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I'd be curious to know how many organizations once they get on DataDog get off of it, despite it probably easily costing $40k/mo between log ingestion/indexing,

I'd be curious to know how many organizations once they get on DataDog get off of it, despite it probably easily costing $40k/mo between log ingestion/indexing, span/trace/APM storage, monitors, etc. for smaller tech companies. Yes, you can do it all yourself open-source, invest engineer time to keep it all running. Pay for cloud infrastructure, run DataDog-like/clone UIs... There's just something about paying top dollar to get the "crem de la crem". That isn't to say that there's just a certain level of polish missing from all open-source alternatives (some of them probably even strive to be drop-in replacements/turnkey) but DataDog is a $40b company for a reason I guess? That 1-5% of polish missing from opensource is worth $40b I guess? Is that a good number to represent "what is missing in 'free' solutions versus DataDog"? 5%? Might be underselling it.

andrewstuart2 2y ago
I think the big reason they're so huge is they make it easy to onboard alllll your data, and incentivise you financially to stick with all their custom tooling and instrumentation. So the "quick wins" have a long tail of financial scaling. As your own scale grows, your DD costs grow. And so you do a few things that may entrench you further to drop your costs and the sunk cost fallacy helps corner you. You need your dashboards and alerts now that you're bigger, so you aren't thrilled about the prospect of rebuilding from scratch. Anyway, I know this because I've been there at a former employer. We started off (and mostly stayed) otel at the base layers, but more and more had to move to proprietary DD collectors/agents for off-the-shelf system metrics (db, cloud, VMs, k8s, etc), because otherwise they were custom metrics and very very expensive. So they're very very sticky. And the market loves a sticky + expensive vendor.
Spivak 2y ago
> Yes, you can do it all yourself open-source, invest engineer time to keep it all running. Pay for cloud infrastructure, run DataDog-like/clone UIs This stuff is table stakes for any competent ops person and we can spin this whole stack up in our sleep. You do it at every job. It's cheap to run and maintain as well. This isn't to say that Datadog can't be worth it but $40k/mo will get you the whole stack plus 35 hrs/wk each of a senior and junior SRE that can work on other projects. If you're swimming in cash and want the best at any price then hell yeah do it, DD is unbelievably polished. But if you're at all cost sensitive it's a bit of a catch-22 because if you have enough infrastructure to warrant DD then you likely have an ops team that can do it themselves.
- skrtskrt 2y ago
  a lot of the open source stuff has click to deploy setups in AWS & GCP too
m-o11y 2y ago
This has been a constant source of friction between build vs buy, esp. when talking about day 1 operations, which is why at OpsVerse (https://opsverse.io/ https://opsverse.io/), built out ObserveNow, a fully managed, OSS based observability platform built for enterprise scale. So you don't have to tie yourself into a walled garden, can run pretty much any exporter to bring in data to the system (or take out), and always have access to the tooling that powers your platform without needing to babysit the observability platform itself as you grow. And since it's purely ingestion based pricing, in general it works out a LOT cheaper as well. explicit disclaimer: I work at OpsVerse
skrtskrt 2y ago
Grafana has hosted cloud offerings for metrics/logs/traces and some other stuff that come in waaaaay under DataDog costs. The super-integrated UI polish type work isn't up to DataDog's level but considering it's a way cheaper option to still not have to run it yourself, it's a good option.

andrewstuart2 2y ago

I think the big reason they're so huge is they make it easy to onboard alllll your data, and incentivise you financially to stick with all their custom tooling and instrumentation. So the "quick wins" have a long tail of financial scaling. As your own scale grows, your DD costs grow. And so you do a few things that may entrench you further to drop your costs and the sunk cost fallacy helps corner you. You need your dashboards and alerts now that you're bigger, so you aren't thrilled about the prospect of rebuilding from scratch. Anyway, I know this because I've been there at a former employer. We started off (and mostly stayed) otel at the base layers, but more and more had to move to proprietary DD collectors/agents for off-the-shelf system metrics (db, cloud, VMs, k8s, etc), because otherwise they were custom metrics and very very expensive. So they're very very sticky. And the market loves a sticky + expensive vendor.

Spivak 2y ago

> Yes, you can do it all yourself open-source, invest engineer time to keep it all running. Pay for cloud infrastructure, run DataDog-like/clone UIs This stuff is table stakes for any competent ops person and we can spin this whole stack up in our sleep. You do it at every job. It's cheap to run and maintain as well. This isn't to say that Datadog can't be worth it but $40k/mo will get you the whole stack plus 35 hrs/wk each of a senior and junior SRE that can work on other projects. If you're swimming in cash and want the best at any price then hell yeah do it, DD is unbelievably polished. But if you're at all cost sensitive it's a bit of a catch-22 because if you have enough infrastructure to warrant DD then you likely have an ops team that can do it themselves.

skrtskrt 2y ago
a lot of the open source stuff has click to deploy setups in AWS & GCP too

m-o11y 2y ago

This has been a constant source of friction between build vs buy, esp. when talking about day 1 operations, which is why at OpsVerse (https://opsverse.io/ https://opsverse.io/), built out ObserveNow, a fully managed, OSS based observability platform built for enterprise scale. So you don't have to tie yourself into a walled garden, can run pretty much any exporter to bring in data to the system (or take out), and always have access to the tooling that powers your platform without needing to babysit the observability platform itself as you grow. And since it's purely ingestion based pricing, in general it works out a LOT cheaper as well. explicit disclaimer: I work at OpsVerse

skrtskrt 2y ago

Grafana has hosted cloud offerings for metrics/logs/traces and some other stuff that come in waaaaay under DataDog costs. The super-integrated UI polish type work isn't up to DataDog's level but considering it's a way cheaper option to still not have to run it yourself, it's a good option.