I would like to launch multiple Amazon EC2 spot instances (fleet?) using a custom AMI (docker?) for performing a deep-learning training task. I would like all the instances to share a common set of files for the purposes of training the model.
The idea here is not to lose training history and keep a backup in EBS (network drive?) when the spot instance is terminated by AWS due to pricing-limit/demand. The task state can be updated in a file and then resumed when instances are available.
Is it possible to launch all instances and let them work cooperatively to complete the training task? What kind of a setup could accomplish this?
Firstly, you might be interested in the Deep Learning AMI from the AWS Marketplace, which comes fully-configured with popular Deep Learning tools.
If the software you are using wishes to save its data to a local file system (as opposed to Amazon S3), then you could use Deep Learning AMI to share a file system amongst multiple Amazon EC2 instances (including Spot instances). Amazon EFS is similar to a NAS and can be used simultaneously across multiple instances.
The EFS volume could be mounted via a User Data script, together with a setup script to load and run your desired application (which can be easier than making a new AMI).
Related
I wanted to know is it possible to automate the creation of AMI in AWS without downtime and data loss, if possible how can we achieve it.
I have use system manager-> maintenance window in which i have set the reboot to true for data integrity, but i need a way so that the data is not lost.
Any help will be appreciated.
Thank-you.
Answering it as per comments discussion, question is somehow still vague to me
You have EBS right now. I'm not sure if your Instances are in Same AZ or not. If they are in same AZ then you can use EBS multi attach feature (available for IO volumes only) to share same storage with all of them.
Regarding backup you can choose EBS snapshots
Ideally my suggestion to you would be create a launch template, use EFS that can be mounted to multiple instances in same region, if you want it across regions then create mount targets. EFS is natively integrated with AWS backup.
Whenever any failover happens or your EC2 crashes for any reason and it goes less than your target capacity, auto scaling would automatically provision a new instance using launch template which would be using same EFS
but i need a way so that the data is not lost.
if you want to achieve this, then According to Docs, you need to ensure that application or os is not writing to ebs, which can be managed by either a script or a custom logic.
You can take a snapshot of an attached volume that is in use. However, snapshots only capture data that has been written to your Amazon EBS volume at the time the snapshot command is issued. This might exclude any data that has been cached by any applications or the operating system. If you can pause any file writes to the volume long enough to take a snapshot, your snapshot should be complete. However, if you can't pause all file writes to the volume, you should unmount the volume from within the instance, issue the snapshot command, and then remount the volume to ensure a consistent and complete snapshot.
if you achieved the above then you can automate the creation, retention, and deletion of EBS snapshots and EBS-backed AMIs it using Data Lifecycle Manager
I haven't tried this but I think exporting VM to S3 and then automating the entire pipeline with Ec2 image builder should do the trick, you can customise your further images with build components
Refers importing and exporting vm's
Unfortunately there is not of box solution other than compromising data integrity but you can try above mentioned which can ensure data integrity and automation
I am currently looking for a way of easily distributing customised volumes to clients.
An approach I am looking at is creating RAW disk images, saving them to S3 and having clients import them as snapshots using the AWS CLI.
My question is - who pays for the data access request/data transfer?
...I'm assuming its bucket owner as there is no "requester-pays" option for the Import-Snapshot command. Has anybody done anything similar?
Another approach is directly sharing snapshots to a clients account - but this involves an added charge on our part to create the ideal sized volumes + generate the snapshots to share.
Is there a better method of generating + sharing data (essentially what would become EBS volumes) of varying sizes and content?
The easiest method would be to create an Amazon Machine Image (AMI), which is a bootable snapshot. You can list this it as a Community AMI.
Your clients can select the AMI when launching an Amazon EC2 instance. The boot disk will be exactly as you configured -- with the operating system, your application and all configurations that were saved on the disk.
There is no cost to you when a client uses the AMI.
