數據狗 (DDOG) 2024 Q3 法說會逐字稿

Good day, and thank you for standing by.

美好的一天，感謝您的支持。

Welcome to the Q3 2024 Datadog earnings conference call.

歡迎參加 2024 年第三季 Datadog 財報電話會議。

(Operator instructions) Please be advised that today's conference is being recorded.

（操作員說明）請注意，今天的會議正在錄製中。

I would now like to hand the conference over to your first speaker today, Yuka Broderick, Senior Vice President of Investor Relations.

現在我想將會議交給今天的第一位發言人，投資者關係高級副總裁尤卡·布羅德里克 (Yuka Broderick)。

Please go ahead.

請繼續。

Thank you, Liz.

謝謝你，莉茲。

Good morning, and thank you for joining us to review Datadog's third quarter 2024 financial results, which we announced in our press release issued this morning.

早安，感謝您與我們一起回顧 Datadog 的 2024 年第三季財務業績，我們在今天早上發布的新聞稿中宣布了這一結果。

Joining me on the call today are Olivier Pomel, Datadog's Co-Founder and CEO; and David Obstler, Datadog's CFO.

今天和我一起參加電話會議的是 Datadog 聯合創始人兼執行長 Olivier Pomel；以及 Datadog 的財務長 David Obstler。

During this call, we will make forward-looking statements, including statements related to our future financial performance, our outlook for the fourth quarter and fiscal year 2024 and related notes, our gross margins and operating margins, our product capabilities and our ability to capitalize on market opportunities.

在本次電話會議中，我們將做出前瞻性陳述，包括與我們未來的財務業績、第四季和2024 財年的展望及相關說明、我們的毛利率和營業利潤率、我們的產品能力和資本化能力相關的陳述關於市場機會。

The words anticipate, believe, continue, estimate, expect, intend, will and similar expressions are intended to identify forward-looking statements or similar indications of future expectations.

預期、相信、繼續、估計、期望、打算、意願和類似表達等詞語旨在識別前瞻性陳述或未來預期的類似指示。

These statements reflect our views only as of today and are subject to a variety of risks and uncertainties that could cause actual results to differ materially.

這些陳述僅反映我們截至目前為止的觀點，並受到各種風險和不確定性的影響，可能導致實際結果出現重大差異。

For a discussion of the material risks and other important factors that could affect our actual results, please refer to our Form 10-Q for the quarter ended June 30, 2024.

有關可能影響我們實際業績的重大風險和其他重要因素的討論，請參閱截至 2024 年 6 月 30 日的季度的 10-Q 表格。

Additional information will be made available in our upcoming Form 10-Q for the fiscal quarter ended September 30, 2024, and other filings with the SEC.

更多資訊將在我們即將發布的截至 2024 年 9 月 30 日的財政季度的 10-Q 表格以及向 SEC 提交的其他文件中提供。

This information is also available on the Investor Relations section of our website along with a replay of this call.

此資訊以及本次電話會議的重播也可在我們網站的投資者關係部分取得。

We will also discuss non-GAAP financial measures, which are reconciled to their most directly comparable GAAP financial measures in the tables in our earnings release, which is available at investors.datadoghq.com.

我們還將討論非 GAAP 財務指標，這些指標與我們收益報告中表格中最直接可比較的 GAAP 財務指標進行了協調，該報告可在 Investors.datadoghq.com 上取得。

With that, I'd like to turn the call over to Olivier.

說到這裡，我想把電話轉給奧利維爾。

Thanks, Yuka, and thank you all for joining us this morning.

謝謝 Yuka，也謝謝大家今天早上加入我們。

We are pleased to report on a solid Q3 as we continue to execute against our goals to help our customers grow faster, safer and more efficient as we modernize our applications.

我們很高興地報告第三季的業績，因為我們將繼續執行我們的目標，在我們實現應用程式現代化的同時，幫助我們的客戶更快、更安全、更有效率地發展。

We kept broadening our platform in observability and beyond, including in next-gen AI, where interest continues to rise, and we added new customers while expanding with existing ones as they grow into the cloud.

我們不斷擴大我們在可觀察性及其他領域的平台，包括人們對下一代人工智慧的興趣不斷上升，我們在增加新客戶的同時，隨著現有客戶向雲端的發展，不斷擴大他們的規模。

Let me start with a review of our Q3 financial performance.

讓我先回顧一下我們第三季的財務表現。

Revenue was $690 million, an increase of 26% year-over-year and above the high end of our guidance range.

營收為 6.9 億美元，年成長 26%，高於我們指導範圍的上限。

We ended the quarter with about 29,200 customers, up from about 26,800 a year ago.

本季末，我們約有 29,200 名客戶，高於一年前的約 26,800 名。

We had about 3,490 customers with ARR of $100,000 or more, up from about 3,130 a year ago, and these customers generated about 88% of our ARR.

我們約有 3,490 名客戶的 ARR 為 100,000 美元或以上，高於一年前的約 3,130 名，這些客戶產生的 ARR 約占我們的 88%。

And we generated free cash flow of $204 million with a free cash flow margin of 30%.

我們產生了 2.04 億美元的自由現金流，自由現金流利潤率為 30%。

Turning to platform adoption.

轉向平台採用。

Our platform strategy continues to resonate in the market.

我們的平台策略持續在市場上引起共鳴。

As of the end of Q3, 83% of customers were using two or more products, up from 82% a year ago. 49% of customers were using four or more products, up from 46% a year ago, 26% of our customers were using six or more products, up from 21% a year ago, and 12% of our customers were using eight or more products, up from 8% a year ago.

截至第三季末，83% 的客戶使用兩種或兩種以上產品，高於一年前的 82%。 49% 的客戶使用四種或更多產品，高於一年前的46%；26% 的客戶使用六種或更多產品，高於一年前的21%；12% 的客戶使用八種或更多產品產品，較一年前的 8% 上升。

We continue to execute on growth across the three pillars of observability.

我們繼續在可觀察性的三大支柱上實現成長。

And we are pleased to report that infrastructure monitoring, our APM suite and log management together represent more than $2.5 billion in ARR.

我們很高興地報告，基礎設施監控、我們的 APM 套件和日誌管理總共代表了超過 25 億美元的 ARR。

As a reminder, within the APM suite, we include core APM, Synthetics, Real User Monitoring and Continuous Profiler.

提醒一下，在 APM 套件中，我們包括核心 APM、合成、真實使用者監控和連續分析器。

We also want to call out our newer products, which are increasingly contributing to our business.

我們也想介紹我們的新產品，這些產品對我們的業務做出了越來越大的貢獻。

Of our 23 products, 15 now exceeded $10 million in ARR.

在我們的 23 種產品中，有 15 種產品的 ARR 現已超過 1000 萬美元。

These include (inaudible) cloud security products as well as CI Visibility and Cloud Cost Management.

其中包括（聽不清楚）雲端安全產品以及 CI 可見度和雲端成本管理。

So we have many products beginning to contribute to our revenue growth, and we're continuing to build greater capabilities within those products for our customers.

因此，我們有許多產品開始為我們的收入成長做出貢獻，並且我們將繼續為我們的客戶在這些產品中建立更強大的功能。

Now let's discuss this quarter's business drivers.

現在讓我們討論本季的業務驅動因素。

Overall, the business environment for Datadog has remained stable and similar to what we have seen throughout 2024.

整體而言，Datadog 的商業環境保持穩定，與我們在 2024 年看到的情況類似。

Our customers overall are growing their cloud usage, while some are continuing to be cost conscious.

我們的客戶整體上正在增加他們的雲端使用量，而有些客戶仍然非常注重成本。

In Q3, we continue to see existing customer usage growth broadly in line with our expectations.

