I'm looking for advice on how to reduce monthly costs for my organization's S3 bucket, which holds around 100 million objects averaging 250 KB each. Currently, we're spending over $500 a month to store them, and since most of these objects are quite old and rarely accessed, I want to take steps to optimize expenses. I've considered several strategies:
1. Intelligent tiering, but the monitoring fees could add up to $250 a month.
2. Lifecycle policies, which seem to come with expensive transition fees—estimates suggest it could cost us around $1,000 to transition all those objects.
3. Manual transitions via CLI look similar in cost to lifecycle policies due to request fees.
4. Aggregating data through zipping isn't feasible for our needs.
5. Deleting old objects is an option, but I'd like to avoid that if possible.
I'm worried about making the wrong choice that could result in even higher costs. Can anyone suggest the best way to go about this? Thanks a bunch!
6 Answers
This might help: set lifecycle rules to transition to Infrequent Access after 30 days of non-use, then archive after 180 days. Transitioning back to Standard on first access could optimize access cost-wise too. It'll cost some upfront to implement, but it should pay off quickly if done right!
I get your concerns! Honestly, $500 a month isn't too bad for a business. If you manage to cut costs to $250, that just translates to a savings of $3,000 a year, which isn't much for the salary of a good software engineer. You should weigh whether the effort and engineering costs to cut savings are worth it in your situation, especially if your object count is expected to grow and costs may rise significantly later.
Implementing a tiering strategy could increase complexity, which makes it crucial to consider the tradeoff. You might save $100-200 monthly with lifecycle rules, but think about whether that’s worth the extra management hassle. Your current expenses are manageable as is, so be sure about your data access patterns before making any transitions that could affect performance.
For a solid strategy, try combining lifecycle rules with a plan for data cleanup. Use a lifecycle policy to transition objects to Infrequent Access after 90 days and then to Glacier after several months. While there are fees, this approach usually pays off in the long run—plus, cleaning up any unnecessary data upfront helps reduce costs immediately. Just keep an eye on your data access patterns to ensure you're making smart choices!
Thanks for that! Setting specific time frames for transitions makes sense. I'll definitely look into cleaning up old data too.
We've had good results utilizing lifecycle rules similar to yours. Transitioning after a fixed period gives you better control over storage costs. Just be patient; the initial costs can be recouped in just a few months, plus you maintain access when needed.
Appreciate the insight! It’s definitely a balancing act between cost and management.