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We built a modern data stack from scratch and reduced our bill by 70%

jchandra.com

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Re: We built a modern data stack from scratch and reduced our bill by 70%

#11
I know it's easy to be critical, but I'm having trouble seeing the ROI on this.

This is a $20k/year savings. Perhaps, I'm not aware of the pricing in the Indian market (where this startup is), but that simply doesn't seem like a good use of time. There's an actual cost of doing these implementations. Both in hard financial dollars (salaries of the people doing the work) and the trade-offs of de prioritizing other other.

Re: We built a modern data stack from scratch and reduced our bill by 70%

#13
There is something here that doesn't sit right.

We use BQ and Metabase heavily at work. Our BQ analytics pipeline is several hundred TBs. In the beginning we had data (engineer|analyst|person) run amock and run up a BQ bill around 4,000 per month.

By far the biggest things was:-

- partition key was optional -> fix: required

- bypass the BQ caching layer -> fix: make queries use deterministic inputs [2]

It took a few weeks to go through each query using the metadata tables [1] but it worth it. In the end our BQ analysis pricing was down to something like 10 per day.

[1] https://cloud.google.com/bigquery/docs/information-schema-jo...

[2] https://cloud.google.com/bigquery/docs/cached-results#cache-...

Re: We built a modern data stack from scratch and reduced our bill by 70%

#14

I know it's easy to be critical, but I'm having trouble seeing the ROI on this. This is a $20k/year savings. Perhaps, I'm not aware of the pricing in the Indian market (where this startup is), but that simply doesn't seem like a good use of time. There's an actual cost of doing these implementations. Both in hard financial dollars (salaries of the people doing the work) and the trade-offs of de prioritizing other oth…

The biggest issue IMO is that engineers who work on projects like these inevitably get bored and move on, and then the company is stuck trying to add features, fix bugs and generally untangle the mess, all taking away time and resources from their actual product.

Re: We built a modern data stack from scratch and reduced our bill by 70%

#15

I know it's easy to be critical, but I'm having trouble seeing the ROI on this. This is a $20k/year savings. Perhaps, I'm not aware of the pricing in the Indian market (where this startup is), but that simply doesn't seem like a good use of time. There's an actual cost of doing these implementations. Both in hard financial dollars (salaries of the people doing the work) and the trade-offs of de prioritizing other oth…

>Perhaps, I'm not aware of the pricing in the Indian market

It's approximately 4 annual salaries (non dev)

Re: We built a modern data stack from scratch and reduced our bill by 70%

#16

So you saved just $20k per year? Not sure the context of your company but I’m not sure if this turns out to be a net win given the cost of engineering resources to produce this infra gain

If it's only for cost savings it's a hard sell.

But generally rolling your own has other benefits.

Re: We built a modern data stack from scratch and reduced our bill by 70%

#17
You’d think that pushing all of the data into any ldap database, but especially some of the newer postgres based ones would give you all the performance you need at 10% of the costs? Let alone all the maintenance of the mind boggling architecture drawing.

Re: We built a modern data stack from scratch and reduced our bill by 70%

#19

Is Debezium the only good CDC tool out there? I have a fairly simple data stack and am looking at integrating a CDC solution but I really dont want to touch Kafka just for this. Are there any easier alternatives?

AWS has DMS with a serverless option which is great for CDC

Re: We built a modern data stack from scratch and reduced our bill by 70%

#20
How much did this cost in engineering time and how much will it cost to maintain? How about when you need to add a new feature? Seems like you saved roughly 1.5k per month which pays for a couple days of engineering time (ignoring product,mgmt and costs related to maintaining the software)
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