I have a cluster running two services, a web app, and a message queue handler. The app has autoscaling configured, but the queue handler does not. There's also a couple of scheduled tasks that run as well.
If I run a task manually using the cli (aws ecs run-task), the task works properly at first, then then after about 5 minutes loses the ability to make outbound connections.
From looking at the scaling logs, it doesn't look like autoscaling would be causing this issue.
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I have 2 questions:
first, what does it mean that the Kubernetes executor is fault tolerance, in other words, what happens if one worker nodes gets down?
Second question, is it possible that the whole Airflow server gets down? if yes, is there a backup that runs automatically to continue the work?
Note: I have started learning airflow recently.
Thanks in advance
This is a theoretical question that faced me while learning apache airflow, I have read the documentation
but it did not mention how fault tolerance is handled
what does it mean that the Kubernetes executor is fault tolerance?
Airflow scheduler use a Kubernetes API watcher to watch the state of the workers (tasks) on each change in order to discover failed pods. When a worker pod gets down, the scheduler detect this failure and change the state of the failed tasks in the Metadata, then these tasks can be rescheduled and executed based on the retry configurations.
is it possible that the whole Airflow server gets down?
yes it is possible for different reasons, and you have some different solutions/tips for each one:
problem in the Metadata: the most important part in Airflow is the Metadata where it's the central point used to communicate between the different schedulers and workers, and it is used to save the state of all the dag runs and tasks, and to share messages between tasks, and to store variables and connections, so when it gets down, everything will fail:
you can use a managed service (AWS RDS or Aurora, GCP Cloud SQL or Cloud Spanner, ...)
you can deploy it on your K8S cluster but in HA mode (doc for postgresql)
problem with the scheduler: the scheduler is running as a pod, and the is a possibility to lose depending on how you deploy it:
Try to request enough resources (especially memory) to avoid OOM problem
Avoid running it on spot/preemptible VMs
Create multiple replicas (minimum 3) for the scheduler to activate HA mode, in this case if a scheduler gets down, there will be other schedulers up
problem with webserver pod: it doesn't affect your workload, but you will not be able to access the UI/API during the downtime:
Try to request enough resources (especially memory) to avoid OOM problem
It's a stateless service, so you can create multiple replicas without any problem, if one gets down, you will access the UI/API using the other replicas
I have an ECS cluster (fargate), task, and service I have had setup in Terraform for at least a year. I haven't touched it for a long while. My normal deployment for updating the code is to push a new container to the registry and then stop all tasks on the cluster with a script. Today, my service did not run a new task in response to that task being stopped. It's desired count is fixed at so it should.
I have go in an tried to manually run this and I'm seeing this error.
Unable to run task
Http request timed out enforced after 4999ms
When I try to do this, a new stopped task is added to my stopped tasks lists. When I look into that task the stopped reason is "Deployment restart" and two of them are now showing "Task provisioning failed." which I think might be tasks the service tried to start. But these tasks do not show a started timestamp. The ones I start in the console have a started timestamp.
My site is now down and I can't get it back up. Does anyone know of a way to debug this? Is AWS ECS experiencing problems right now? I checked the health monitors and I see no issues.
This was an AWS outage affecting Fargate in us-east-1. It's fixed now.
I've created a simple task to print a hello world. I've created a ECR image, docker compose and ecs-params.yml.
I get the cloudwatch log for the print, but the task keeps launching every minute, which I guess it's due to REPLICA service type.
How can I stop this from happening, I want to launch this Fargate task ONLY from a lambda, and when it finishes I don't it to be relaunched.
Thanks in advance
If you want a one-shot / one-off / standalone task to be launched by ECS and have it run until it finishes, you wouldn't use an ECS service definition but merely a task.
You can run tasks on their own without packaging as an ECS service.
See: https://docs.aws.amazon.com/AmazonECS/latest/developerguide/ecs_run_task.html
If you are using the ECS CLI, then there is also ecs-cli compose create. So, you would use that call and not the one also creating an ECS service along with it.
You can then use AWS Lambda and send an ecs:RunTask AWS API call to invoke/start the ECS task.
I am trying to upgrade an application deployed to service fabric.
How can I only upgrade nodes that have no active connections and wait for the busy nodes to finish before upgrading them?
Most of the time, you don't really have to worry about the upgrades on a node level as the SF runtime handles it internally if configured in Monitored mode. This is what we've been using with a high level of success and never really had to do much. This also fit our requirement that all upgrade domains (nodes) have to match our health state policies before considered healthy.
If you want to have more advanced control over your upgrades like using request draining etc, have a look at the info as mentioned here. But to be honest, we've been quite happy with just using monitored mode and investigating why stuff fails if it does. We had some apps that had a long background task running as a stateful actor that sometimes failed upgrade and most always it was due to an issue that was caused in the background task itself instead of anything to do with Service Fabric.
Service Fabric knew when no active connections and background tasks were running to then upgrade nodes and we could actually see the nodes that were temporarily 'stuck' due to waiting for an active background task to finish.
I have a batch process, written in PHP and embedded in a Docker container. Basically, it loads data from several webservices, do some computation on data (during ~1h), and post computed data to an other webservice, then the container exit (with a return code of 0 if OK, 1 if failure somewhere on the process). During the process, some logs are written on STDOUT or STDERR. The batch must be triggered once a day.
I was wondering what is the best AWS service to use to schedule, execute, and monitor my batch process :
at the very begining, I used a EC2 machine with a crontab : no high-availibilty function here, so I decided to switch to a more PaaS approach.
then, I was using Elastic Beanstalk for Docker, with a non-functional Webserver (only to reply to the Healthcheck), and a Crontab inside the container to wake-up my batch command once a day. With autoscalling rule min=1 max=1, I have HA (if the container crash or if the VM crash, it is restarted by AWS)
but now, to be more efficient, I decided to move to some ECS service, and have an approach where I do not need to have EC2 instances awake 23/24 for nothing. So I tried Fargate.
with Fargate I defined my task (Fargate type, not the EC2 type), and configure everything on it.
I create a Cluster to run my task : I can run "by hand, one time" my task, so I know every settings are corrects.
Now, going deeper in Fargate, I want to have my task executed once a day.
It seems to work fine when I used the Scheduled Task feature of ECS : the container start on time, the process run, then the container stop. But CloudWatch is missing some metrics : CPUReservation and CPUUtilization are not reported. Also, there is no way to know if the batch quit with exit code 0 or 1 (all execution stopped with status "STOPPED"). So i Cant send a CloudWatch alarm if the container execution failed.
I use the "Services" feature of Fargate, but it cant handle a batch process, because the container is started every time it stops. This is normal, because the container do not have any daemon. There is no way to schedule a service. I want my container to be active only when it needs to work (once a day during at max 1h). But the missing metrics are correctly reported in CloudWatch.
Here are my questions : what are the best suitable AWS managed services to trigger a container once a day, let it run to do its task, and have reporting facility to track execution (CPU usage, batch duration), including alarm (SNS) when task failed ?
We had the same issue with identifying failed jobs. I propose you take a look into AWS Batch where logs for FAILED jobs are available in CloudWatch Logs; Take a look here.
One more thing you should consider is total cost of ownership of whatever solution you choose eventually. Fargate, in this regard, is quite expensive.
may be too late for your projects but still I thought it could benefit others.
Have you had a look at AWS Step Functions? It is possible to define a workflow and start tasks on ECS/Fargate (or jobs on EKS for that matter), wait for the results and raise alarms/send emails...