在第三季度，我們繼續看到現有客戶使用量的成長與我們的預期基本一致。

Our usage growth with existing customers continued to be higher than in the year ago quarter, and we saw healthy growth across our product lines with newer products growing faster than more mature products off a smaller base.

我們現有客戶的使用量成長持續高於去年同期，我們的產品線健康成長，新產品的成長速度快於更小基數的更成熟產品。

Finally, churn continues to be low and gross revenue retention was stable in the mid to high 90s, highlighting the mission critical nature of our platform for our customers.

最後，客戶流失率持續保持在較低水平，總收入保留穩定在 90 年代中上旬，凸顯了我們平台對客戶的關鍵任務性質。

Moving on to R&D.

繼續研發。

In the next-gen AI space, customers continue to experiment with new AI technologies.

在下一代人工智慧領域，客戶不斷嘗試新的人工智慧技術。

And as they do, they want to get visibility into their AI use.

當他們這樣做時，他們希望了解他們的人工智慧使用情況。

At the end of Q3, about 3,000 customers used one or more Datadog AI integrations to send us data about their AI, machine learning and LLM usage.

截至第三季末，約 3,000 名客戶使用一個或多個 Datadog AI 整合向我們發送有關他們的 AI、機器學習和 LLM 使用的資料。

As some of these experiments start turning into production AI applications, we are seeing initial signs of traction for our LLM observability products.

隨著其中一些實驗開始轉化為人工智慧應用程序，我們看到了法學碩士可觀察性產品受到關注的初步跡象。

Today, hundreds of customers are using LLM observability with more exploring it every day.

如今，數百名客戶正在使用 LLM 可觀察性，並且每天都有更多客戶對其進行探索。

And some of our first paying customers have told us that they have cut the time spent investigating LLM latency, errors and quality from days or hours to just minutes.

我們的一些首批付費客戶告訴我們，他們將調查 LLM 延遲、錯誤和品質的時間從幾天或幾小時縮短到幾分鐘。

Our customers not only want to understand the performance and cost of their LLM applications.

我們的客戶不僅想了解其法學碩士申請的性能和成本。

They also want to understand the LLM model performance within the context of their entire application.

他們也希望了解 LLM 模型在整個申請背景下的表現。

So they are using APM alongside LLM observability to get fully integrated end-to-end visibility across all their applications and tech stacks.

因此，他們將 APM 與 LLM 可觀察性結合使用，以在所有應用程式和技術堆疊中獲得完全整合的端到端可見性。

Meanwhile, we continue to work to make the Datadog platform the best place for customers to monitor, secure and take action on their systems no matter where they deploy.

同時，我們繼續努力使 Datadog 平台成為客戶監控、保護其係統並對其採取行動的最佳場所，無論其係統部署在何處。

In September, we launched Datadog monitoring for Oracle cloud infrastructure for general availability.

9 月，我們推出了針對 Oracle 雲端基礎架構的 Datadog 監控，以實現全面可用性。

With this launch, our customers gain visibility into their OCI stack and they can manage in real time the performance of OCI cloud services, servers, VMs, databases, containers and apps in Datadog.

透過此次發布，我們的客戶可以了解他們的 OCI 堆疊，並且可以在 Datadog 中即時管理 OCI 雲端服務、伺服器、虛擬機器、資料庫、容器和應用程式的效能。

And customers can now unify their monitoring across OCI, other clouds and on-prem environments.

客戶現在可以跨 OCI、其他雲端和本地環境統一監控。

We also continue to extend our platform in new ways to bring value to our customers.

我們也繼續以新的方式擴展我們的平台，為我們的客戶帶來價值。

At our DASH User Conference this summer, we announced Datadog OnCall, our newest product in the cloud service management space.

在今年夏天的 DASH 用戶大會上，我們發布了 Datadog OnCall，這是我們在雲端服務管理領域的最新產品。

As you know, our customers use Datadog extensively during their workdays for alerting and troubleshooting, whether that's for observability or security use cases.

如您所知，我們的客戶在工作日廣泛使用 Datadog 進行警報和故障排除，無論是用於可觀察性還是安全用例。

Now with Datadog OnCall, we are bringing a modern paging experience directly into our unified platform, and we now offer a completely integrated solution that covers incidents from end-to-end from detection, alerting and paging to incident management, troubleshooting and resolution.

現在，透過Datadog OnCall，我們將現代尋呼體驗直接引入我們的統一平台，並且我們現在提供完全整合的解決方案，涵蓋從檢測、警報和尋呼到事件管理、故障排除和解決的端到端事件。

Even though OnCall is still in limited availability, we are already seeing very strong reception for the product, and we are beginning to see customers request OnCall as part of their deals.

儘管 OnCall 的供應量仍然有限，但我們已經看到該產品的反應非常強烈，我們開始看到客戶要求將 OnCall 作為其交易的一部分。

In particular, new customers are interested in including paging as part of their land with Datadog.

特別是，新客戶有興趣將尋呼納入其 Datadog 土地的一部分。

So we're working hard to deepen and broaden our platform.

因此，我們正在努力深化和拓寬我們的平台。

And our innovations are rightfully being recognized by independent research firms.

我們的創新理所當然地得到了獨立研究公司的認可。

We are pleased to see that for the fourth year in a row, Datadog has been named a leader in the 2024 Gartner Magic Quadrant for Observability Platforms.

我們很高興看到 Datadog 連續第四年被評為 2024 年 Gartner 可觀察性平台魔力像限的領導者。

We believe that this validates our approach to deliver a unified platform, which breaks down silos across teams.

我們相信，這驗證了我們提供統一平台的方法，該平台打破了團隊之間的孤島。

And Datadog has also been named a leader in Gartner's very first Magic Quadrant for Digital Experience Monitoring, which includes Datadog's products across synthetic testing, real user monitoring, product analytics, session replay and error tracking.

Datadog 也被 Gartner 首個數位體驗監控魔力像限評為領導者，該象限包括 Datadog 的綜合測試、真實用戶監控、產品分析、會話重播和錯誤追蹤產品。

Now let's move on to sales and marketing.

現在讓我們繼續進行銷售和行銷。

Our sales team continued to execute this quarter, and we added some exciting new customers while expanding with many more.

我們的銷售團隊本季繼續執行任務，我們增加了一些令人興奮的新客戶，同時擴大了更多客戶。

So let's go through a few examples.

讓我們來看幾個例子。

First, we landed a seven figure annualized deal with a leading e-commerce company in India.

首先，我們與印度一家領先的電子商務公司達成了七位數的年化交易。

With its previous observability vendor, the customer saw quickly increasing costs while lacking the enterprise grade observability they needed.

對於先前的可觀測性供應商，客戶發現成本迅速增加，同時缺乏所需的企業級可觀測性。

By switching to Datadog, they expect to support their scaling goals and will rely for that on our tracing, granular profiling and cloud integration support.

透過切換到 Datadog，他們希望支援其擴展目標，並將依賴我們的追蹤、精細分析和雲端整合支援。

I will note that we are pleased to have landed a large new logo customer in India, and we are continuing to invest to grow our presence and our opportunities there.

我要指出的是，我們很高興在印度找到了一個大型新徽標客戶，我們將繼續投資以擴大我們在印度的業務和機會。

Next, we signed a six figure annualized land with a major US Federal Agency.

接下來，我們與美國主要聯邦機構簽署了年化六位數的土地。

This agency is beginning to move some of its workloads to the cloud and is expanding the services offers to every single US citizen through cloud applications.

