Amazon ECS provides really good service for scheduled tasks : ECS Scheduled tasks that works pretty well.
However it's important in this always keep one ECS instance in ECS cluster.
What is the best way:
Launch/scale in ECS instance in for periodical job (just before task execution);
Run ECS tasks on newly created instance;
Terminate/scale out instance after completion.
One possible workaround is to write lambda that will do smth. like that (launch ec2) but it looks as too much pain.
Finally I found out an easy solution for that problem. Everything was quite simple:
Go to Autoscaling groups (This you can find on EC2 dashboard-> Autoscaling section);
Create scheduled action (In that case necessary frequency can be specified for your container instance);
Save your configuration. Instance will be added in the specified time.
In my case I also need to scale down this instance in 1 hour period.
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I have an ECS cluster running service and task that sits on an EC2 machine. The task is big and takes up the whole machine its running on. Is there any way to set up ECS & EC2 to scale temporally on deployments to create a new instance, run the new task then stop the old pre-deployment task?
So far tried to play with the auto-scaling on both EC2 & ECS separately but it seems to me that the conditions for scaling are down to CPU or memory utilization, however as my task takes up the whole instance there are no alarms that could be triggered on deployment as there's just no suitable instance to start the task on.
Right now I have the services running as DAEMON, so it's one per instance, and autoscaling seems to be disabled for it. During deployments, it drains the old task before starting the new one creating downtime. To set the service type to REPLICA, scaling can be enabled, however, it's based on instance resource utilization and I can't seem to figure out how I would create a new instance on deployments.
I am missing something or interpreting how these auto-scalers work wrong, as I can't seem to see a nice way to deploy without affecting the current task sort of having just an unused instance sitting there running in the background all the time(wasting money).
I'm trying to deploy a docker image to AWS's Elastic Container Service, and then run this as an EC2 instance (via Fargate). However, I believe I need to specify a minimum of 1 running instance in the TaskDefinition.
What I want to achieve though is basically to be able to spin up this container on demand, as it'll be used infrequently and then shut it down after. So the plan was to start/stop this via a lambda and redirect to the public IP (so within web request timeouts).
I've seen examples of how to do this using EC2, but none actually using Fargate. I don't believe I can define an EC2 task, based off of a docker image (if I can, this might be my solution?).
Does anyone know if it's possible to achieve this? If so could you provide some guidance on how I might approach it, and if you've any CloudFormation examples that would be brilliant.
There is almost not difference in defining ECS task for EC2 or Fargate. Only one difference is networking. With Fargate you have to use awsvpc networking.
You can use lambda. But there is better idea to achieve your use case.
To spin exactly one task, you have to set
Minimum instances: 0
Desired count: 1
Max instances: 1 or more
Autoscaling solution
However better idea than Lambda is to use Service autoscaling. The ECS Servce autoscaling requires metrics in cloudwatch. So you can push metric to cloudwatch to start task. Then compute your task and on the end of your computation put metrics to stop task.
Manual solution
Another solution can be switching desired count to 1 when you want to start task and to 0 when you want to stop task
References: https://docs.aws.amazon.com/AmazonECS/latest/developerguide/service-auto-scaling.html
I am using AWS ECS in combination with EC2 instances.
Right now I am setting up Auto Scaling. How can I make sure that when, an EC2 instance gets terminated, all ECS tasks get migrated before the machine gets terminated?
Right now it is not automatically possible to achieve this. The best approach would be to have atleast 2 tasks running of each service, spread on different instances via a placement constraint.
Manually (or scripted) it is possible:
If you want to replace an instance attached to an ECS cluster, you can simply drain the instance. This will do the following
Start a new task of each running service on another instance in the cluster
Wait until the recently started task is 'steady'
shutdown the old task
To drain an instance using the AWS CLI, do the following:
Open the Amazon ECS console at https://console.aws.amazon.com/ecs/.
In the navigation pane, choose Clusters and select the cluster.
Choose ECS Instances and select the check box for the container
instances.
Choose Actions, Drain instances.
After the instances are processed, choose Done.
This can also be done via the command line.
