I currently have an EC2 instance that is on constantly, but has very low usage. I wish to shut down the instance when not in use and restart the instance when it is accessed.
It can be turned off automatically with CloudWatch Alarms fairly easily (tutorial here: https://successengineer.medium.com/how-to-automatically-turn-off-your-ec2-instance-in-2021-b73374e51090 ).
What I cannot find is a way to start the instance automatically when there is an incoming request, given that there are no other instances active.
Currently users arrive by redirection from a Route 53 record (policy: simple, type: A).
The Route 53 record can be changed to make this possible.
If the request is sent to the EC2 instance via an A-Record, then it is not possible to 'activate' the EC2 instance. This is because the request is being sent to the IP address of an instance that is turned off.
One option would be to provide a way for users to Start the instance, and after 1-2 minutes they could access the instance. Some ways to trigger the instance to start are:
Use the AWS CLI to call StartInstances() (but this requires AWS credentials)
Use a web browser to access a URL, which triggers an AWS Lambda function, which calls StartInstances()
If you do not want users to first Start the instance and wait until it is available, you'll need to send the requests to something that is not the EC2 instance. That 'something' could then check that the instance is running (and Start the instance if it is not running), and then forward the request to the instance. Since you are probably doing this to save money, you presumably don't want to use something that is "always on" to do this task.
You should be able to create an AWS Lambda function with a web-accessible URL, so that requests are sent to the Lambda function instead of the instance. The Lambda function would confirm that the instance is running and then forward the request to the instance, and then pass back the response to the user. OR, it could return an HTTP redirect to send the user to the instance. (So, the URL will change between the original request and where the response comes from.)
Bottom line: There is no easy way to achieve what you want. You could use auto-scaling to handle variable loads, but that assumes that at least one instance is always running. If an instance is off, it cannot respond to requests sent to the instance.
I think chrome to cloud run is doing http/2 from what I am reading and looking at developer tools, it shows things as http/2 headers(at least I don't think chrome displays it in http/2 header format if it is http1, but I can't tell as I would think this website is http1 but I see http/2 request headers in chrome's dev tools -> https://www.w3.org/Protocols/HTTP/Performance/microscape/).
Anyways, I am wondering for cloud run if I loop and keep calling a json endpoint to delivery pieces of a file to cloud storage, will it stay connected to the same instance the entire time such that my upload will work with the ByteReader in the server. In this way, I can load large files as long as it loads within the cloud run timeout window.
Does anyone know if this will work or will cloud run see each json request form chrome hit the firewall and the firewall might round robin it among cloud run instances?
Anyways, I am wondering for cloud run if I loop and keep calling a
JSON endpoint to deliver pieces of a file to cloud storage, will it
stay connected to the same instance the entire time ...
The answer sometimes it will and sometimes it will not. Do not design something that depends on that answer.
What you are looking for is often termed sticky sessions or session affinity.
Google Cloud Run is designed as a stateless service.
Google Cloud Run automatically scales container instances and load balances every request. Cloud Run does not offer any session stickiness between requests.
Google Cloud Run: About sticky sessions (session affinity)
Cloud Run offer bidirectional streaming and websocket support. The timeout is still limited to 1 hour, but it's a suitable connection to stream your large file into the same instance (don't crash the instance memory size, remember that even the file that you store take space in memory, because it's a stateless service)
A bad solution is to set a max instance to 1. It's a bad solution, because it's not scalable and, even if most of the time, you will have only one instance, sometime Cloud Run service can provision 2 or more instances and only guaranty you that only one is used at the same time.
I have an AWS, load-balanced, EC2 environment running a legacy ASP website. The application uses session variables to manage user login state.
The problem is, it doesn't always work when the environment scales to 2 or more instances. It's hit and miss and sometimes the variables don't exist after they are declared. Am I missing something for this type of environment?
When, there is only one EC2 instance. No trouble. More, and the session variable doesn't always establish.
Session("loggedin")=true
If you're storing user session "in process" meaning it's stored in the memory of the server running your application, you need to enable "sticky sessions" on your load balancer so that each user is tied to that particular server. Otherwise you run into the issue you're seeing where the load balancer is sending traffic to a different server that may or may not have the session data you're looking for.
(this is a bad idea so don't do this but this will solve your problem)
The proper way to handle session, as sticky sessions doesn't scale properly, is to use a separate service or data store to handle user session data. You can store user session in Elasticache or DynamoDB for example and therefore session will be read outside of your EC2 instances and you can continue to add (or remove) new EC2 instances with no issues. You can also use a database server to handle your session information as well. The key is to not handle session data on the actual EC2 instance.
Check this out: Using DynamoDB with Session
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.
I have an Azure web role with two instances. Both instances are "ready" - running okay.
On my desktop I have four instances of the same program running simultaneously and hitting the web role URL with HTTP requests. Yet according to the logs all requests are dispatched to instance 0 only. I need requests to be dispatched to both instances to test concurrent operation.
Why are requests not dispatched to the second instance and how do I make them dispatched there?
This is likely from the Load Balancer optimizing request routes because all of the requests are coming from the same IP. While it often looks like it, the LB in Azure is not a true dumb Round Robin.
If you just didn't expect this, but the server is handling the load, then you are ok. You could even turn off the second instance until your metrics show the server is busy (saving you money).
If you need to be able to load balance from the same IP, then I would look at using a queue perhaps. Although that would be unusual for a web request (versus some backend processing).
Looks like this behavior is due to IIS "keep alive" (<system.webServer><httpProtocol allowKeepAlive="true">. Because of "keep alive" once a client has been served by an instance it gets stuck with that instance.
Disabling "keep alive" removes that and requests now get to all instances more or less randomly. MSDN says disabling "keep alive" may reduce performance but for the sake of testing concurrent operation it would be okay.