autoscaling | AutoScaling with Docker | AWS library

You can't ignore some files from a pull request selectively. But there are 2 simple workarounds for this :

First -
Create a new branch from ‘develop’

Replace the non-required files from 'main'

Create pull request from this new branch

Second -
Create a new branch from 'main'

Put changes of required files from 'develop'

Create pull request from this new branch

Any of these methods will work. Which will be easier depends on how many files are to be included / excluded.

Example :
Considering main as target and dev as source

Yeah, JMESPATH can be weird sometimes. Try:

When autoscaling occurs nothing will automatically update the state to reflect that event. If you do not update the terraform code to reflect the new value, in the next terraform plan you will see the state change show up. Which could indeed cause issues.

If you don't need to track the desired capacity outside of the creation of the autoscaling group I would recommend you ignore the desired_capacity argument by using a lifecycle block to ignore changes to the argument.

containerConcurrency is an argument to the Knative infrastructure indicating how many requests your container can handle at once.

In AWS Lambda and some other Function-as-a-Service offerings, each instance will only ever process a single request. This can be simpler to manage, but some languages (Java and Golang, for example) easily support multiple requests concurrently using threaded request models. Platforms like Cloud Foundry and App Engine support this larger concurrency, but not the "function" model of code transformation.

Knative is somewhere between these two; since you can bring your own container, you can build an application container which is single-threaded like Lambda expects and set containerConcurrency to 1, or you can create a multi-threaded container and set containerConcurrency higher.

I can see 1 new task added to my service and then I get this error message in the even.

This is because t2.small has 1000 CPU units. So your two tasks take all of them, and there is no other instances to place your extra task on.

I also notice that no new EC2 instances were added.

You set min_capacity=1 so you have only instance. The _scaling_steps are for the tasks only, not for your instances in autoscaling group. If you want more instance you have to set min_capacity=2 or whatever value you want.

I guess you thought that QueueProcessingEc2Service scales both instances and tasks. Sadly this is not the case.

Your Ingress should have a serviceName which in your case is "gateway-443" and "gateway-80" but the actual name specified in the Service in metadata.name is "gateway-8243".

(If this is on purpose, please post the YAML of the other resources so I can take a look at the whole setup.)

Also please take a look at this page that has lots of good examples on how to achieve what you are looking to do.

From the terraform manual for aws_autoscaling_group:

wait_for_capacity_timeout (Default: "10m") A maximum duration that Terraform should wait for ASG instances to be healthy before timing out. (See also Waiting for Capacity below.) Setting this to "0" causes Terraform to skip all Capacity Waiting behavior.

https://registry.terraform.io/providers/hashicorp/aws/latest/docs/resources/autoscaling_group

I think its unhealthy on the basis that it cant communicate yet, judging from the ec2 error. 0 seconds is too short a time for an ec2 instance to go from initialising to inService, the check of which will take place after the "aws_autoscaling_group" resource is fired in terraform. If I were a web user (or health check) hitting the ec2 instance thats currently initialising, I'd get a 500, not a 500-but-ec2-will-be-span-up-soon-try-again-in-a-minute. In resource "aws_autoscaling_group" "autoscaling", try giving it a value:

You must inform Boto3 in which region you want to use the sqs resource.

Set region_name in queue_service.py for sqs resource.

HPA can be used with the following resources: ReplicationController, Deployment, ReplicaSet or StatefulSet. However HPA doesn't support scaling to 0.

There are some serverless frameworks that support scalability to zero in kubernetes such as Knative and Keda.

Your use case sounds much simpler though, as you're looking to scale to zero based on a manual action. You can achieve this by setting the number of replicas of your deployment to 0.