a grid setup on AWS EC2 but scaling and descaling of resources manualy is time-consuming, so we decided to explore AWS ECS Fargate where we can scale based on CPU and Memory utilization.
Motivation blog: https://aws.amazon.com/blogs/opensource/run-selenium-tests-at-scale-using-aws-fargate/
Problem Statement: Node is initiating registration requests but it is not able to register itself to the hub.
Findings till now: I found a repo on git which is doing what we are trying to achieve except for one thing, that is in version 3.141.59 and we want the version 4.4.0-20220831
What I can achieve: So using this repo I changed the version of Hub and Node to 4.4.0-20220831 and also changed environment variables according to the specific version requirements, on the execution of cloudFormation template Hub is up and running but there was no node connected when I checked the log of hub and node, I found hub service was configured and running as well as the node service was sending registration requests for N times.
This is my first question here so I am not able to show images in question itself, sorry for inconveniance.
HUB Screenshots
Hub environment
Hub service discovery
Hub logs
Node Screenshots
Node environment
Node service discovery
Node logs
Before changing anything everyting is working as expected on V3 but we need V4.
Thank you for gving your valuable time, looking forward for you response.
Thank you once again.
The problem is not with any of these resources, when I allowed ports 4442 and 4443 in my security group it worked.
Thank you everyone for your time and support.

Which is the best way on AWS to set up a CI/CD of a Django app from GitHub?

I have a Django Web Application which is not too large and uses the default database that comes with Django. It doesn't have a large volume of requests either. Just may not be more than 100 requests per second.
I wanted to figure out a method of continuous deployment on AWS from my source code residing in GitHub. I don't want to use EBCLI to deploy to Elastic Beanstalk coz it needs commands in the command line and is not automated deployment. I had tried setting up workflows for my app in GitHub Actions and had set up a web server environment in EB too. But it ddn't seem to work. Also, I couldn't figure out the final url to see my app from that EB environment. I am working on a Windows machine.
Please suggest the least expensive way of doing this or share any videos/ articles you may hae which will get me to my app being finally visible on the browser after deployment.
You will use AWS CodePipeline, a service that builds, tests, and deploys your code every time there is a code change, based on the release process models you define. Use CodePipeline to orchestrate each step in your release process. As part of your setup, you will plug other AWS services into CodePipeline to complete your software delivery pipeline.
https://docs.aws.amazon.com/whitepapers/latest/cicd_for_5g_networks_on_aws/cicd-on-aws.html

AWS ECS run latest task definition

I am trying to have run the lastest task definition image built from GitHub deployment (CD). Seems like on AWS it creates a task definition for example "task-api:1", "task-api:2", on was my cluster is still running task-api: 1 even though there is the latest task as a new image has been built. So far I have to manually stop the old one and start a new one . How can I have it automated?
You must wrap your tasks in a service and use rolling updates for automated deployments.
When the rolling update (ECS) deployment type is used for your service, when a new service deployment is started the Amazon ECS service scheduler replaces the currently running tasks with new tasks.
Read: https://docs.aws.amazon.com/AmazonECS/latest/developerguide/deployment-type-ecs.html
This is DevOps, so you need a CI/CD pipeline that will do the rolling updates for you. Look at CodeBuild, CodeDeploy and CodePipeline (and CodeCommit if you integrate your code repository in AWS with your CI/CD)
Read: https://docs.aws.amazon.com/codepipeline/latest/userguide/tutorials-ecs-ecr-codedeploy.html
This is a complex topic, but it pays off in the end.
Judging from what you have said in the comments:
I created my task via the AWS console, I am running just the task definition on its own without service plus service with task definition launched via the EC2 not target both of them, so in the task definition JSON file on my Github both repositories they are tied to a revision of a task (could that be a problem?).
It's difficult to understand exactly how you have this set up and it'd probably be a good idea for you to go back and understand the services you are using a little better using the guide you are following or AWS documentation. Pushing a new task definition does not automatically update services to use the new definition.
That said, my guess is that you need to update the service in ECS to use the latest task definition. You can do that in many ways:
Through the console (https://docs.aws.amazon.com/AmazonECS/latest/developerguide/update-service-console-v2.html).
Through the CLI (https://docs.aws.amazon.com/cli/latest/reference/ecs/update-service.html).
Through the IaC like the CDK (https://docs.aws.amazon.com/cdk/api/latest/docs/aws-ecs-readme.html).
This can be automated but you would need to set up a process to automate it.
I would recommend reading some guides on how you could automate deployment and updates using the CDK. Amazon provide a good guide to get you started https://docs.aws.amazon.com/cdk/latest/guide/ecs_example.html.

how to deploy code on multiple instances Amazon EC2 Autocaling group?