See: Make an AMI public - Amazon Elastic Compute Cloud
We have an EC2 instance running in AWS EC2 instance. We have our ML algorithms and data that. We have also hosted a web-based interface also in that machine.
Now there are no new developments happening in that EC2 instance. We would like to terminate AWS subscription for a short period of time (for the purpose of cost-reduction and exploring new cloud services). Most importantly, we want to be in a position where we can purchase a new EC2 instance with a fresh AWS subscription, use the backup which we take now, and resume all operations (web-backend, SMS services for our app which is hosted in AWS, etc.).
What is the best way to do it? Is temporary termination of AWS subscription advisable?
There is no concept of an "AWS Subscription". AWS is charged on-demand, which means you only pay when you use resources.
If you temporarily do not want the Amazon EC2 instance, you could:
Stop the instance, which is like turning off the power. You will not be charged for the instance, but you will still pay for the disk storage attached to the instance. You can simply Start the instance again when you wish to use it. You will only be charged while the instance is running. OR
Create an image of the instance, then terminate the instance. This will create an Amazon Machine Image (AMI), which contains a copy of the disks. You can then launch a new Amazon EC2 instance from the AMI when you wish to use it again. This is a lower-cost option compared to simply stopping the instance, but it takes more effort to stop/start.
It is quite common for companies to stop Amazon EC2 instances at night or over the weekend to reduce costs while they are not needed.
EDIT: Just thought of a third option. Will test it and be back. Not worth it; it would involve creating an image from the EC2 instance and then convert that image to a VM image, storing the VM image in S3. There may be some advantages to this, but I do not see them.
I think you have two options, both of them very reasonably priced. If you can separate the data from the operating system, then your best option would be to use an S3 bucket as a file system within the EC2 instance. Your EC2 instance would use this bucket to store all your "ML algorithms and data" and, possibly, even your "web-based interface". Whenever you decide that you no longer need the processing capacity of the EC2, you would unmount the S3 bucket file system from the EC2 instance and terminate that instance. After configuring an appropriate lifecycle rule for the S3 bucket, it would transition to Glacier, or even Glacier Deep Archive [you must considerer the different options of long term storage]. In the future, whenever you want to work with your data again, you would move your data from Glacier back to S3, create a new EC2 instance, install your applications, mount your S3 bucket as a file system and you would have access to all your data. I think this is your least expensive and shortest recovery time objective option. To implement this option, look at my answer to this question; everything you need to use an S3 bucket as a regular folder inside the EC2 instance is there.
The second option provides an integrated solution, meaning the operating system and the data stay together, and allows you to restore everything as it was the day you stopped processing your data. It's made up of the following cycle:
Shutdown your EC2 and make a note of all the specs [you need them further down].
Export your instance to a virtual image, vmdk for example, and store it in your S3 bucket. Something like this:
aws ec2 create-instance-export-task --instance-id i-0d54b0682aa3998a0
--target-environment vmware --export-to-s3-task DiskImageFormat=VMDK,ContainerFormat=ova,S3Bucket=sm-vm-backup,S3Prefix=vms
Configure an appropriate lifecycle rule for the S3 bucket so that it transitions to Glacier, or even Glacier Deep Archive.
Terminate the EC2 instance.
In the future you will need to implement the inverse, so you will need to restore the archived S3 Object [make sure you you can live with the time needed by AWS to do this]
Import the virtual image as an EC2 AMI, something like this [this is not complete - you will need some more options that you saved above]:
aws ec2 import-image --disk-containers
Format=ova,UserBucket="{S3Bucket=sm-vm-backup,S3Key=vmsexport-i-0a1c382e740f8b0ee.ova}"
Create an EC2 instance based on the image and you're back in business.
Obviously you should do some trial runs and even automate the entire process if it's something that will be done frequently. I have a feeling, based on what you said, that the first option is a better option, provided you can easily install whatever applications they use.