該機構開始將部分工作負載轉移到雲端，並透過雲端應用程式向每位美國公民提供服務。

They have chosen Datadog to observe and secure their cloud environment and deliver a faster, better experience to end users.

他們選擇 Datadog 來觀察和保護其雲端環境，並為最終用戶提供更快、更好的體驗。

This deal includes eight products on Datadog GovCloud, including Cloud SIEM and cloud security management.

該交易包括 Datadog GovCloud 上的八個產品，包括雲端 SIEM 和雲端安全管理。

Next, we landed a seven figure annualized deal with a large American financial services company.

接下來，我們與一家大型美國金融服務公司達成了年化七位數的交易。

This customer has a very seasonal business and experiences dozens of major incidents during the annual peak season with an average downtime per incident of about 5 hours.

該客戶的業務季節性很強，每年旺季都會發生數十起重大事故，平均每次事故停機時間約5小時。

And they estimate millions of dollars of lost revenue for each hour of downtime.

他們估計，每一小時的停機都會造成數百萬美元的收入損失。

By replacing its cloud providers monitoring tool with Datadog and in particular, using our Real User Monitoring product, this customer targets substantial reductions in downtime.

透過以 Datadog 取代其雲端供應商監控工具，特別是使用我們的真實用戶監控產品，該客戶的目標是大幅減少停機時間。

They are starting with five Datadog products and are trialing our network monitoring, database monitoring, cloud security and cloud cost management products as they look to consolidate dozens of homegrown commercial tools.

他們從五種 Datadog 產品開始，並正在試用我們的網路監控、資料庫監控、雲端安全和雲端成本管理產品，因為他們希望整合數十種本土商業工具。

Next, we landed a seven figure annualized expansion with a major airline in Europe.

接下來，我們與歐洲一家主要航空公司實現了七位數的年增長率。

This customer has adopted Datadog for its customer-facing websites.

該客戶已在其面向客戶的網站中採用了 Datadog。

They are now moving hundreds of applications from on-prem to AWS, and they want to derisk their cloud migration.

他們現在正在將數百個應用程式從本地遷移到 AWS，並且希望降低雲端遷移的風險。

They estimate that each incident can cost tens of millions of dollars in lost revenue and customer impact.

他們估計，每次事件都會造成數千萬美元的收入損失和客戶影響。

By using Datadog across five products, this customer expects to significantly improve mean time to resolution, and they have already seen progress in that respect during their evaluation period with Datadog.

透過在五種產品中使用 Datadog，該客戶希望顯著縮短平均解決時間，並且他們在使用 Datadog 的評估期間已經看到了這方面的進展。

Next, we signed a seven figure annualized expansion with a division of a hyperscaler delivering next-gen AI models.

接下來，我們與一家提供下一代人工智慧模型的超大規模公司的一個部門簽署了七位數的年度擴張協議。

This customer is very technically capable and already has a homegrown observability solution, which requires time-consuming customization and manual configuration.

該客戶技術能力很強，已經擁有自己開發的可觀測性解決方案，需要耗時的客製化和手動配置。

They will be launching new features for their large language models soon and need a platform that can scale flexibly while supporting proactive incident detection.

他們很快就會為其大型語言模型推出新功能，並且需要一個可以靈活擴展同時支援主動事件偵測的平台。

By expanding the use of Datadog, they expect to efficiently onboard new teams and environments and support the rapidly increasing adoption of the LLMs.

透過擴大 Datadog 的使用，他們希望能夠有效地加入新的團隊和環境，並支持法學碩士的快速採用。

Next and last, we signed a seven figure annualized expansion with a leading online food delivery company in Latin America.

接下來也是最後一個，我們與拉丁美洲一家領先的線上食品配送公司簽署了七位數的年度擴張協議。

Before Datadog, this customer suffered from excessive alerting noise, siloed teams and lack of visibility with each minute of downtime resulting in thousands of lost orders.

在使用 Datadog 之前，該客戶遭受過多的警報噪音、孤立的團隊以及每分鐘停機時間缺乏可見性的困擾，導致數千個訂單遺失。

By using Datadog, this customer has experienced meaningful reductions in mean time to resolution and false alerts while saving on hard costs in the Kubernetes environment.

透過使用 Datadog，該客戶顯著縮短了平均解決時間和錯誤警報，同時節省了 Kubernetes 環境中的硬成本。

This customer is expanding to 10 products in the Datadog platform.

該客戶正在將 Datadog 平台中的產品擴展到 10 種。

And that is it for another productive quarter from our go-to-market team.

這就是我們的市場推廣團隊又一個有生產力的季度。

Now, let me say a few words on our longer-term outlook.

現在，讓我談談我們的長期前景。

Overall, we continue to see no change to the multiyear trend towards digital transformation and cloud migration, which we continue to believe are still in early days.

總體而言，我們仍然認為數位轉型和雲端遷移的多年趨勢沒有變化，我們仍然認為這仍處於早期階段。

We are seeing continued experimentation with new advances such as next-gen AI, and we believe this is one of the many factors that will drive greater use of the cloud and other modern technologies.

我們看到下一代人工智慧等新進步的不斷實驗，我們相信這是推動雲端和其他現代技術更多使用的眾多因素之一。

So we are helping our customers every day to observe, secure and act on their business-critical applications and workloads.

因此，我們每天都在幫助客戶觀察、保護他們的關鍵業務應用程式和工作負載並採取行動。

With that, I will turn it over to our CFO.

這樣，我會將其移交給我們的財務長。

David?

大衛？

Thanks, Olivier, and good morning.

謝謝，奧利維爾，早安。

Q3 revenue was $690 million, up 26% year-over-year and up 7% quarter-over-quarter.

第三季營收為 6.9 億美元，年增 26%，季增 7%。

To dive into some of the drivers of our Q3 revenue growth.

深入探討第三季營收成長的一些驅動因素。

Overall, we saw trends for usage growth from existing customers that were consistent with our expectation.

整體而言，我們看到現有客戶的使用成長趨勢與我們的預期一致。

We've seen conditions remain roughly stable throughout 2024, with continued movement to cloud and modern DevOp technologies and with customers remaining cost conscious and seeking efficiency and value from their spend.

我們看到，隨著雲端和現代 DevOp 技術的持續發展，以及客戶保持成本意識並從支出中尋求效率和價值，整個 2024 年情況基本上保持穩定。

In Q3, we saw usage growth from existing customers that was higher than usage growth in the year ago quarter as well as higher than usage growth in the prior quarter.

在第三季度，我們看到現有客戶的使用量成長高於去年同期的使用量成長，也高於上一季的使用量成長。

Now some of our growth is coming from AI native customers who this quarter represented more than 6% of our Q3 ARR, up from more than 4% in Q2 and about 2.5% of our ARR in the year ago quarter.

現在，我們的部分成長來自人工智慧原生客戶，他們本季占我們第三季 ARR 的 6% 以上，高於第二季的 4% 以上和去年同期的 2.5% 左右。

AI native customers contributed about 4 percentage points of year-over-year growth in Q3 versus about 2 percentage points in the year ago quarter.

AI 原生客戶對第三季年成長的貢獻約為 4 個百分點，而去年同期約為 2 個百分點。

While we believe that adoption of AI will continue to benefit Datadog in the long term, we are mindful that some of the large customers in this cohort have ramped extremely rapidly, and that these customers may optimize cloud and observability usage and increase their commitments to us over time with better terms.

雖然我們相信，從長遠來看，人工智慧的採用將繼續使Datadog 受益，但我們注意到，該群體中的一些大客戶成長極其迅速，這些客戶可能會優化雲端和可觀測性的使用，並增加他們對我們的承諾隨著時間的推移，條件會更好。

This may create volatility in our revenue growth in future quarters on the backdrop of long-term volume growth.

