AWS ECS allows for new services to automatically use Service Discovery, as mentioned in the documentation here:
https://docs.aws.amazon.com/AmazonECS/latest/developerguide/service-configure-servicediscovery.html
If I understand correctly, there should always be a namespace and a service created in CloudMap, before a service instance can register itself into it. After registering, the service instance can then be discovered using DNS records, which are kept in Route 53, which is a global service. The namespace has its own private zone and applications from VPCs associated with this zone can query the records and discover the service needed, regardless of the region they are in.
However, if I understand Correctly, CloudMap resources themselves are regional
Let's consider the following scenario: There is a CloudMap namespace and service X defined in region A. For redundancy reasons I would like instances of service X run in region A, but also in region B. However, when configuring service discovery in ECS, it is not possible to use a namespace from region A.
How can then CloudMap service discovery be used in a multi-region environment? Shall corresponding namespaces be created in both regions?
Redundancy can be built in within a single region. I have not seen a regulator yet that expects more than what is offered by multiple Availability Zones in a single region, but if you still wanted to achieve what you are asking, you would need to perform some kind of VPC network peering: https://docs.aws.amazon.com/vpc/latest/peering/peering-scenarios.html#peering-scenarios-full
I've not got experience with how Cloud Map behaves in this context though. Assuming DNS resolution is possible, it would supposedly still work. But aws services are best (cheaper, more stable and lower latency) when used within each region, targeting their region specific api https://docs.aws.amazon.com/general/latest/gr/cloud_map.html
I'm trying to "delete VCP" from within AWS.
When doing so it shows me all the resources that need to be removed. After removing them I'm left with a network interface which seems to be connected to RDS as its description is "RDSNetworkInterface". So when attempting to delete/detach it states: "Network interface is currently in use."
Just can't work out how to remove the association it has with RDS, so I can remove it then finally delete the VCP?
Is the RDSNetworkInterface being used in anyway or attached to any existing resource? Try to describe it and you might get some idea.
Once it is deleted, you should be able to delete vpc as well.
See also: AWS not able to delete network interface
I have created a terraform stack with modules, and within this stack I create:
3 Instances (000, 001,002)
Instance group per each Google Compute Engine (gce) instance
Internal back-end internal load balancer (ilb)
forwarding rule
Everything gets created fine: However as part of new image recycling we have to destroy single instance from those 3 instances created above and rebuild with new image..
My question here is that : When i am try to destroy an Instance
destroy -force -target=module.gce_test.google_compute_instance.test_initial_follower-02
Deletes also the ilb backend, forwarding rules which other instances are using...
Any ideas? Can I delete just the instance with the instance group only, no backend and forwarding rule? Is this possible?
Thanks
I have a web app which runs behind Amazon AWS Elastic Load Balancer with 3 instances attached. The app has a /refresh endpoint to reload reference data. It need to be run whenever new data is available, which happens several times a week.
What I have been doing is assigning public address to all instances, and do refresh independently (using ec2-url/refresh). I agree with Michael's answer on a different topic, EC2 instances behind ELB shouldn't allow direct public access. Now my problem is how can I make elb-url/refresh call reaching all instances behind the load balancer?
And it would be nice if I can collect HTTP responses from multiple instances. But I don't mind doing the refresh blindly for now.
one of the way I'd solve this problem is by
writing the data to an AWS s3 bucket
triggering a AWS Lambda function automatically from the s3 write
using AWS SDK to to identify the instances attached to the ELB from the Lambda function e.g. using boto3 from python or AWS Java SDK
call /refresh on individual instances from Lambda
ensuring when a new instance is created (due to autoscaling or deployment), it fetches the data from the s3 bucket during startup
ensuring that the private subnets the instances are in allows traffic from the subnets attached to the Lambda
ensuring that the security groups attached to the instances allow traffic from the security group attached to the Lambda
the key wins of this solution are
the process is fully automated from the instant the data is written to s3,
avoids data inconsistency due to autoscaling/deployment,
simple to maintain (you don't have to hardcode instance ip addresses anywhere),
you don't have to expose instances outside the VPC
highly available (AWS ensures the Lambda is invoked on s3 write, you don't worry about running a script in an instance and ensuring the instance is up and running)
hope this is useful.
While this may not be possible given the constraints of your application & circumstances, its worth noting that best practice application architecture for instances running behind an AWS ELB (particularly if they are part of an AutoScalingGroup) is ensure that the instances are not stateful.
The idea is to make it so that you can scale out by adding new instances, or scale-in by removing instances, without compromising data integrity or performance.
One option would be to change the application to store the results of the reference data reload into an off-instance data store, such as a cache or database (e.g. Elasticache or RDS), instead of in-memory.
If the application was able to do that, then you would only need to hit the refresh endpoint on a single server - it would reload the reference data, do whatever analysis and manipulation is required to store it efficiently in a fit-for-purpose way for the application, store it to the data store, and then all instances would have access to the refreshed data via the shared data store.
While there is a latency increase adding a round-trip to a data store, it is often well worth it for the consistency of the application - under your current model, if one server lags behind the others in refreshing the reference data, if the ELB is not using sticky sessions, requests via the ELB will return inconsistent data depending on which server they are allocated to.