I'm assuming that you launched an EC2 instance from a base Amazon Machine Image and then added your own software and models to it. As opposed to launched an EC2 instance from an AWS Marketplace offering.
The simplest thing to do is to create an Amazon Machine Image (AMI) from your running EC2 instance. That will capture the current state of the instance and persist it in your AWS account. Then you can terminate the instance. Later, when you want to recreate it, launch a new instance, selecting the saved AMI instead of a standard AMI.
An alternative is to avoid the need to capture machine state at all, by using standard DevOps practices to revision-control everything you need to recreate the state of a running machine.
Note that there are costs associated with an AMI, though they are minimal ($0.05 per GB-month of data stored, for example).
I had contacted AWS customer care regarding this issue. Given below is the response I received. Please add your comments on which option might be good for me.
Note: I acknowledge the AWS customer care team for their help.
I understand that you require some information on cost saving for your
Instance since you will not be utilizing the service for a while.
To assist you with this I would recommend checking out the Instance
Stop/Start link here:
==>https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/Stop_Start.html .
When you stop an Instance, you do not lose any data & you are not
charged for the resources any further. However please keep in mind
that you will still be charged for any EBS Storage Volumes attached to
the stopped Instance(s).
I also recommend checking out the below links on how you can reduce
your costs.
==>https://aws.amazon.com/premiumsupport/knowledge-center/reduce-aws-bill/
==>https://aws.amazon.com/blogs/compute/10-things-you-can-do-today-to-reduce-aws-costs/
That being said, please note that as I am in the billing department,
for the best assistance with the various plans you will require the
assistance of our Sales Team.
The Sales Team will be able to assist with ways to save while
maintaining your configurations.
You will be able to reach the Sales Team here:
==>https://aws.amazon.com/websites/contact-us/.
Once you have completed the details in the link, a member of the team
will be in touch with you at their soonest.
I'm trying AWS auto-scaling for the first time, as far as I understand it creates instances if for example my CPU Utilization reaches critical level, that I define.
So I am curious, after I lunch my instance I spend a fair amount of time configuring it and copying the data, if AWS auto-scales my instance how will it configure the new instances and move the data to it?
You can't store any data that you want to keep on an instance that is part of an autoscaling group (well you can, but you will lose it).
There are (at least) two ways to answer your question:
Create a 'golden image', in other words spin-up an instance, configure it, install the software etc and then save it as an AMI (amazon machine image). Then tell the autoscaling group to use that AMI each time an instance starts - it will be pre-configured when it starts.
Put a script on the instance that tells the instance how to configure itself when it starts up (in the user data). SO basically each time an instance scales up, it runs the script and does all the steps it needs to to configure itself.
As for you data, best practice would be to store any data you want to keep in a database or object store that is not on the instance - so something like RDS, DynamoDB or even S3 objects.
You could also use AWS EFS, store there your data/scripts that the EC2 Instances will be sharing, and automatically mount it every time a new EC2 Instance is created via /etc/fstab.
Once you have configured the EFS to be mounted on the EC2 Instance (/etc/fstab), you should create a new AMI, and use this new AMI to create a new Launch Configuration and AutoScaling Group, so that the new Instances automatically mount your EFS and are able to consume that shared data.
https://aws.amazon.com/efs/faq/
Q. What use cases is Amazon EFS intended for?
Amazon EFS is designed to provide performance for a broad spectrum of
workloads and applications, including Big Data and analytics, media
processing workflows, content management, web serving, and home
directories.
Q. When should I use Amazon EFS vs. Amazon Simple Storage Service (S3)
vs. Amazon Elastic Block Store (EBS)?
Amazon Web Services (AWS) offers cloud storage services to support a
wide range of storage workloads.
Amazon EFS is a file storage service for use with Amazon EC2. Amazon
EFS provides a file system interface, file system access semantics
(such as strong consistency and file locking), and
concurrently-accessible storage for up to thousands of Amazon EC2
instances. Amazon EBS is a block level storage service for use with
Amazon EC2. Amazon EBS can deliver performance for workloads that
require the lowest-latency access to data from a single EC2 instance.