So we are launching an ecommerce store built on magento. We are looking to deploy it on Amazon EC2 instance using RDS as database service and using amazon auto-scaling and elastic load balancer to scale the application when needed.
What I don't understand is this:
I have installed and configured my production magento enviorment on an EC2 instance (database is in RDS). This much is working fine. But now when I want to dynamically scale the number of instances
how will I deploy the code on the dynamically generated instances each time?
Will aws copy the whole instance assign it a new ip and spawn it as a
new instance or will I have to write some code to automate this
process?
Plus will it not be an overhead to pull code from git and deploy every time a new instance is spawned?
A detailed explanation or direction towards some resources on the topic will be greatly appreciated.
You do this in the AutoScalingGroup Launch Configuration. There is a UserData section in the LaunchConfiguration in CloudFormation where you would write a script that is ran when ever the ASG scales up and deploys a new instance.
https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-as-launchconfig.html#cfn-as-launchconfig-userdata
This is the same as the UserData section in an EC2 Instance. You can use LifeCycle hooks that will tell the ASG not to put the EC2 instance into load until everything you want to have configured it set up.
https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-as-lifecyclehook.html
I linked all CloudFormation pages, but you may be using some other CI/CD tool for deploying your infrastructure, but hopefully that gets you started.
To start, do check AWS CloudFormation. You will be creating templates to design how the infrastructure of your application works ~ infrastructure as code. With these templates in place, you can rollout an update to your infrastructure by pushing changes to your templates and/or to your application code.
In my current project, we have a github repository dedicated for these infrastructure templates and a separate repository for our application code. Create a pipeline for creating AWS resources that would rollout an updated to AWS every time you push to the repository on a specific branch.
Create an infrastructure pipeline
have your first stage of the pipeline to trigger build whenever there's code changes to your infrastructure templates. See AWS CodePipeline and also see AWS CodeBuild. These aren't the only AWS resources you'll be needing but those are probably the main ones, of course aside from this being done in cloudformation template as mentioned earlier.
how will I deploy the code on the dynamically generated instances each time?
Check how containers work, it would be better and will greatly supplement on your learning on how launching new version of application work. To begin, see docker, but feel free to check any resources at your disposal
Continuation with my current project: We do have a separate pipeline dedicated for our application, but will also get triggered after our infrastructure pipeline update. Our application pipeline is designed to build a new version of our application via AWS Codebuild, this will create an image that will become a container ~ from the docker documentation.
we have two triggers or two sources that will trigger an update rollout to our application pipeline, one is when there's changes to infrastructure pipeline and it successfully built and second when there's code changes on our github repository connected via AWS CodeBuild.
Check AWS AutoScaling , this areas covers the dynamic launching of new instances, shutting down instances when needed, replacing unhealthy instances when needed. See also AWS CloudWatch, you can design criteria with it to trigger scaling down/up and/or in/out.
Will aws copy the whole instance assign it a new ip and spawn it as a new instance or will I have to write some code to automate this process?
See AWS ElasticLoadBalancing and also check out more on AWS AutoScaling. On the automation process, if ever you'll push through with CloudFormation, instance and/or containers(depending on your design) will be managed gracefully.
Plus will it not be an overhead to pull code from git and deploy every time a new instance is spawned?
As mentioned, earlier having a pipeline for rolling out new versions of your application via CodeBuild, this will create an image with the new code changes and when everything is ready, it will be deployed ~ becomes a container. The old EC2 instance or the old container( depending on how you want your application be deployed) will be gracefully shut down after a new version of your application is up and running. This will give you zero downtime.

Mesos, Marathon, the cloud and 10 data centers - How to talk to each other?

I've been looking into Mesos, Marathon and Chronos combo to host a large number of websites. In my head I should be able to type a few commands into my laptop, and wait about 30 minutes for the thing to build and deploy.
My only issue, is that my resources are scattered across multiple data centers, numerous cloud accounts, and about 6 on premises places. I see no reason why I can't control them all from my laptop -- (I have serious power and control issues when it comes to my hardware!)
I'm thinking that my best approach is to build the brains in the cloud, (zoo keeper and at least one master), and then add on the separate data centers, but I am yet to see any examples of a distributed cluster, where not all the nodes can talk to each other.
Can anyone recommend a way of doing this?
I've got a setup like this, that i'd like to recommend:
Source code, deployment scripts and dockerfiles in GIT
Each webservice has its own directory and comes together with a dockerfile to containerize it
A build script (shell script running docker builds) builds all the docker containers, of which all images are pushed to a docker image repository
A ansible deploy deploys all the containers remotely to a set of VPSes. (You use your own deployment procedure, that fits mesos/marathon)
As part of the process, a activeMQ broker is deployed to the cloud (yep, in a container). While deploying, it supplies each node with the URL of the broker they need to connect to. In your setup you could instead use ZooKeeper or etcd for example.
I am also using jenkins to do automatic rebuilds and to run deploys whenever there has been GIT commits, but they can also be done manually.
Rebuilds are lightning fast, and deploys dont take much time either. I can replicate everything I have in my repository endlessly and have zero configuration.
To be able to do a new deploy, all I need is a set of VPSs with docker daemons, and some datastores for persistence. Im not sure if this is something that you can replace with mesos, but ansible will definitely be able to install a mesos cloud for you onto your hardware.
All logging is being done with logstash, to a central logging server.
i have setup a 3 master, 5 slave, 1 gateway mesos/marathon/docker setup and documented here
https://github.com/debianmaster/Notes/wiki/Mesos-marathon-Docker-cluster-setup-on-RHEL-7-with-three-master
this may help you in understanding the load balancing / scaling across different machines in your data center
1) masters can also be used as slaves
2) mesos haproxy bridge script can be used for service discovery of the newly created services in the cluster
3) gateway haproxy is updated every min with new services that are created
This documentation has
1) master/slave setup
2) setting up haproxy that automatically reloads
3) setting up dockers
4) example service program
You should use Terraform to orchestrate your infrastructure as code.
Terraform has a lot of providers that allows you to manage different resources accross multiples clouds services and/or bare-metal resources such as vSphere.
You can start with the Getting Started Guide.