在長期銷售成長的背景下，這可能會導致我們未來幾季的營收成長出現波動。

Now regarding usage growth by customer size in Q3, similar to the last quarter, we saw the strongest performance among our largest customers who spent multiple millions of dollars with us annually.

現在，就第三季客戶規模的使用成長而言，與上個季度類似，我們看到最大的客戶表現最為強勁，他們每年在我們這裡花費數百萬美元。

And as we look at usage growth by segment, similar to recent quarters, we are seeing the strongest growth from our enterprise customers, where year-over-year growth in usage has accelerated over the past several quarters.

當我們按細分市場查看使用量成長時，與最近幾季類似，我們發現企業客戶​​的成長最為強勁，在過去幾個季度中，企業客戶的使用量同比增長有所加快。

Meanwhile, our SMB customers remain solid with year-over-year growth similar to the past several quarters.

同時，我們的中小企業客戶保持穩定，年成長與過去幾季類似。

As a reminder, we define enterprise customers as our clients with 5,000 employees or more, mid-market customers with 1,000 to 5,000 employees and SMB customers as those companies with less than 1,000 employees.

需要提醒的是，我們將企業客戶定義為擁有 5,000 名或以上員工的客戶，將中端市場客戶定義為擁有 1,000 至 5,000 名員工的客戶，將中小企業客戶定義為員工少於 1,000 名的公司。

Regarding our retention metrics, our net revenue retention percentage was in the mid-110s in Q3 with continued improvement from last quarter.

關於我們的保留指標，第三季我們的淨收入保留百分比在 110 左右，較上季度持續改善。

This is a trailing 12 month measure.

這是過去 12 個月的指標。

Meanwhile, we've continued to see an increase in recent quarters as we look at the NRR quarterly trend.

同時，當我們觀察 NRR 季度趨勢時，我們繼續看到最近幾季的成長。

And finally, our trailing 12 month gross revenue retention percentage remains stable in the mid to high 90s.

最後，我們過去 12 個月的總收入保留率保持穩定在 90 多歲左右。

Now moving on to our financial results.

現在轉向我們的財務表現。

First, billings were $689 million, up 14% year-over-year.

首先，營收為 6.89 億美元，年增 14%。

Billings duration decreased slightly year-over-year.

比林斯持續時間較去年同期略有下降。

Pro forma for changes in billing timing and the slight change in duration, billings growth would have been in the mid-20s percent range.

預計計費時間的變化和持續時間的輕微變化，計費成長將在 20% 左右。

Our billings and billings growth can be volatile on a quarterly basis depending on the timing of our deals.

根據我們的交易時間，我們的帳單和帳單成長可能會按季度波動。

Our 12 month trailing billing growth is similar to our trailing 12 month revenue growth with both in the mid 20s percent.

我們過去 12 個月的帳單成長與過去 12 個月的營收成長類似，兩者都在 20% 左右。

Remaining performance obligations, or RPO, was $1.82 billion, up 26% year-over-year.

剩餘履約義務（RPO）為 18.2 億美元，年增 26%。

And current RPO growth was in the high 20s percent year-over-year.

目前的 RPO 年成長率高達 20% 左右。

RPO duration was down slightly year-over-year.

RPO 持續時間較去年同期略有下降。

Normalizing for duration, RPO growth would have been in the high 30s percent year-over-year.

如果持續時間正常化，RPO 年成長率將高達 30% 左右。

We continue to believe that revenue is a better indicator of our business trends than billing and RPO as those fluctuate on a quarterly basis relative to revenue based on the timing of invoicing and the duration of customer contracts.

我們仍然認為，收入比計費和 RPO 更能反映我們的業務趨勢，因為收入會根據開票時間和客戶合約期限而按季度相對於收入波動。

Now let's review some key income statement results.

現在讓我們回顧一些重要的損益表結果。

Unless otherwise noted, all metrics are non-GAAP.

除非另有說明，所有指標均為非公認會計準則。

We have provided a reconciliation of GAAP to non-GAAP financials in our earnings release.

我們在收益報告中提供了 GAAP 與非 GAAP 財務數據的調整表。

First, gross profit in the quarter was $560 million, representing a gross margin of 81.1%.

首先，該季毛利為5.6億美元，毛利率為81.1%。

This compares to a gross margin of 82.1% last quarter and 82.3% in the year ago quarter.

相較之下，上季毛利率為 82.1%，去年同期毛利率為 82.3%。

Our Q3 OpEx grew 21% year-over-year, the same growth as last quarter, though it would have been represented an acceleration from last quarter, excluding the impact of our DASH User Conference in Q2.

我們第三季的營運支出年增 21%，與上季成長相同，儘管不包括第二季 DASH 用戶大會的影響，但與上季相比有所加速。

As we said before, we are investing in headcount in 2024, and the acceleration in OpEx reflects our execution on our hiring in sales and marketing and R&D so far this year.

正如我們之前所說，我們將在 2024 年對員工進行投資，營運支出的加速反映了我們今年迄今為止在銷售、行銷和研發方面的招募執行情況。

Q3 operating income was $173 million or a 25% margin compared to 24% last quarter and 24% in the year ago quarter.

第三季營業收入為 1.73 億美元，利潤率為 25%，而上季為 24%，去年同期為 24%。

Turning to the balance sheet and cash flow statements.

轉向資產負債表和現金流量表。

We ended the quarter with $3.2 billion in cash, cash equivalents and marketable securities.

本季結束時，我們擁有 32 億美元的現金、現金等價物和有價證券。

Cash flow from operations was $229 million in the quarter.

該季度營運現金流為 2.29 億美元。

And after taking into consideration capital expenditures and capitalized software, free cash flow was $204 million for a free cash flow margin of 30%.

考慮到資本支出和資本化軟體後，自由現金流為 2.04 億美元，自由現金流利潤率為 30%。

Now for our outlook for the fourth quarter and for fiscal 2024.

現在我們對第四季和 2024 財年的展望。

First, our guidance philosophy remains unchanged.

首先，我們的指導思想並沒有改變。

As a reminder, we base our guidance on trends observed in recent quarters and apply conservatism on these growth trends.

提醒一下，我們的指導是基於最近幾季觀察到的趨勢，並對這些成長趨勢採取保守態度。

For the fourth quarter, we expect revenue to be in the range of $709 million to $713 million, which represents a 20% to 21% year-over-year growth rate.

我們預計第四季營收將在 7.09 億美元至 7.13 億美元之間，年成長率為 20% 至 21%。

Non-GAAP operating income is expected to be in the range of $163 million to $167 million, which implies an operating margin of 23% and non-GAAP net income per share is expected to be $0.42 to $0.44 per share based on approximately 361 million weighted average diluted shares outstanding.

非 GAAP 營業收入預計在 1.63 億美元至 1.67 億美元之間，這意味著營業利潤率為 23%，根據約 3.61 億美元加權，非 GAAP 每股淨利潤預計為 0.42 美元至 0.44 美元。已發行股份。

And for the full fiscal year 2024, we expect revenue to be in the range of $2.656 billion to $2.660 billion, which represents 25% year-over-year growth.

對於 2024 年整個財年，我們預計營收將在 26.56 億美元至 26.60 億美元之間，年增 25%。

Non-GAAP operating income is expected to be in the range of $658 million to $662 million, which implies an operating margin of 25% and non-GAAP net income per share is expected to be in the range of $1.75 to $1.77 per share based on approximately 359 million weighted average diluted shares.