Amazon S3 is an object storage service. Amazon S3 makes data available
through an Internet API that can be accessed anywhere.
https://docs.aws.amazon.com/efs/latest/ug/mount-fs-auto-mount-onreboot.html
You can use the file fstab to automatically mount your Amazon EFS file
system whenever the Amazon EC2 instance it is mounted on reboots.
There are two ways to set up automatic mounting. You can update the
/etc/fstab file in your EC2 instance after you connect to the instance
for the first time, or you can configure automatic mounting of your
EFS file system when you create your EC2 instance.
I recommend using a shared data container if it is data that is updated and the updated data is needed by all instances that might be spinning up.
If it is database data or you could store the needed data in a database I would consider using an RDS.
If it is static data only used to configure the instances like dumps or configuration files which are not updated by running instances then I would recommend pulling them from CloudFlare or S3 of iT is not possible to pull them from a repository.
Good luck
I am trying to create a backup mechanism for our server, so that if my system crashes, I should be able to create the whole system by running a single script
After going through Amazon documentation, this is my understanding of creating a backup and restoring
Backup
Create a AMI Image (this can be updated monthly)
Create a snapshot (This can be done using a daily script creating a snapshot)
Restore (A script to)
Create an EBS instance using AMI
Attach the EBS volume to Instance created
Now my Questions are
Is it the best way to take a backup and restore?
Do we actually need to backup 2 things, AMI and EBS volume (using snapshot), Can we just keep snapshots?
I understand this cannot work for a local instance store instance, as there is no snapshot functionality. So how can I create a backup and restore process for local instance store instances?
As I could not find any better alternative, I am sticking with the initial approach.
For EBS
Backup:
Create a AMI Image (this can be updated monthly).
Create a snapshot (This can be done using a daily script creating a snapshot).
Restore (A script to)
Create an EBS instance using AMI.
Attach the EBS volume to Instance created.
For instance store, I am only keeping the application (no database), so no need to keep a backup of that.
EBS Snapshots are an excellent way to create backups.
You can perform frequent Snapshots of your EBS Volumes via scripts. Weekly, Daily, Hourly, or as frequently as your Credit Card will allow. The only limit is around how many simultaneous snapshots you can be doing - when you hit that, the EBS API will start giving back errors until a few of the in-flight operations complete.
Snapshots can also be copied from Region to Region in order to provide backup against a catastrophic event.
When you snapshot an EBS volume, that snapshot is of the entire volume. Even if it was created from an AMI, your snapshot contains everything you need to create a new instance of the volume. You can pretty easily try this yourself.
If your instances are Linux based, there is no need to create an AMI if you're taking snapshots. You can create the AMI on the fly, from the snapshots, when you need to recover. If you got that process automated, it's pretty easy to do.
In Windows there is a limitation not allowing to launch an EC2 instance from a snapshot, so AMIs must be used. There are ways to workaround that limitation: You can check out the this post I wrote in our company's blog:
http://www.n2ws.com/blog/3-ways-ec2-windows-backup-and-recovery.html
I would suggest to use Auto Scaling in addition to EBS snapshots. If Instance is dying because of Hardware failure or it's scheduled for retirement by Amazon, Auto Scaling will start new Instance automatically.
But in this case, you have to setup NAS for your dynamic data. Depending on Server Load, the number of running Instances will be different and all your scaling servers must mount NAS storage which is shared across them.
Your Database should be on separate server or servers as well. Or you might want to use Amazon RDS as it has great auto-backup / Point-In-Time-Restore features, but you have to pay extra for that.
1) Yes.Snapshot is best way to backup and restore EBS volumes.
2) Depends, if you have the root volume as EBS backed AMI, then you can snapshot them as well and improves the manageability
3) Rsync and AMI is the option available for instance store