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Avoiding Beginner Mistakes Hampering You to Scale Backend⚡️

Riken Shah on June 14, 2024

This blog covers how I unlocked performance that allowed me to scale my backend from 50K requests → 1M requests (~16K reqs/min) on minimal resource...

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Achintya • Jun 17 • Edited

Amazing blog, can you also share the code of the backend you made.
Also, another optimization that I would have added was to use Sqlc with pgx rather than gorm as sqlc gives the performance of raw query execution with proper idomatic go models.

Riken Shah • Jun 21

Thanks, Achintya!
My next set of optimization is pushing the app beyond ~350 RPS, for which I might need to dump gorm and opt for something faster-ligher alternative like pgx.

Sorry, I cannot share the code for the backend as it is proprietary to my work.

Nadeem Ahmad • Jun 18

couldn't have worded it better !!.

Riken Shah • Jun 21

Thanks Nadeem :D

Riken Shah • Jun 21

Thanks Nadeem!

Steven Brown • Jun 17

Thanks for this blog post! A lot of good information here and I'm mostly curious around the database and data set.

How large was the initial data set you're working with or was it an empty database? At first I was thinking most operations were on a single table (incredibly simple CRUD) but when you mentioned the joins, my curiosity peaked on the DB schema.

How many tables are joined on the queries you were able to bring down to ~50ms initially?
Are those included in the ones that went back to 200-400ms?

I'm also curious on the database settings and query structure.

Do you have the fields being returned added to the index (in the correct order) to better utilize the machines memory, or would that make the index is too large?

Thanks again!

Riken Shah • Jun 21

How large was the initial data set you're working with or was it an empty database?

The CRUD operation I mentioned touches multiple tables for authentication, verification of integrity, actual operation, and post-processing tasks. Most of the tables had records < 10K but the entity on which operations were performed had ~500K records to start with and in the end it had > 1M records.

How many tables are joined on the queries you were able to bring down to ~50ms initially?

Just two but on fairly heavy tables > 500K and 100K

Are those included in the ones that went back to 200-400ms?

Yep, My suspicion for query taking 200-400ms is on the availability of open connections. As we have capped open connections to 300, the SQL driver might wait for the connection to free up. Going to sit on this to investigate the real reason, might just be slow query execution

I'm also curious on the database settings and query structure.

We are using AWS managed Postgres service AWS Aurora, we are running this on base instance db.t4g.medium - 2 CPU, 4GB Ram, 64bit Graviton

Sorry, won't be able to share the query structure as this is proprietary work.

Do you have the fields being returned added to the index (in the correct order) to better utilize the machines memory, or would that make the index is too large?

Yep, I do have, we suffer from slightly slow writes, but it is worth it as we are READ heavy app.

Great questions and Thanks for reading this, Steve!

timylv • Jun 19

Great!

Samuel Adams • Jun 19

Loved every bit of this. Well detailed and informative. Keep dropping them 🙌🏼

Riken Shah • Jun 21

Thanks Samuel, going to write more :D

Idorenyin Obong • Jun 16

good article

Riken Shah • Jun 17

Thanks, Idorenyin ❤️

Antonio | CEO at Litlyx.com • Jun 18

Really good article and value shared.

Riken Shah • Jun 21

Thanks Antonio :)

Leo Antony • Jun 15

Excellent content, very informative. I'm gonna learn Grafana after this.

Riken Shah • Jun 15

Definitely, Grafana is too good.
Thanks, Leo for the kind words :)

Marcos Silva • Jun 15

nice done! keep going on this excelent content!

Riken Shah • Jun 15

thanks marcos, happy to see you liked it :D

Harsh Agarwal • Jun 21

Thanks for the article
This was really helpful. Will try to implement some of it in our Go service as well

Riken Shah • Jun 21

Thanks Harsh, Glad you enjoyed it :D

Petra Grunheidt • Jun 18 • Edited

Total Banger 🔥🔥🔥🔥🔥
Thanks for sharing

Riken Shah • Jun 21

Thanks Peta, Glad you liked it :D

Kiran Naragund • Jun 15

Thanks for sharing this Riken Shah!
Really Helpful

Riken Shah • Jun 15

Thanks Kiran, Glad it was helpful :D

M • Jun 18

github.com/eranyanay/1m-go-websockets ;)

Riken Shah • Jun 21

Yep, I've read this article, it's one of the best. I got to know about file descriptors after reading this :D

kalyan k • Jun 17

You mentioned you have strong transaction handling in your middle ware. How is this implemented? Is this in Go? Great article btw

Riken Shah • Jun 21

Thanks for giving it a read Kalyan :D

How is this implemented? Is this in Go?
Yep, Will share this in the next article!

Nirmesh Mashru • Jun 19

Great, Thanks for sharing

Vinod Borole • Jun 17

can you share this git project so we can also contribute?

Riken Shah • Jun 21

Sorry this is proprietary work, can't share!

Tablepad • Jun 18

Good post, thanks!

Riken Shah • Jun 21

Thanks for giving it a read :D

Yudi Haryasa • Jun 25

Great writeup! 🔥 🔥 🔥

Ajay • Jun 21

Great blog! I understand the code is proprietary to your work, but could you provide a sample repository that you made? It would be helpful for reference and learning. ❤️