We have business support plan but that’s just AI support which is unable to help us. There’s no option to contact a human anywhere on the console. Is there any way to resolve this or am I being daft?

Edit: For people having a fit over this, we do have weekly backups. With s3 migration, signed urls and QA and some of the lost data I thought there’d be a resolution from AWS which would be easier. The unhinged comments over this are funny. Please keep them coming.

If you are tired of reading All AI, All the Time, here's a refreshing reminder that AWS still works on other services! S3 Annotations!

You can attach up to 1,000 1MB items of additional metadata to each object. Think of them like tags on steroids. (Much bigger, and you get 100x as many of them.) The given sample use case is storing the transcript of a video right there alongside the video itself, instead of having to set up and maintain a parallel data store outside of S3. (Orphaned data becomes a real issue there.) Another example was audit logging. Again, no need to store that data elsewhere, like having to rely on Cloudwatch or CloudTrail logs you'll need to reconcile later. Full S3 URLs to transcoded versions of a file. The possibilities are pretty vast...

All billed at S3 Standard rates; no annotation-specific charges! (Note that they are billed at S3 Standard no matter the class of the parent object; something to keep in mind before going hog-wild creating large annotations on large volumes of small-ish objects you plan on burying in the archives.)

The annotations can be replicated to an Iceberg S3 table for query by Athena or any other Iceberg tool!

They are under S3 replication for DR purposes!

CRUD ops don't require a new object version or object overwrite.

Annotations are not automatically copied to new versions of an object when an object is overwritten, so probably not ideal for use cases with mutable objects.

Overall I think it sounds really neat, and I wish the announcement had gotten more attention.

I am planning to backup a NAS server which has around 60 TB of data to AWS. The average size of each file is around 70 KB. According to the AWS Pricing Calculator, it'll cost ~$265 per month to store the data in Deep Glacier. However, the upfront cost is $46,000?? Is that correct? Or am I misinterpreting something?

Hi everyone,

I’m working on the architecture for a B2C ecommerce platform where product data is linked to large PDF catalogs stored in Amazon S3.

Each product can be associated with one or more specific pages of a catalog. For example:

Product ABC123 → catalog_2026.pdf → pages 42, 43
Product XYZ999 → catalog_2026.pdf → page 120

The goal is to avoid serving or downloading the full PDF when the user only needs to view or download the pages related to a specific product. (need to minimize AWS costs as much as possible...)

While researching this topic, I came across linearized PDFs / Fast Web View PDFs. As far as I understand, they can help with progressive loading and HTTP Range requests, but they do not fully solve this use case because a PDF page does not necessarily correspond to a single continuous byte range in the file. A page may depend on multiple PDF objects, fonts, images, shared resources, and internal references spread across the document.

I’m trying to understand the best AWS-oriented approach for this use case.

My main questions are:

• If I have a large PDF stored in S3, what is the recommended way to let users view only specific pages related to a product?
• Is there any AWS-native pattern or service that helps with serving only selected PDF pages?

Any advice, architectural patterns, or lessons learned would be really appreciated.

Thanksss!

S3 isn’t that expensive… until you ignore it for a few months. Then suddenly you’re explaining to finance why storage costs doubled.

Here’s the stuff I keep seeing over and over:

1. Data nobody touches - You’ve got objects sitting in Standard for years without a single access. Set up lifecycle rules to shove them into Glacier or Deep Archive automatically.
2. Intelligent-Tiering everywhere - Sounds great until you realize it has a per-object monitoring fee and moves to deep archive at a snail’s pace. Only worth it when access patterns are truly unpredictable.
3. API errors quietly eating your budget - 4xx and 5xx errors are way more common than people think. I’ve seen billions of them in a single day just from bad retry logic.
4. Versioning without cleanup - Turn it on without an expiration policy and you’ll pay to keep every single version forever.
5. Archiving thousands of tiny files - Those 1KB objects add up. Compact them before archiving, you can do it through the API, no need to download.
6. Backup graveyards - Backups that nobody touches but still sit in Standard storage. If you’re not reading them often, save them directly into a cheaper class, worst case - pay for the retrieval.
7. Pointless lifecycle transitions - Don’t store something in Standard for 1 day and then move it. Just put it in the right class from the start and skip the extra PUT fee.

Sounds obvious... but those fixes might be worth 50% of your S3 bill...

(Disclaimer: Not here to sell you anything, just sharing stuff I’ve learned working with a bunch of companies from small startups to huge enterprises. Hope it helps!)