非 GAAP 營業收入預計在 6.58 億美元至 6.62 億美元之間，這意味著營業利潤率為 25%，非 GAAP 每股淨利潤預計在 1.75 美元至 1.77 美元之間。 。

Now finally, some additional notes on guidance.

最後，關於指導的一些附加說明。

We expect net interest and other income for the fiscal year 2024 to be approximately $140 million.

我們預計 2024 財年的淨利息和其他收入約為 1.4 億美元。

Next, we expect cash taxes in 2024 to be in the $20 million to $25 million range, and we continue to apply a 21% non-GAAP tax rate for 2024 and going forward.

接下來，我們預計 2024 年的現金稅將在 2,000 萬美元至 2,500 萬美元的範圍內，並且我們將在 2024 年及以後繼續採用 21% 的非 GAAP 稅率。

Finally, we expect capital expenditures and capitalized software together to be in the 3% to 4% of revenue range for fiscal 2024.

最後，我們預計 2024 財年資本支出和資本化軟體合計將佔營收的 3% 至 4%。

Now to conclude, we are continuing to execute on our strategy, investing in our innovation and expanding our platform to deliver more value to our customers.

現在總而言之，我們將繼續執行我們的策略，投資我們的創新並擴展我們的平台，以為我們的客戶提供更多價值。

And lastly, I want to thank all Datadogs worldwide for their efforts as we close out 2024.

最後，我要感謝全球所有 Datadog 在 2024 年即將結束之際所做的努力。

And with that, we'll open the call for questions.

接下來，我們將開始提問。

Operator, let's begin the Q&A.

接線員，我們開始問答。

(Operator instructions)

（操作員說明）

Mark Murphy, JPMorgan.

馬克墨菲，摩根大通。

Thank you very much and congrats on another very healthy performance.

非常感謝，並祝賀您又取得了非常健康的表現。

Olivier, we noticed your AI contributions surged to about 6% this quarter.

Olivier，我們注意到您本季的 AI 貢獻飆升至 6% 左右。

We're watching all the advances in the foundation models, including the OpenAI's strawberry version.

我們正在關注基礎模型的所有進步，包括 OpenAI 的草莓版本。

We're watching the multistep reasoning, how they're becoming multimodal, the longer duration inference and video models.

我們正在觀察多步驟推理，它們如何變得多模態，持續時間更長的推理和視訊模型。

Does it seem reasonable to you that we are on the cusp of a pretty interesting period in the next couple of years for the inferencing loads and that might drive some incremental traction for Datadog that is tied to AI?

在您看來，我們正處於未來幾年推理負載非常有趣的時期的風口浪尖，這可能會為與人工智慧相關的 Datadog 帶來一些增量牽引力，這是否合理？

And then I have a quick follow-up for David.

然後我對大衛進行了快速跟進。

I mean, look, it's definitely a very interesting period to say the least.

我的意思是，看，至少可以說這絕對是一個非常有趣的時期。

We see tons of innovation across our customer base, still largely more around experimenting and testing new applications.

我們在客戶群中看到了大量的創新，其中更多的是圍繞著試驗和測試新應用程式進行的。

So as we reported, we are seeing some customers moving to production, and we are seeing our production-minded LLM observability products, for example, being used by real paying customers with real volumes and real applications in real production workloads.

因此，正如我們所報導的，我們看到一些客戶轉向生產，並且我們看到我們注重生產的LLM 可觀察性產品，例如，被真正的付費客戶在實際生產工作負載中使用，具有真實的數量和真實的應用程式。

So that's exciting and healthy.

所以這是令人興奮和健康的。

I think it's a great trend for the future.

我認為這是未來的一個偉大趨勢。

In general, in terms of the workloads, you're right that we're starting to see more inference workloads, but they still tend to be more concentrated across a number of API driven providers.

總的來說，就工作負載而言，我們開始看到更多的推理工作負載，這是正確的，但它們仍然傾向於更集中在許多 API 驅動的提供者中。

So there are a few others, both on LLMs and other kinds of models.

所以還有其他一些，無論是法學碩士還是其他類型的模型。

So this is where I think most of the usage in production at least is today.

所以我認為這至少是目前生產中大部分使用的地方。

We expect that to diversify more over time as companies get further into production with their applications and they start to be customizing more on their models.

我們預計，隨著公司進一步將其應用程式投入生產，並且他們開始對模型進行更多定制，這種情況將隨著時間的推移而更加多樣化。

Okay.

好的。

Understood.

明白了。

And then, David, to the extent, and you've always said that revenue is a better indicator than billings and RPO.

然後，大衛，在某種程度上，您總是說收入是比帳單和 RPO 更好的指標。

But to the extent the billings growth was affected by timing, as you mentioned, we've seen that before.

但正如您所提到的，就帳單成長受到時間影響的程度而言，我們之前已經看到過這種情況。

We know it can bounce around.

我們知道它可以反彈。

But did you have some invoices that would have gone out in September and instead, they were issued in October?

但是您是否有一些發票本應在 9 月發出，但實際上是在 10 月開立的？

In other words, would we see some recapture of the timing element in Q4 or perhaps in early next year?

換句話說，我們會在第四季或明年初看到一些時間元素的重新出現嗎？

Or is it some other dynamic there?

或是還有其他的動態嗎？

Yes, it's really some other dynamic.

是的，這確實是其他一些動態。

It's that the timing of billing for last year was slightly different than for this year.

去年的計費時間與今年略有不同。

And so it was more a factor of timing for billing last year that didn't repeat this year.

因此，這更多是去年計費時間的因素，今年沒有重複。

So we think that the weighted average, what we talked about, the average over the 12 months is a better indicator of the relationship between billing and revenues and when you look at that, they're much more closely aligned.

因此，我們認為加權平均值，也就是我們所說的 12 個月的平均值，可以更好地反映計費和收入之間的關係，當你觀察這一點時，它們的一致性要緊密得多。

Excellent.

出色的。

Thank you again.

再次感謝您。

Thank you.

謝謝。

Sanjit Singh, Morgan Stanley.

桑吉特辛格，摩根士丹利。

Yes, thank you for taking the questions.

是的，感謝您提出問題。

Olivier, in the framework that you sort of laid out for the business, Observe, Secure and Act, I wanted to focus on the last two pillars, Secure and Act.

Olivier，在您為業務制定的框架「觀察、安全和行動」中，我想專注於最後兩個支柱：「安全」和「行動」。

When we think about how the security, cloud security, sales motion has been going this quarter versus prior quarters.

當我們考慮本季的安全、雲端安全、銷售活動與前幾季的進度時。

Any trend lines there?

有趨勢線嗎？

And any sort of early indications on the uptake of some of the service management products and more of the automation features within the Datadog platform?

關於 Datadog 平台中某些服務管理產品和更多自動化功能的採用，有什麼早期跡象嗎？

Yes.

是的。

So on the security side, I think we, there's quite a bit of focus right now on the cloud SIEM as we see a number of very exciting opportunities there.

因此，在安全方面，我認為我們現在非常關注雲端 SIEM，因為我們在那裡看到了許多非常令人興奮的機會。

I think when you look at the landscape with competitively what other companies are using, because most companies have a SIEM already at least for some part of their business, I think there's a very interesting opportunity for us there.

我認為，當你看看其他公司正在使用的競爭格局時，因為大多數公司至少在其業務的某些部分已經擁有 SIEM，我認為這對我們來說是一個非常有趣的機會。

And the product is mature enough to win in best of breed situations across the existing products.

而且該產品已經足夠成熟，可以在現有產品中脫穎而出。

So we are making quite a bit of a push.

所以我們正在大力推動。

And you know we're still investing quite a bit in the rest of the platform and bringing all the products together to be a unified platform for security.

