amazon-ecs | Amazon Product Advertising Ruby API | AWS library

It's been weeks that I am trying to make CodeDeploy / CodePipeline works for our solution. To make some sort of CI/CD, and make deployment faster, safer...etc

As I keep diving into it, I feel like either I am not doing it the right way at all, or either it is not suitable in our case.

What all our AWS infra is :

• We have an ECS Cluster, that contain for now one service (under EC2), associated with one or multiple tasks, a reverse proxy and an API. So the reverse proxy is internally listening to port 80, and when reached, proxy pass internally to the API on port 5000.

• We have an application load balancer associated with this service, that will be publicly reachable. It currently has 2 listeners, http and https. Both listener redirect to the same target group, that only have instance(s) where our reverse proxy is. Note that the instance port to redirect to is random (check this link)

• We have an auto scaling group, that is scaling numbers of instance depending on the number of call to the application load balancer.

What we may have in the futur :

• Other tasks will be in the same instance as our API. For example, we may create another API that is in the same cluster as before, on another port, with another reverse proxy, and yet another load-balancer. We may have some Batch running, and other stuffs.

What's the problem :

Well for now, deploying "manually" (that is, telling the service to make a new deployment on ECS) doesn't work. CodeDeploy is stuck at creating replacement tasks, and when i look at the log of the service, there is the following error

service xxxx-xxxx was unable to place a task because no container instance met all of its requirements. The closest matching container-instance yyyy is already using a port required by your task.

Which i don't really understand, since port assignation is random, but maybe CodeDeploy operate before that, and just understand that assignated port is 0, and that it's the same as the previous task definition ?

I don't really know how i can resolve this, and i even doubt that CodeDeploy is usable in our case...

-- Edit 02/18/2021 --

So, i know why it is not working now. Like i said, the port that my host is listening for the reverse proxy is random. But there is still the port that my API is listening on that is not random

But now, even if i tell the API port to be random like the reverse proxy one, how would my reverse proxy know on what port the API will be reachable ? I tried to link containers, but it seems that it doesn't work in the configuration file (i use nginx as reverse proxy).

--

Not specifying hostPort seems to assign a "random" port on the host

But still, since NGINX and the API are two diferent containers, i would need my first NGINX container to call my first API container which is API:32798. I think i'm missing something

I need to deploy an application stack to ECS. To do this, I use the new Docker Compose ECS integration (see e.g. here).

In few words, everything boils up to using the correct docker context and launching the command docker compose up. This is of great help and very quick.

I would like to automate the deploy process in a GitLab pipeline.

What (Docker) image should I use in my pipeline to be able to run the new docker compose command?

Thanks in advance.

I have a internet-facing load balancer in a public subnet and have a privated hosted zone with a cname record for the load balancer as described here. I try to request the record from a lambda in a private subnet which times out. I thought it is VPC internal and should resolve. Is that possible at all?

I'm trying to build docker images for a Spring Boot application (2.3.6.RELEASE) using the spring-boot-maven-plugin build-image goal (buildpacks), but it's downloading the internet everytime! Is there a way to mount the .m2 directory to the buildpack, so it can use dependencies from the cache?

My spring boot app deployed in Elastic Beanstalks docker is unable to connect to external RDS. It always stuck at "com.zaxxer.hikari.HikariDataSource - HikariPool-1 - Starting..." during app startup.

Dockerfile (I added the db connection details in ENTRYPOINT for troubleshooting purpose)

I'm trying to run my dotnet core project and mongodb as container services with docker-compose. Both services have a clean start with no errors. When I call an endpoint that interacts with mongo I get a timeout error. Since I'm using docker-compose I expect that I can reference the mongo service by the compose service name in the connection string.

mongo:27017/api?authSource=api with username api and password password123 as seen in the docker-compose file below. Instead I get this error:

I can't access a running docker image from outside of the EC2 instance.

• I created a cluster in ECS, a service with a related task definition and an Application Load Balancer.
• When the task gets executed I can see the logs from the Docker image in the task:
• I also see the related EC2 instance running. When I ssh into the instance I can see the docker image running, as expected:

We want to build an ECS cluster with the following characteristics:

1. It must run inside a VPC, then, we need the awsvpc mode
2. It must use GPU instances, so we can't use Fargate
3. It must provision dynamically the instances, therefore, we need a capacity provider
4. It will run tasks (batch jobs) that are going to be triggered directly through the AWS ECS API. For this reason, we don't need a service, only a task definition.
5. These tasks must have access to S3 (internet), so according to AWS documentation the instances must be placed inside a private subnet (a reference to docs).

We've already read this post in stackoverflow where it says that we need to set up a private subnet with a route table that points to a NAT Gateway configured in a public subnet, and this public subnet should point to an internet gateway. We already have this configuration. We also have an S3 vpc endpoint configured in the route table.

Bellow, you can see some relevant configurations of the cluster in terraform (for the shake of simplicity I only put the relevant parts):

I am building my cluster on ECS while using EC2 instances. I am curious about specifying CPU reservation on my Task definitions. How does AWS manage my tasks inside of EC2 instances when i leave CPU reservation empty or write 0?

I have read this article: https://aws.amazon.com/blogs/containers/how-amazon-ecs-manages-cpu-and-memory-resources/

And here it says:

when you don’t specify any CPU units for a container, ECS intrinsically enforces two Linux CPU shares for the cgroup (which is the minimum allowed).

I am not really sure what this means and is it different for Tasks, because this is specifically stated for containers?