To do it automatically, you will need to add a lifecycle hook on termination.
Call the AWS CLI from the termination lifecycle hook to drain the instance, wait a fixed amount of time and then continue terminating the instance.
I've an ECS cluster with running one task for my backend instance. I would like to be able to stop/start the EC2 instance whenever I want. Is it possible?? I was trying to stop instance directly but it terminates after few second when stopped and after that new instance is created automatically. I tried to change the Auto Scale Group to match desired=min=0 capacity but when I do that the instance gets auto terminated. I just want to turn off the Ec2 instance when its not needed to be used but at the same time I want data to persist betweet turning on and off. I am fighting with this for a few days now and wasn't able to achieve my goals.
Also how to link EBS volume with VOLUME /root/.local/share/XYZ from docker file image to persist the data from the XYZ folder
I would suggest you to do modifications in autoscaling group, when you want to turn off instance put 0 in auto scaling and when you want to turn on change value in autoscaling,
... you can do that with aws cli , and you can shcdule the period also by putting aws cli command in cron job
I would suggest using EFS. Here is an article from AWS on how to persist data from ECS containers using EFS.
Using Amazon EFS to Persist Data from Amazon ECS Containers
Start/Stop instances and auto-scale don't really fit together.
Auto-scale is specifically designed to solve scalein/scaleout.
One way to address this could be using customized termination policy (but I never tried this in ECS setup).
One note though, if your customized termination policy never terminates the instances and you continue adding instances to keep always, you might get good amount EC2 bill.
I am using an ECS cluster for Jenkins agents/slaves with the Jenkins ECS plugin.
The plugin places a ECS Task when a job requests a build-node. Now I want to scale the EC2 instances in a Autoscaling Group associated with the ECS Cluster according to the demand.
The jenkins is often idle. In this case, I do not want there to be any instances in the autoscaling group.
If a node (and therefore an ECS task) is requested and cannot be placed, I want to add an EC2 instance to the autoscaling group.
If an instance is idle and shortly before an billing hour, I want that instance to be removed.
The 3. point can be accomplished by a cronjob on the EC2 instances that regularly checks if the conditions are met and removes the EC2 instance.
But how can I accomplish the 2. point? I am unable to create a cloudwatch alarm that triggers, if a task cannot be placed.
How can I accomplish this?
A rather hacky way to achieve this: You could use a Lambda function to detect when a service has runningCount + pendingCount < desiredCount for more than X seconds. (I have not tested this yet.)
Similar solutions are proposed here.
There does not seem to be a proper solution to scale only when tasks cannot be placed. Maybe AWS wants us to over-provision our clusters, which might be good practice for high availability, but not always the best or cheapest solution.
When a task cannot be placed it means that placing that task in your ECS cluster would exceed either your MemoryReservation or CPUReservation. You could set up Cloudwatch alarms for one or both of these ECS metrics and an auto scaling policy that will add and remove EC2 instances in your ECS cluster.
This, in combination with an auto scaling policy that scales your ECS services on the ecs:service:DesiredCount dimension should be enough to get you adding the underlying EC2 instances your ECS cluster requires.
For example your ScalingPolicy for an ECS Service might be "when we're using 70% of our allotted memory for this service, add 2 to the DesiredCount". After adding 1 service task, your ECS Cluster MemoryReservation metric might bump up past an "80" threshold, at which point a Cloudwatch alarm would trigger for some threshold on ECS MemoryReservation, with an auto scaling policy adding another EC2 node, on which the 2nd task could now be placed.
For those arriving after January 2020, the way to handle it now is probably Cluster Auto Scaling as documented here: "Amazon ECS cluster auto scaling" with more info here: "Deep Dive on Amazon ECS Cluster Auto Scaling)".
Essentially, ECS now handles most the heavy lifting. Not all, or I wouldn't be here looking for an answer ;)
For point 2, one way to solve this would be to autoscale when there is not enough cpu units for placing a new jenkins slave.
You should use the cpu reservation metric on the cluster to scale.
http://docs.aws.amazon.com/AmazonECS/latest/developerguide/cloudwatch-metrics.html#cluster_reservation