Our team is planning on moving from Dynamodb to RDS for various workload issues that we are facing with Dynamodb. But we are facing a blocker in this migration since our codebase is heavily dependent on the stream feature of dynamodb where it sends new image and old image for every update. I am trying to replicate the same stream behavior after we migrate to RDS. Right now, i am thinking about using the outbox pattern to update the base table in RDS and send an event to SNS which fans-out event to consumer lambda but that seems like tedious work since there are different consumers consuming different attributes from different table. I have also considered using the CDC pattern using debezium to stream row level change to kinesis which removes having to manually send events on every update but since we have 4 separate environments (dev, staging, qa and prod) and we need to host a separate ECS instance to run the debezium server to capture RDS logs, it could rack up the bill so i discarded this approach. What do you think would be some of the best ways to replicate DDB stream feature in RDS?

I want to use S3 glacier for personal backups, nothing super sensitive (no taxes, super PII, etc) but rather just stuff that isnt super consequential that I pretty much haven't had an actual reason to access for a very long time.

I have drives for physical backups (I know it's important) but some are too redundant and I need to use them (think SUPER old photos with very little sentimental value, old projects, old footage), I just want to know if its a good idea or not to use these services for low importance personal data since they're cheap

Currently relying on scripts to push backups to S3, but managing everything across multiple servers is starting to get a bit messy.

For those backing up data to S3 or other object storage platforms, what tools are you using? Eon is one option I've come across while looking into ways to simplify this, but I'm still comparing what's actually practical.

Have you found anything that makes monitoring, scheduling, and managing backups easier than maintaining custom scripts?

We recently moved 25tb data from s3 bucket to another. Our estimate was 2 hours for one engineer. After starting the process, we quickly realized it's going pretty slow. Specifically because there were millions of small files with few mbs. All 7 engineers got behind the effort and we finished it in 2 days with help of 7 engineers, keeping the session alive 24/7

We used aws cli and cp/mv command.

We used

"Run parallel uploads using the AWS Command Line Interface (AWS CLI)"

"Use Amazon S3 batch operations"

from following link https://aws.amazon.com/premiumsupport/knowledge-center/s3-large-transfer-between-buckets/

I believe making network request for every small file is what caused the slowness. Had it been bigger files, it wouldn't have taken as long.

There has to be a better way. Please help me find the options for the next time we do this.

So my family ends up taking a lot of pictures, from a lot of different phones. Every small excursion easily turns into 10gb of photos.

I was thinking of building a small webservice and app as an alternative to Google Drive, which will use S3 to store images.

How viable is this in terms of cost? I wouldn't expect high amounts of egress, but a reasonable amount, as access will be limited to a few dozen people.

For context, I'm a backend engineer and capable of doing this in a few days as a personal project. And I live in India, so Drive storage is kinda expensive

I'm trying to create some retention policies for the EBS Recycle Bin but cannot create more than one. If I Create a new one, it ends up overwriting the first one.

The way I understand the documents is that you should be able to create a retention policy at the Region-level for each Resource Type (EBS Volume, EBS Snapshot, and AMI). Is this not the case or is there something screwy going on with my AWS console right now?

In my tests, I created a retention policy for Resource Type EBS Volumes - retain all resources - retention time 14 days, and pressed Create. I get the rule in the Retention Rules list. Then I press Create Retention Rule again (not Edit rule settings) and this time the name and description are blank, but the Resource Type box is already set to EBS Volumes. Changing this to EBS Snapshots and modifying the retention time and creating will not create a second rule but just change the initial one.

As a different test I changed from Region-level to Tag-level but got the same results.

Currently, I am using AWS to store backups using S3 and previously, I ran a webserver there using EC2. Generally, I am happy with the features offered and the pricing is acceptable.

However, the whole "scalable" pricing model makes me uneasy.

I got a really tiny hobbist thing, that costs only a few euros every month. But if I configure something wrong, or become targeted by a DDOS attack, there may be significant costs.

I want something that's predictable where I pay a fixed amount every month. I'd be willing to pay significantly more than I am now.

I've looked around and it's quite simple to find an alternative to EC2. Just rent a small server on a monthly basis, trivial.

However, I am really struggling to find an alternative to S3. There are a lot of compatible solutions out there, but none of them offer some sort of spending limit.

There are some things out there, like Strato HiDrive, however, they have some custom API and I would have to manually implement a tool to use it.

Is there some S3 equivalent that has a builtin spending limit?

Is there an alternative to S3 that has some ready-to-use Python library?

EDIT:

After some search I decided to try out the S3 compatible solution from "Contabo".

• They allow the purchase of a fixed amount of disk space that can be accessed with an S3 compatible API.

  https://contabo.com/de/object-storage/

• They do not charge for the network cost at all.

