So, that’s the second big reason because there is that set of capabilities that is so compelling. The third, I’d say, is areas around just our openness, right? So, we are very – we’ve always had this mindset of being very open as a Company, providing our customers a lot of choice. So we are LLM-agnostic. We have excellent partnerships with all the major cloud vendors, with Azure OpenAI, with Google Vertex AI, with AWS Bedrock. You saw the recent announcement of the Strategic Collaboration Agreement with AWS around Bedrock. And we also support, you know, a lot of the open source, the community LLMs, like Llama 2 and so on from Meta. And that just means that, you know, when somebody uses us, they get a platform that gives them that choice of LLMs because we don’t believe there’s going to be one LLM to rule them all in the future.
And that choice matters to customers. And then the last thing I’d say is just the incumbency. There’s so much, when you talk about all this unstructured complex, messy data that is so critical, that’s what the customers are trying to tap into to build these generative AI applications, a lot of that data is already sitting in Elastic clusters on, you know, literally tens of thousands of customers, right. So, you know, for them it becomes the easy button. They’re able to just use our platform, use all that data that they’ve already ingested in, and now build these GenAI applications on top of it. And that, you know, that sort of makes it a very compelling proposition.
Matthew Hedberg: Super comprehensive. Thanks for that. And then I guess, you know, obviously it’s still early and the acquisition of Splunk hasn’t gone through yet. But I’m curious, you know, has there been any initial feedback from customers on what that might mean for, you know, existing Splunk customers? And I’m just sort of curious if that’s starting to show up at all in any customer conversations that you’re seeing.
Ashutosh Kulkarni: Look, I think I’ve said this many times that when it comes to the core markets in observability and security that we play in, whether it’s log analytics for observability or, you know, security analytics or SIM for security, you know, in those markets, we have very few competitors that operate at our scale. And I’m not going to talk about, you know, any one particular competitor. But what I will say is that, given that, you know, we are one of very few, you know, our ability to take share from others by having customers move to our platform consolidate onto our platform because we have a more scalable offering, you know, we are really differentiating our offering with generative AI, with the AI assistance that we have built.
And probably one of the most exciting things is the Elasticsearch Query Language, right, ESQL, the uptake and the interest in that has been just absolutely phenomenal, because not only is it easy to use, it’s this piped query language that gives them the ability to iterate over their work and it’s making it super easy for customers to migrate off of existing incumbent solutions onto Elastic. So, everything that’s happening in the market right now, we feel is really supporting our ability to continue to have a very strong future.
Matthew Hedberg: Great to hear. And also, welcome back, Anthony.
Operator: The next question is from Kash Rangan with Goldman Sachs. Please go ahead. Excuse me. The next question is from Tyler Radke with Citi. Please go ahead.
Yitchuin Wong: Hi, good afternoon. This is Yitchuin Wong on for Tyler here. Thanks for taking the question. Congrats on a great quarter. I guess I want to drill in a little bit on the top numbers. That looks really strong. Almost $40 million is like a record high. Is there a one-time factor that would cause this not to be sustainable going forward? And like kind of how we look at the contribution here? Is it more the customer consumption easing or kind of more GenAI use cases that drove that $40 million ARR Cloud revenue here?
Janesh Moorjani: Yes. Hi Yitchuin great to talk to you. And as I mentioned earlier, we saw healthy consumption from customers across geographies and across different industry segments. So, it was relatively broad-based. There was, you know, nothing stand out in terms of one or two customers that caused any kind of distortions. Overall, what I’d say is, optimization trends seem to have stabilized and while customers are still focused on making sure that they, you know, get value in terms of their investments, I think they are generally where they wanted to be in terms of those optimizations. And we – so we saw customers ramping their consumption, but in terms of GenAI, we think it’s still early days overall for GenAI workloads and it’ll take time for customers to ramp their usage for GenAI.
But we are quite pleased with the initial contribution to consumption from some of these newer GenAI workloads and we do expect that those will continue to grow over time. So, you know, as I think about the outlook on consumption, as I’ve said before, there can be some fluctuations. And as I think about the guide, what we’ve simply tried to do is balance the strength that we’ve seen in execution in the first half against potential broader macro concerns or potential consumption fluctuations that might be out there in the second half. So, we feel really good about the back half and that’s the way we’ve approached it.
Yitchuin Wong: Got it. That makes sense. I guess with kind of the GenAI still anything you can do the total, but how do you view kind of the new bookings on the consumption in the quarter on that net new of front of GenAI?