您知道，我們仍在該平台的其餘部分進行大量投資，並將所有產品整合在一起成為一個統一的安全平台。

But I would say the tip of the spear for this quarter and next is slightly, I think there's a very specific opportunity there.

但我想說，本季和下一個季度的矛尖略有上升，我認為那裡有一個非常具體的機會。

On the, and we also have a few other products security that are coming online soon that we haven't brought to (inaudible) yet, but that we think can make a big difference.

此外，我們還有一些其他產品安全性即將上線，我們尚未推出（聽不清楚），但我們認為可以產生很大的影響。

In the service management, we actually see very exciting trends from customers.

在服務管理中，我們實際上從客戶那裡看到了非常令人興奮的趨勢。

We mentioned on the call, our OnCall product, which puts us directly to the paging loop and the start of many incidents.

我們在電話中提到了我們的 OnCall 產品，它使我們直接進入尋呼循環和許多事件的開始。

The product is getting stronger reception than we initially thought to the point where customers are basically clamoring to buy even though it's still in preview.

該產品的受歡迎程度比我們最初想像的要強烈，以至於客戶基本上都在吵著要購買，儘管它仍處於預覽階段。

So we feel good about handling the full loop for them, starting with when we detect something in observability, all the way to full incident resolution and automation as a big part of it.

因此，我們對為他們處理整個循環感到滿意，從我們在可觀察性中檢測到某些東西開始，一直到完整的事件解決和自動化作為其中的重要組成部分。

So we think OnCall can be a bit of a watershed for us to do quite a bit more on that.

因此，我們認為 OnCall 可能是我們在這方面做更多事情的分水嶺。

So we're also excited, and we're doing what we can to accelerate the road map there because we think there's a very good opportunity.

所以我們也很興奮，我們正在盡我們所能加速那裡的路線圖，因為我們認為這是一個非常好的機會。

We have a few other building blocks on the service management that we released over the past year.

我們在過去的一年中發布了一些關於服務管理的其他建置模組。

And they're all growing quite nicely,

而且都長得很好

I would say, from a small basis today, but we're very excited in the way they all come together to form an integrated platform where we can fully automate resolution for our customers.

我想說的是，從今天的一個小基礎開始，但我們對它們聚集在一起形成一個整合平台感到非常興奮，在這個平台上我們可以為我們的客戶完全自動化解決方案。

So that's, again, still something we're building largely from those building blocks, but something that we think is going to be very exciting in the quarters and years to come.

因此，這仍然是我們主要從這些構建模組中構建的東西，但我們認為在未來幾個季度和幾年內將非常令人興奮。

That's great to hear.

很高興聽到這個消息。

And sort of one follow-up going to sort of the spending intentions from your customers.

一種後續行動是將客戶的消費意圖分類。

It feels like most of the past 12 to 18 months, the sales playbook, particularly in the enterprise has been around consolidation.

感覺過去 12 到 18 個月的大部分時間裡，銷售策略（尤其是企業的銷售策略）一直圍繞著整合。

Is that still the theme in terms of driving new bookings, new expansion deals?

這仍然是推動新預訂、新擴張交易的主題嗎？

Or are you starting to see customers focus more, less about the consolidation opportunity and more about innovation and bringing their innovation budgets to bear to invest in AI and cloud and bringing on Datadog along for the ride?

或者您是否開始看到客戶更專注於創新，而不是整合機會，並將他們的創新預算用於投資人工智慧和雲端，並引入 Datadog？

There's always been innovation and new things.

總是有創新和新事物。

You're right that at least for the deals we talk about in the earnings, there tends to be more consolidation, but that's the nature of it.

你是對的，至少對於我們在收益中討論的交易來說，往往會出現更多的整合，但這就是它的本質。

I mean innovation typically happens gradually as opposed to being a big bang customers switching $5 million from five vendors into another vendor.

我的意思是，創新通常是逐漸發生的，而不是客戶將 500 萬美元從五個供應商轉移到另一個供應商的大爆炸。

So we talk about these less in those earnings calls, but that's been happening throughout.

因此，我們在財報電話會議中較少談論這些問題，但這種情況一直在發生。

We definitely see room for a lot more consolidation moving forward, both in terms of existing customers and new logos.

我們確實看到了進一步整合的空間，無論是在現有客戶還是新標誌方面。

And at the same time, we are excited to see what's happening with the AI innovation as it gets further down the pipe and away from testing and experimenting and more into production applications.

同時，我們很高興看到人工智慧創新正在發生什麼，因為它進一步遠離測試和實驗，更多地進入生產應用。

And we have some signs that it's starting to happen.

我們有一些跡象表明它正在開始發生。

Again, we see that with our LLM observability product.

我們再次透過我們的法學碩士可觀察性產品看到了這一點。

We see that also with some of the workloads we monitor from our customers on the infrastructure side.

我們在基礎設施方面監控客戶的一些工作負載時也發現了這一點。

But I would say it's still very early days in terms of customers being in production with their next-gen AI applications.

但我想說，就客戶使用下一代人工智慧應用程式進行生產而言，現在還處於早期階段。

Great.

偉大的。

Thank you for the

謝謝你的

(inaudible)

（聽不清楚）

Raimo Lenschow, Barclays.

雷莫‧倫肖 (Raimo Lenshow)，巴克萊銀行。

Thank you and congrats from me as well.

謝謝你，也恭喜我。

Can I stay on that subject a little bit longer, Olivier?

我可以在這個話題上多聊一會兒嗎，奧利維爾？

The, if you think about it, the one big driver for you guys in the past was workload growth, and that's something that we're kind of all watching out for the hyperscalers as well, but it looks like there are stable trends at the hyperscalers and for you as well.

如果你想一想，過去對你們來說的一個重要驅動因素是工作負載的成長，這也是我們對超大規模企業所關注的事情，但看起來在這個領域有穩定的趨勢。適合您。

Like if you think about the puts and takes there to think that, that's changing, like how much of that is just plain vanilla macro?

就像如果你考慮一下看跌期權和看跌期權，你會認為情況正在發生變化，例如其中有多少只是普通的宏觀？

And how much of that is like taking project resources away, not so much money, but also time for kind of AI, and it's obviously like, as you said, early in its life cycle.

其中有多少就像拿走了專案資源，不是那麼多錢，而是人工智慧的時間，正如你所說，這顯然是在其生命週期的早期。

Can you just, how do you see that playing out?

您能看一下結果如何嗎？

Because that's the one thing we're all watching out.

因為這是我們都在關注的一件事。

Thank you.

謝謝。

Yes.

是的。

I mean, look, the key thing to remind everyone of is, we think the general move of workload growth in the cloud or cloud environment, it might be public cloud-based, but they might also be private cloud.

我的意思是，要提醒大家的關鍵是，我們認為雲端或雲端環境中工作負載成長的整體趨勢可能是基於公有雲的，但也可能是私有雲的。

So this growth and move to the cloud is going to last for a very long time and it's going to be at a high, fairly high level for a very long time.

因此，這種成長和向雲端的遷移將持續很長一段時間，並且將在很長一段時間內處於很高、相當高的水平。

So you're right that when we look at the numbers from the hyperscalers and when we try to factor out what's GPU driven, the growth looks stable-ish.

所以你是對的，當我們查看超大規模提供者的資料並嘗試排除 GPU 驅動的因素時，成長看起來很穩定。

We think that growth is still high and is going to last for a very long time, and that's one of the big underpinning trends that we're going to ride for the years to come.

我們認為成長仍然很高，並將持續很長一段時間，這是我們未來幾年將遵循的主要趨勢之一。

Now on the edge of that, you're right that the, where the workloads could have grown maybe instead of growing 20%, they could grow 25%, maybe some of those 5% instead are being invested both in terms of infrastructure budget or innovation, time innovation budget.