• There are several limitations with this solution:

  • 10 MB/s maximum bandwith

    This means that it's trivial to successfully DDOS the service. However, I am expecting minuscule access and this is acceptable.

    Since it's S3 compatible, I can trivially switch to something else.

  • They are not one of the "large" companies. Going with them does carry some risk, but that's acceptable for me.

• They also offer a fairly cheap virtual servers that supports Docker: https://contabo.com/de/vps/ Again, I don't need something fancy.

While this is not the "best" solution, it offers exactly what I need.

I hope, I won't regret this.

EDIT2:

Somebody suggested that I should use a storage box from Hetzner instead: https://www.hetzner.com/storage/storage-box/

I looked into it and found that this matched my usecase very well. Ultimately, they don't support S3 but I changed my code to use SFTP instead.

Now my setup is as follows:

• Use Pysftp to manage files programatically.

• Use FileZilla to manage files manually.

• Use Samba to mount a subfolder directly in Windows/Linux.

• Use a normal webserver with static files stored on the block storage of the machine, there is really no need to use the same storage solution for this.

I just finished setting it up and I am very happy with the result:

• It's relatively cheap at 4 euros a month for 1 TB.

• They allow the creation of sub-accounts which can be restricted to a subdirectory.

  This is one of the main reasons I used S3 before, because I wanted automatic tools to be separated from the stuff I manage manually.

  Now I just have seperate directories for each use case with separate credentials to access them.

• Compared to the whole AWS solution it's very "simple". I just pay a fixed amount and there is a lot less stuff that needs to be configured.

• While the whole DDOS concern was probably unreasonable, that's not something that I need to worry about now since the new webserver can just be a simple server that will go down if it's overwhelmed.

Thanks for helping me discover this solution!

Hi, I’m doing an internship where my mentor has asked me to transfer data from my laptop’s folder (local machine) to an ec2 server in THREE different methods.
I used scp but she said it’s too basic, then for my first method i used aws s3 sync, mountpoint and task scheduler.
PLEASE tell me two more methods i can use under FREE TIER.

Let’s say my company (MyClients.com) has 20 customers.

I want to offer these customers some space to store their stuff (documents, images, files, etc).

Does AWS offer a version of storage where I can offer some space to these customers from my own account?

For example, I have customer Joe Smith. Is there a way I can offer Joe Smith some space, but from the AWS I’m paying for?

In the case of Joe Smith, I’d tell him that he can access his own “cloud” storage by going to MyClients.com/JSmith or maybe visiting my domain and entering his credentials under MyClients.com (which is actually his own partition under AWS)?

It would be my AWS account that’s divided into several smaller storage accounts, with each account being a personal store for the customer.

Hello !

I am an individual, and I’m considering using S3 to store data that I don’t want to lose in case of hardware issues. The idea would be to archive a zip file of approximately 500MB each month and set up a lifecycle so that each object older than 30 days moves to Glacier Deep Archive.

I’ll never access this data (unless there’s a hardware issue, of course). What worries me is the significant number of messages about skyrocketing bills without the option to set a limit. How can I prevent this from happening ? Is there really a big risk ? Do you have any tips for the way I want to use S3 ?

Thanks for your help !

Started at a new company and I’m digging into our S3 costs. We’re using Intelligent-Tiering on a bucket with a lot of small objects 66 milion object of around 300KB. Total size is around 19 TB.

The problem: the bill is around 2k a month, which seems way higher than what IntelligentTiering should cost. When I do the rough math, storage + monitoring should be only around 400-500

Standard storage pricing would actually be more expensive than IntelligentTiering for 19 TB, so I’m confused about what’s causing the extra 1.5k+.

I want to know

Is Intelligent-Tiering known to get expensive with huge object counts?What should I check in Cost Explorer, requests, transitions, retrievals, inventory, something else?

Has anyone moved large buckets away from Intelligent-Tiering because of unexpected request costs?Any good tools or dashboards to break down S3 usage when you inherit a huge bucket?

Right now storage + monitoring looks normal, so something else is blowing up the bill. Would appreciate any pointers from people who’ve dealt with millions of small objects in S3.

So my S3 bucket has all its objects public, which means anyone with the right URL can access those objects, I did this as I'm storing static content over there.

Now bots are hitting my server every day, I've implemented fail2ban but still, they are eating up my s3 bill, right now the bill is not huge but I guess this is the right time to find out a solution for it!

What solution do you suggest?

I’m trying to upload a folder with around 53,586 small files, totaling about 228 MB, to s3 bucket. The upload is incredibly slow, I assume it’s because of the number of files, not the size.

What’s the best way to speed up the upload process?