How to make automated S3 Backups - amazon-web-services

I am working on an app which uses S3 to store important documents. These documents need to be backed up on a daily, weekly rotation basis much like how database backups are maintained.
Does S3 support a feature where a bucket can be backup up into multiple buckets periodically or perhaps in Amazon Glacier. I want to avoid using an external service as much as possible, and was hoping S3 had some mechanism to do this, as its a common usecase.
Any help would be appreciated.

Quote from Amazon S3 FAQ about durability:
Amazon S3 is designed to provide 99.999999999% durability of objects over a given year. This durability level corresponds to an average annual expected loss of 0.000000001% of objects. For example, if you store 10,000 objects with Amazon S3, you can on average expect to incur a loss of a single object once every 10,000,000 years
These numbers mean, first of all, that they are almost unbeatable. In other words, your data is safe in Amazon S3.
Thus, the only reason why you would need to backup your data objects is to prevent their accidental loss (by your own mistake). To solve this problem Amazon S3 enables versioning of S3 objects. Enable this feature on your S3 bucket and you're safe.
ps. Actually, there is one more possible reason - cost optimization. Amazon Glacier is cheaper than S3. I would recommend to use AWS Data Pipeline to move S3 data to Glacier routinely.

Regarding Glacier, you can make settings on your bucket to backup (old) s3 data to glaciaer if it is older than specified duration. This can save you cost if you want infrequently accessed data to be archived.

In s3 bucket there are lifecycle rules using which we can automatically move data from s3 to glaciers.
but if you want to access these important documents frequently from backup then you can also use another S3 bucket for backup your data.This backup can be scheduled using AWS datapipeline daily,weekly etc.
*Glaciers are cheaper than S3 as data is stored in compressed format in galaciers.

I created a Windows application that will allow you to schedule S3 bucket backups. You can create three kinds of backups: Cumulative, Synchronized and Snapshots. You can also include or exclude root level folders and files from your backups. You can try it free with no registration at https://www.bucketbacker.com

Related

Amazon S3 Glacier vs Glacier Storage Class

This question might look like an easy/idiot/beginner question but I'm really confused between both of them.
Why do I need to use Amazon S3 Glacier if I can use the normal S3 Bucket and just change the storage class of the objects inside to Glacier manually or by using Lifecycle rule?
Thanks in advance,
In the old days, Amazon Glacier was only available as a separate product. Frankly, the Glacier service is a pain to use.
Every request has to be submitted as a Job, which takes a long time to return. Even obtaining a list of archives is slow, let alone restoring a file from the archive.
The best way to use the Amazon Glacier service is with a third-party tool (eg Cloudberry Backup) that knows how to interface with Glacier, isolating you from having to use it directly.
Then, in 2012, the Amazon S3 team introduced a new Glacier Storage Class where S3 would move the data to Glacier, but still present the objects as being "in S3". (Well, the objects appear in S3 and their metadata is accessible, but the contents of the objects is stored in Glacier.) Then, in 2019, an even lower-cost Glacier Deep Archive storage class offered even lower prices than available through Amazon Glacier itself.
Therefore, it is now both easier and lower cost to use Glacier via Amazon S3 storage classes.
Amazon Glacier still remains available for use, and has been renamed Amazon S3 Glacier to further confuse things. There might be some use-cases where it is preferable to use (eg acting like traditional tape backups for AWS Storage Gateway Tape Gateways), but Glacier Deep Archive in S3 would be the lowest-cost option.
These days most people will just use S3 glacier storage class, because S3 api is much more convenient to work with then Glacier api.
However, Amazon S3 Glacier offers some extra functionality, not available in regular S3. Most notably this would be Vault Lock Policies which allow for fine-grain control of locking your vaults with archives for regulatory purposes.
S3 offers Object Lock which performs similar function, but it is not as versatile as vault lock policies. For example, the s3 object locks can be only enabled on bucket creation, and legal holds apply only to individual versions of objects. In contrast, vault lock policies, as the names suggest, are policy documents written in json, which don't have such limitations.