You can't make these requests through the load balancer, So you will have to open up the security group of the instances to allow incoming traffic from source other than the ELB. That doesn't mean you need to open it to all direct traffic though. You could simply whitelist an IP address in the security group to allow requests from your specific computer.
If you don't want to add public IP addresses to these servers then you will need to run something like a curl command on an EC2 instance inside the VPC. In that case you would only need to open the security group to allow traffic from some server (or group of servers) that exist in the VPC.
I solved it differently, without opening up new traffic in security groups or resorting to external resources like S3. It's flexible in that it will dynamically notify instances added through ECS or ASG.
The ELB's Target Group offers a feature of periodic health check to ensure instances behind it are live. This is a URL that your server responds on. The endpoint can include a timestamp parameter of the most recent configuration. Every server in the TG will receive the health check ping within the configured Interval threshold. If the parameter to the ping changes it signals a refresh.
A URL may look like:
/is-alive?last-configuration=2019-08-27T23%3A50%3A23Z
Above I passed a UTC timestamp of 2019-08-27T23:50:23Z
A service receiving the request will check if the in-memory state is at least as recent as the timestamp parameter. If not, it will refresh its state and update the timestamp. The next health-check will result in a no-op since your state was refreshed.
Implementation notes
If refreshing the state can take more time than the interval window or the TG health timeout, you need to offload it to another thread to prevent concurrent updates or outright service disruption as the health-checks need to return promptly. Otherwise the node will be considered off-line.
If you are using traffic port for this purpose, make sure the URL is secured by making it impossible to guess. Anything publicly exposed can be subject to a DoS attack.
As you are using S3 you can automate your task by using the ObjectCreated notification for S3.
https://docs.aws.amazon.com/AmazonS3/latest/dev/NotificationHowTo.html
https://docs.aws.amazon.com/cli/latest/reference/s3api/put-bucket-notification.html
You can install AWS CLI and write a simple Bash script that will monitor that ObjectCreated notification. Start a Cron job that will look for the S3 notification for creation of new object.
Setup a condition in that script file to curl "http: //127.0.0.1/refresh" when the script file detects new object created in S3 it will curl the 127.0.0.1/refresh and done you don't have to do that manually each time.
I personally like the answer by #redoc, but wanted to give another alternative for anyone that is interested, which is a combination of his and the accepted answer. Using SEE object creation events, you can trigger a lambda, but instead of discovering the instances and calling them, which requires the lambda to be in the vpc, you could have the lambda use SSM (aka Systems Manager) to execute commands via a powershell or bash document on EC2 instances that are targeted via tags. The document would then call 127.0.0.1/reload like the accepted answer has. The benefit of this is that your lambda doesn't have to be in the vpc, and your EC2s don't need inbound rules to allow the traffic from lambda. The downside is that it requires the instances to have the SSM agent installed, which sounds like more work than it really is. There's AWS AMIs already optimized with SSM agent stuff, but installing it yourself in the user data is very simple. Another potential downside, depending on your use case, is that it uses an exponential ramp up for simultaneous executions, which means if you're targeting 20 instances, it runs one 1, then 2 at once, then 4 at once, then 8, until they are all done, or it reaches what you set for the max. This is because of the error recovery stuff it has built in. It doesn't want to destroy all your stuff if something is wrong, like slowly putting your weight on some ice.
You could make the call multiple times in rapid succession to call all the instances behind the Load Balancer. This would work because the AWS Load Balancers use round-robin without sticky sessions by default, meaning that each call handled by the Load Balancer is dispatched to the next EC2 Instance in the list of available instances. So if you're making rapid calls, you're likely to hit all the instances.
Another option is that if your EC2 instances are fairly stable, you can create a Target Group for each EC2 Instance, and then create a listener rule on your Load Balancer to target those single instance groups based on some criteria, such as a query argument, URL or header.
Is it possible to do AutoScaling with Static IPs in AWS ? The newly created instances should either have a pre-defined IP or pick from a pool of pre-defined IPs.
We are trying to setup ZooKeeper in production, with 5 zooKeeper instances. Each one should have a static-IP which are to hard-coded in the Kafka's AMI/Databag that we use. It should also support AutoScaling, so that if one of the zooKeeper node goes down, a new one is spawned with the same IP or from a pool of IPs. For this we have decided to go with 1 zoo-keeper instance per AutoScaling group, but the problem is with the IP.
If this is the wrong way, please suggest the right way. Thanks in advance !
One method would be to maintain a user data script on each instance, and have each instance assign itself an elastic IPs from a set of EIPs assigned for this purpose. This user data script would be referenced in the ASGs Launch Configuration, and would run on launch.
Say the user script is called "/scripts/assignEIP.sh", using the AWS CLI you would have it consult the pool to see which ones are available and which ones are not (already in use). Then it would assign itself one of the available EIPS.
For ease of IP management, you could keep the pool of IPs in a simple text properties file on S3, and have the instance download and consult that list when the instance starts.
Keep in mind that each instance will need an to be assigned IAM instance profile that will allow each instance to consult and assign EIPs to itself.