現在，在這一點上，你是對的，工作負載可能會成長 25%，而不是成長 20%，也許這 5% 中的一些會被投資於基礎設施預算或創新，時間創新預算。

All that is going into AI, and that's largely right now in experimentation and model training and that sort of thing.

所有這些都將進入人工智慧，目前主要是在實驗和模型訓練之類的事情中。

That's probably right.

這可能是對的。

But we see that also as a precursor to further workload growth in the future, like I would say, more traditional production application workload growth.

但我們認為這也是未來工作負載進一步成長的先兆，就像我所說的，更傳統的生產應用程式工作負載成長。

So for us, it doesn't really change the equation.

所以對我們來說，它並沒有真正改變方程式。

It does create a bit of a decorrelation between our numbers as a whole and the numbers you might see reported from the hyperscalers, where a lot of their short-term growth rides more into, on the capacity of GPUs they bring online for those experimentation and training workloads.

它確實在我們的整體數據與您可能會看到的超大規模數據中心報告的數據之間造成了一些不相關，超大規模數據中心的許多短期增長更多地依賴於他們為這些實驗和測試而在線提供的GPU 的容量。

Okay.

好的。

Perfect.

完美的。

Thank you.

謝謝。

And then one follow-up for David.

然後是大衛的後續行動。

Like if you think about capacity, like where are you in terms of sales capacity in case things are changing?

就像你考慮產能一樣，例如在情況改變的情況下，你的銷售能力在哪裡？

Or how do you think about like increasing, maintaining capacity as we think about the new year?

或者，當我們考慮新的一年時，您如何看待增加、維持產能？

Thank you.

謝謝。

We think long term, our revenue, our sales capacity is highly correlated with our top line growth.

我們認為，從長遠來看，我們的收入、銷售能力與我們的營收成長高度相關。

And as we said, we've been attempting to increase our sales capacity similar to top line growth rates.

正如我們所說，我們一直在嘗試提高銷售能力，以達到與營收成長率類似的水平。

And that has to do, as we've mentioned, with bottoms-up planning, putting sales capacity in areas where we see either under covered for a lot of white space and then ramping and training our salespeople.

正如我們所提到的，這與自下而上的規劃有關，將銷售能力放在我們認為有大量空白區域的區域，然後加強和培訓我們的銷售人員。

So our philosophy is to scale our sales capacity roughly in line with the top line.

因此，我們的理念是根據收入大致調整我們的銷售能力。

We see plenty of opportunity for growth and we're like, the plan is to keep growing the sales capacity.

我們看到了很多成長機會，我們的計劃是繼續提高銷售能力。

There are many markets, many geographies where we are underpenetrated.

我們在許多市場、許多地區的滲透率還不夠。

We mentioned India on the call, it's one of them, where there's tremendous opportunity, and we have very little presence at this point.

我們在電話會議上提到了印度，它就是其中之一，那裡有巨大的機會，但我們目前的參與度很少。

And in general, there's a question of what we're doing strategically, where we're going and how much we want to invest.

總的來說，存在一個問題：我們在策略上做什麼、我們要去哪裡以及我們想要投資多少。

And then tactically, the question of how we execute against that plan.

然後從戰術上講，我們如何執行該計劃的問題。

And it's, that one is a lot harder because it's easy to say we're going to grow the sales team by 20%, 30%, 40%.

事實上，這要困難得多，因為很容易說我們要將銷售團隊擴大 20%、30%、40%。

It's much harder to then have these people show up in the right region at the right time and be trained in everything else.

讓這些人在正確的時間出現在正確的地區並接受其他方面的培訓要困難得多。

And I would say we're doing fairly well there.

我想說我們在那裡做得相當好。

I would say we probably are doing better at the end of the year than we did at the beginning of the year in terms of bringing all of our, growing our sales capacity for tactical reasons.

我想說，出於戰術原因，在調動我們所有的銷售能力方面，我們在年底的表現可能比年初的表現更好。

But overall, we are executing towards our plan.

但總的來說，我們正在執行我們的計劃。

That's correct.

這是正確的。

Thank you

謝謝

Kash Rangan, Goldman Sachs.

卡什·蘭根，高盛。

Thank you very much.

非常感謝。

Appreciate it.

欣賞它。

I'm curious to get your thoughts on two things.

我很想知道你對兩件事的想法。

I'll keep this brief.

我會保持簡短。

In the subsequent few weeks after the quarter closed, I'm curious, especially with rate cuts, how you feel the customer feedback has been coming along, particularly on the SMB side since the rate of change has not been discernible at least as of the end of the quarter.

在季度結束後的接下來幾週內，我很好奇，特別是在降息的情況下，您對客戶反饋的感覺如何，特別是在中小企業方面，因為至少截至季度末。

And one for you, Olivier.

還有一份給你，奧利維爾。

As you look at GPU workloads, what about the company's existing portfolio geared towards CPU applies in a GPU world?

當您審視 GPU 工作負載時，該公司現有的以 CPU 為導向的產品組合在 GPU 領域的應用如何？

And how do you monetize an instance of GPU versus a CPU if that were to make sense?

如果 GPU 執行個體與 CPU 執行個體有意義的話，如何透過它獲利呢？

Thank you so much.

太感謝了。

You go GPU.

你去GPU。

I can go GPU, yes.

我可以使用 GPU，是的。

So look, the there's two parts to it.

所以看，它有兩個部分。

There is, how do you, what can you do for GPU that's different from a CPU.

GPU 與 CPU 不同，你如何做、你能做什麼。

I think in general, there's quite a few things that are the same in terms of understanding how that machine sits with the rest of the application or like how the system performs and that sort of stuff.

我認為總的來說，在理解機器如何與應用程式的其餘部分配合或系統如何執行等方面有很多相同的東西。

And there's quite a bit that's new and differentiated around profiling in general and understanding how you maximize the usage of the GPU bandwidth, which is usually what it's about.

在一般分析和了解如何最大限度地利用 GPU 頻寬（這通常就是它的意義）方面，有相當多的新內容和差異化內容。

I would say we're, so right now, we're working with a number of customers that have real-world large inference workloads on how we can help on the GPU profiling side for inference.

我想說的是，我們現在正在與許多擁有實際大量推理工作負載的客戶合作，探討如何在 GPU 分析方面提供幫助以進行推理。

We're doing less on the training side, mostly because the training jobs tend to be more bespoke and temporary, and there's less of an application that's attached to those that these are just very large clusters of GPUs.

我們在訓練方面做得較少，主要是因為訓練作業往往更加客製化和臨時，並且附加到那些只是非常大的 GPU 叢集的應用程式較少。

So it's closer to HPC in a way than it is to traditional applications, though we are also experimenting with what we can do there.

因此，它在某種程度上比傳統應用程式更接近 HPC，儘管我們也在嘗試在那裡可以做什麼。

There is a world where maybe in a durable fashion, 60% of workloads are inference and 40% are training.

在這個世界上，60% 的工作負荷是推理，40% 是訓練，也許以一種持久的方式。

And if that's the case, there's going to be a lot of value to be had by having repeatable training and repeatable tooling for that.

如果是這樣的話，那麼為此提供可重複的訓練和可重複的工具將具有很大的價值。

So we are also looking into that.

所以我們也在研究這個問題。

Today, as of today, we really don't monetize GPU instances all that well compared to the other CPU instances.

今天，與其他 CPU 執行個體相比，我們確實沒有很好地透過 GPU 執行個體來實現貨幣化。

So GPU instance is many times the cost of a CPU instance, and we charge the same amount for it.