Fastest and most cost efficient way to copy over an S3 bucket from another AWS account

I have an S3 bucket that is 9TB and I want to copy it over to another AWS account.
What would be the fastest and most cost efficient way to copy it?
I know I can rsync them and also use S3 replication.
Rsync I think will take too long and I think be a bit pricey.
I have not played with S3 replication so I am not sure of its speed and cost.
Are there any other methods that I might not be aware of?
FYI - The source and destination buckets will be in the same region (but different accounts).
There is no quicker way to do it then using sync and I do not believe it is that pricey. You do not mention the number of files you are copying though.
You will pay $0.004 / 10,000 requests on the GET operations on the files you are copying and then $0.005 / 1,000 requests on the PUT operations on the files you are writing. Also, I believe you won't pay data transfer costs if this is in the same region.
If you want to speed this up you could use multiple sync jobs if the bucket has a way of being logically divisible i.e. s3://examplebucket/job1 and s3://examplebucket/job2
You can use S3 Batch Operations to copy large quantities of objects between buckets in the same region.
It can accept a CSV file containing a list of objects, or you can use the output of Amazon S3 Inventory, which can provide a daily or weekly CSV file listing all objects.
While copying, it can also update tags, metadata and ACLs.
See: Cross-account bulk transfer of files using Amazon S3 Batch Operations | AWS Storage Blog
I wound up finding the page below and used replication with the copy to itself method.
https://aws.amazon.com/premiumsupport/knowledge-center/s3-large-transfer-between-buckets/

Confused about *storage-class 'Glacier' use by S3* and *S3-Glacier' service

Still confused about storage-class 'Glacier' use by S3 and S3-Glacier' service.
What's their difference and how about their upload and retrieve?
See a example question below.
You’re researching third-party backup solutions to backup 10 TB of data nightly to Amazon S3. File restores won’t be needed often, but when they are, they’ll need to be available in under five minutes. Your analysis shows that you will exceed your budget for backup storage and you need to find a way to reduce the estimated monthly costs. How should you modify the solution to achieve the cost reduction needed?
Create an S3 lifecycle rule to move the data immediately to Amazon
S3 Glacier
Choose a third-party backup solution that writes directly to the
Amazon S3 Glacier API
Choose a third-party backup solution that leverages AWS Storage
Gateway to write data to Amazon S3 Glacier.
Why option 2 is correct and how about option 1 and option 3? Thanks
Glaicer is a storage class under the S3 service. Glacier is used for archiving data. Glacier and Glacier Deep Archive have a longer retrival time than the other S3 storage tiers (Standard, Standard-IA, One Zone-IA), but also cost significantly cheaper.
This looks like a certification question, CSA - Associate, maybe? You may have forgotten to provide the fourth answer choice.
You cannot move data to Glacier immediately using a lifecycle policy. You can set it to 0 days but it still takes time to make the move.
You do not need third party software to write to the AWS APIs, you can use the CLI and SDKS
This maybe the answer because, using a third-party piece of software that is able to take care of some of the overhead involved in getting a Storage Gateway File Gateway up and running, and configured to store data to Glacier or Glacier Deep Archive is easier.
Typically, "third-party" is not the answer in certification exam questions.

