Our renewal bill for Datadog came to –$83,000/year before we canceled

A cursory reading has not enlightened me.

I've been at many companies where they roll out Datadog and collect a crap ton of metrics/logs and so forth. Teams act all gung ho about "being data driven team" but quickly learn, almost all the numbers don't matter. As SRE, I attempt to drill down but any observations are met with silence or "Oh yea, that, meh, toss another 2 cores at the problem and let's move on."

At the cost of Datadog, their cost rarely exceeds outage cost or higher cloud bill cost. If you think you need it, buy it for a year where you can probably get good discount rate, use the data to rapidly improve most glaring issues you have then cancel the contract until you need it again in 3 years.

Obviously, if you are in highly responsive business, none of this applies but for us just cranking out B2B Rest APIs, you will be fine without Datadog.

Biggest strength is that it is user-friendly. I had very little trouble finding logs I care about, and to set up monitors + dashboards.

This is an interesting point and something I often wonder about. I think there's a number of different reasons for it, obviously markup and the need to make a profit, but one thing I realized is that when you buy something like AWS, you're often paying for the platinum version, with redundant power, networking, etc, and not the bronze version, which a lot of people would settle for. If I setup my one single instance Grafana VM or physical server, it's going to be a lot less expensive than a solution that's both multiple layers of "platinum" and multiple layers of "markup"

Datadog probably runs on the cloud, which means you get the cloud markup and datadog's mark up both built in.

And you realize you're getting a deal

The requirements of supporting the more demanding customers typically are amortized across all customers. Requirements re: security, SLA (uptime, data durability, etc.), data governance for example. It is difficult to both implement and market products that break these dimensions into tiers. You can sometimes do it for the very niche, tail of your customers (air gap regions, for example), but in a lot of products, everyone is sharing in these costs even if they only care about a subset of the capabilities.

The cost savings of scale are offset by the costs of say, needing to support Fortune 100s that need 99.99% availability even if Bob's Wordpress Page doesn't care too much about 99% vs 99.99%. You can apply that analogy to every dimension.

A homegrown solution targets specifically what your company actually cares about. It makes sense that it may be cheaper.

But again. YOU are intelligent, you are informed, you can look and see that Datadog provides a bunch of capabilities you don't need and you're paying for things you don't get benefit from and make the trade-off of building your own. Just stop telling me about it.

Making an argument that there's something abnormal about market competition and that's why prices stay high is different -- I'd read that.

The companies produce generic solutions. Because software is complex, and their customers exist in many domains with different needs and whatever.

When you can make a really focused solution, it becomes cheap.

Look at the C++ STL. How much am I using? Not much in comparison to the whole thing. I could write an implementation of std::vector in an afternoon and use it in my apps. But std::vector is like 10,000 lines long and almost impossible to read. Because it's a generic solution, like the rest of the STL.

DD provides solutions with adapters upon adapters. Using this language? Use this SDK. How about this one? Then this other SDK. Have these types of data points? Use this. Need this graph? Use this. And on and on.

But most customers are only gonna use a little bit. Okay, we'll use the ruby SDK to collect metrics. What about the other 30 SDKs because this is a generic solution? I dunno. But you're paying for them.

Moreso speaking for the companies that feel hopeless when the UIs of these open source tools might probably be ok