Nikesh Arora

Look, observability is a space, as I said, as we get more and more AI deployed, we're going to need more and more real-time capability.

Real-time capability in actions, real-time capability in applications.

Real-time capabilities require 99.99% availability, which means you have to make sure your infrastructure is always up and running.

If it has a problem, you should be able to fix it right away.

sort of similar to security.

We also have to watch security on a constant basis, make sure if something happens, we fix it right away.

So actually, over the last 10 or 15 years, if you look, there are companies who've tried to play in both spaces, and typically they've ended up really well in one side, not the other.

We've not made a foray into observability because we never thought we could build it organically.

We don't have the skillset.

But we went out looking for data pipelining.

We found Chronosphere.

Chronosphere has some of the best engineers in the space.

Observability suffers from two problems.

One, it's too expensive.

And two, it doesn't scale well.

Well, Chronosphere solved that problem.

It is two and a half times cheaper than anybody else on the market.

And two, it can scale to gigawatt size in terms of what is needed from an AI perspective.

So we think the time's right, the asset is right, and the opportunity is right.

Look, in the last seven and a half years, I'd say 30% of our opportunity has been created by strategic and timely M&A.