Checking the integrity of an archive uploaded to AWS Glacier

We have daily database backups created and stored on a server. In order to free up space, it was decided that all the backups older than 30 days should be archived using AWS Glacier.
So far so good, I managed to write a PowerShell script to select the required files and upload them to Glacier, but since I am new to all the AWS stuff, I have one question: is it possible to check that the files I have uploaded are indeed in the archive and that there has been no information loss?
My first approach was to send job retrieval requests for all the files that we have uploaded, and 4 hours later compare the checksums and archive ids of our original files and the ones we retrieved from Glacier. However, I think this process takes long, costs extra money, and most importantly, makes no sense at all..
I have also found that I can use inventory retrieval, but as far as I can tell this approach would be very similar to the one described above, just without downloading all the files again.
Lastly, is there even a point to trying to ensure that a file upload was successful if there are no errors? My vague understanding is that AWS would come back with error messages should an upload to Glacier fail, and it computes checksums internally during uploads.
I know that StackOverflow has seen more precisely worded questions, but any clarification regarding this would be immensely appreciated.
You have to try pretty hard to upload a corrupt file to Glacier, because Glacier requires checksums sent with each API request, and will reject the uploads if they don't match the hashes. Obviously you need to spot check your archives, but each one does not need to be downloaded and verified because of the built-in protections.
See Computing Checksums in the Amazon S3 Glacier Developer Guide for descriptions of how this works, on the wire.
Then, consider not using Glacier at all... not directly, anyway. Use S3, and upload your files using the GLACIER or DEEP_ARCHIVE storage class. Or upload them as Standard, with a lifecycle policy that moves them into one of the archive storage classes after 1 day. (Useful because if you delete Glacier or Deep Archive uploads before the minimum storage time, you're billed for the entire minimum time... this way you have a 24 hour "oops I don't like the way I set this up" window, since Standard storage has no minimum storage time period).
Using S3 is a far better solution, because S3 has a much better API and console, but the pricing is identical, because S3 is actually using Glacier as its backend, while you have the advantage of S3 as the frontend. Glacier has essentially no console functionality, is very opaque, and is not really designed for human interaction -- Glacier appears to have been designed as a backing store for an archiving system or service, which is exactly how S3 uses Glacier.
Amazon Simple Storage Service (Amazon S3) supports lifecycle configuration on an S3 bucket, which enables you to transition objects to the Amazon S3 GLACIER storage class for archival. When you transition Amazon S3 objects to the GLACIER storage class, Amazon S3 internally uses Glacier for durable storage at lower cost. Although the objects are stored in Glacier, they remain Amazon S3 objects that you manage in Amazon S3, and you cannot access them directly through Glacier.
https://docs.aws.amazon.com/amazonglacier/latest/dev/introduction.html
It is confusing and unfortunate that AWS recently confused this issue by dumbing things down, rebranding "Glacier" as "S3 Glacier," as if they were the same thing, when they are two very different services, one of which operates in a mode that gives you a gateway to the other. It's similarly unfortunate how Glacier has traditionally been marketed. Without S3 in front, Glacier is not well suited for very many applications.

Expiry date for Glacier backups

Is there a way to set an expiry date in Amazon Glacier? I want to copy in weekly backup files, but I dont want to hang on to more than 1 years worth.
Can the files be set to "expire" after one year, or is this something I will have to do manually?
While not available natively within Amazon Glacier, AWS has recently enabled Archiving Amazon S3 Data to Amazon Glacier, which makes working with Glacier much easier in the first place already:
[...] Amazon S3 was designed for rapid retrieval. Glacier, in
contrast, trades off retrieval time for cost, providing storage for as
little at $0.01 per Gigabyte per month while retrieving data within
three to five hours.
How would you like to have the best of both worlds? How about rapid
retrieval of fresh data stored in S3, with automatic, policy-driven
archiving to lower cost Glacier storage as your data ages, along with
easy, API-driven or console-powered retrieval? [emphasis mine]
[...] You can now use Amazon Glacier as a storage option for Amazon S3.
This is enabled by facilitating Amazon S3 Object Lifecycle Management, which not only drives the mentioned Object Archival (Transition Objects to the Glacier Storage Class) but also includes optional Object Expiration, which allows you to achieve what you want as outlined in section Before You Decide to Expire Objects within Lifecycle Configuration Rules:
The Expiration action deletes objects
You might have objects in Amazon S3 or archived to Amazon Glacier. No
matter where these objects are, Amazon S3 will delete them. You will
no longer be able to access these objects. [emphasis mine]
So at the small price of having your objects stored in S3 for a short time (which actually eases working with Glacier a lot due to removing the need to manage archives/inventories) you gain the benefit of optional automatic expiration.
You can do this in the AWS Command Line Interface.
http://docs.aws.amazon.com/AmazonS3/latest/dev/object-lifecycle-mgmt.html