Datadog, Open Telemetry, & A History of Observability

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Would you say Datadog has any legacy offerings, given they were built on the cloud?

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Datadog was built on the cloud, but Datadog was built as a metrics first product. They were oriented solely around infrastructure metrics collection. Then they pivoted and said, you can have app metrics. The problem for Datadog’s users, but the way that Datadog profits is when you have application metrics that you're inputting with the same APIs that Datadog uses for infrastructure metrics. Datadog will charge their customers per combination of tags, per combination of dimensions and unique values, or cardinality per tag.

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In these services, like you said, it’s the classic, ‘land grab’. They enter with one product and up-sell and market their 130% net revenue retention number, and all investors love it.

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It’s particularly interesting, because when we see a client already uses both Datadog and New Relic, or they’re using Datadog and New Relic and Splunk, and all three of those players say, why don't you kick off the other two and let us have all your business? It yields tool sprawl; you are trying to resolve problems in three contradictory systems that you're paying each to do the full work of.

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In these services, like you said, it’s the classic, ‘land grab’. They enter with one product and up-sell and market their 130% net revenue retention number, and all investors love it.

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Even if you adopt only one or two of those tools, you end up in this problem, as they’re still destroying product suites. They have different billing models, they have different data collection models, so it's hard to necessarily reconcile that. That’s where this value proposition is of a next generation tool to come in and say, let's ditch all these assumptions about how you need to do it, from the start.

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