因此，GPU 執行個體的成本是 CPU 執行個體的許多倍，我們對其收取相同的費用。

That doesn't have to be the case in the future.

未來不一定如此。

If we do things that are particularly interesting and it's going to have a real impact on, and deliver value and how customers use and make the best of their GPUs and in the end, save money.

如果我們做一些特別有趣的事情，它將對客戶如何使用和充分利用他們的 GPU 產生真正的影響，並提供價值，並最終節省金錢。

So today, that's the current situation.

所以今天，這就是目前的情況。

And as to your other question, in the period since the closing of Q3, we've seen very similar trends to the year-to-date in Q3 in terms of customer growth, strength in enterprise, stability in SMB.

至於你的另一個問題，自第三季結束以來，我們在客戶成長、企業實力、中小企業穩定性方面看到了與第三季迄今非常相似的趨勢。

And we have a strong pipeline for Q4 that we're working hard on harvesting as we get towards year-end.

我們在第四季度擁有強大的管道，我們正在努力在年底前收穫。

Brent Thill, Jefferies.

布倫特·希爾，杰弗里斯。

Hi, Good morning.

嗨，早安。

David, on RPO, it has been decelerating.

大衛，就 R​​PO 而言，它一直在減速。

It's in focus with investors.

這是投資者關注的焦點。

I know you've said focus on revenue.

我知道你說過關注收入。

But I think many are kind of concerned about the trajectory.

但我認為很多人都對發展軌跡感到擔憂。

And I know you've said, hey, the backlog is strong and you're adding sales capacity and all the things that makes sense that your backlog is maybe bigger than the numbers you're reporting.

我知道你說過，嘿，積壓訂單很強大，你正在增加銷售能力以及所有有意義的事情，你的積壓訂單可能比你報告的數字還要大。

But can you add any more context to what the pipeline, how you feel about the pipeline?

但是您能否為管道添加更多背景訊息，您對管道的感受如何？

What you think is going on with the metric in terms of the decel?

您認為減速度指標的情況如何？

It was a pretty big step down.

這是一個相當大的下降。

Yes.

是的。

I think, as we started talking about duration, we had a surge in this period, the period last year of longer-term contracts.

我認為，當我們開始討論期限時，我們在這段期間（去年的長期合約）出現了激增。

That was really customer led.

這確實是客戶主導的。

We may well have that in the future.

將來我們很可能會擁有這樣的東西。

But in just comparing the timing of that, it doesn't affect revenues.

但僅比較時間，它不會影響收入。

We had that kind of compare, I would say.

我想說，我們有過這樣的比較。

When you look at adjusting for duration and looking at over a long term, we do find that all of these metrics are circling around revenue in the mid-20s.

當你考慮調整持續時間並著眼於長期時，我們確實發現所有這些指標都圍繞著 20 多歲的收入。

So I think there's a lot of noise in those, and it has a lot to do with the timing, particularly in RPO of multiyear deals.

因此，我認為其中存在著許多噪音，並且與時機有很大關係，特別是在多年交易的 RPO 中。

We'll report at the end of Q4 how that progressed.

我們將在第四季度末報告進展。

We have a lot of business to do in Q4, particularly in the larger customer and enterprise side.

第四季我們有很多業務要做，特別是在大客戶和企業方面。

And we'll see where that lands.

我們會看看它會落在哪裡。

But I think it's, again, best to go back towards revenues as the North Star.

但我認為最好還是回歸北極星的收入。

And those really don't relate all that much to the sales pipelines because a lot of those, I'm putting my CFO hat right now, but, which I never wear.

這些確實與銷售管道沒有太大關係，因為其中很多，我現在正在戴上我的財務長帽子，但是，我從來沒有戴過。

So bear with me.

所以請耐心聽我說。

Everything has to do with when customers recommit and extend their commit and for how long they extend this commit, and there's a high degree of variability there.

一切都與客戶何時重新提交並延長其承諾以及延長此承諾的時間有關，並且存在很大程度的可變性。

So they might go from one year to three years.

所以他們可能會從一年到三年。

Those three years might actually run out or they might recommit after 1.5 years or 2.5 years or 3 years or maybe 3 years and 2 months if it takes longer to figure out what level they want to be at next.

這三年實際上可能會用完，或者他們可能會在1.5 年、2.5 年或3 年或3 年零2 個月後重新承諾，如果需要更長的時間才能弄清楚他們下一步想要達到什麼水平。

And so it has a ton of variability to the billings numbers in general.

因此，一般來說，帳單數字有很大的可變性。

And that's why we don't look at them at all for managing the business.

這就是為什麼我們根本不考慮他們來管理業務。

We look at usage, and we look at the sales pipelines in terms of what new business units, what new workloads, what new revenue and usage are we getting from customers.

我們專注於使用情況，並根據我們從客戶那裡獲得的新業務部門、新工作負載、新收入和使用情況來專注於銷售管道。

I think what Oli is saying is an output to the natural flow of business, which has more volatility than revenues still.

我認為奧利所說的是業務自然流動的產出，其波動性仍大於收入。

Great.

偉大的。

Thanks.

謝謝。

Karl Keirstead, UBS.

卡爾凱斯特德，瑞銀集團。

Okay.

好的。

Great.

偉大的。

I've got a couple of questions about the comment, David, around some of your larger AI native customers, maybe revenues from them being a little bit more volatile going forward.

大衛，我對一些較大的人工智慧原生客戶的評論有幾個問題，也許他們的收入未來會更加不穩定。

I guess first question is why do you think that is?

我想第一個問題是你認為這是為什麼？

Is this just a natural phenomenon of a few of those AI native customers now becoming quite large.

這是否只是一些人工智慧原生客戶現在變得相當大的自然現象？

And so it's normal that they try to look for better unit pricing and optimization?

那麼他們嘗試尋找更好的單位定價和優化是正常的嗎？

Or is there something else going on?

還是還有其他事情發生？

And then maybe secondly, when you set your 4Q guide, did you embed the assumption of some of these AI start-up pricing and observability trends that you called out?

其次，當你設定第四季指南時，你是否嵌入了你所指出的一些人工智慧新創公司定價和可觀察性趨勢的假設？

Or no, you're just trying to be prudent and that might be a little bit more of a 2025 phenomenon?

或者不，您只是想保持謹慎，這可能更像是 2025 年的現象？

Thanks so much.

非常感謝。

Yes, do you want to?

是的，你想嗎？

I can take some of that.

我可以接受一些。

I think the, look, what we see there is we, so we have that group of AI, like smaller, relatively small number of AI companies or AI native companies.

我認為，看，我們看到的是我們，所以我們有一群人工智慧，例如規模較小、數量相對較少的人工智慧公司或人工智慧本土公司。

Many of them are model providers or infrastructure providers for AI that serve the rest of the industry and they are really a proxy for the future growth of the rest of the industry in AI.

他們中的許多人都是人工智慧的模型提供商或基礎設施提供商，為行業的其他部分提供服務，他們實際上是人工智慧行業其他部分未來成長的代表。

That group has been growing very fast.

該群體增長得非常快。

I mean we mentioned it's 6% of our ARR.

我的意思是我們提到這是我們 ARR 的 6%。

It was about 4% of our year-over-year growth in Q3 versus 2% one year ago.

第三季年增約 4%，而一年前為 2%。

So it's been growing very fast.

所以它的成長速度非常快。

There is some revenue concentration within that group.

該群體內部存在一定的收入集中度。

So customers there are (inaudible) in terms of revenue like the rest of the customer base pretty much.

因此，就收入而言，那裡的客戶（聽不清楚）與其他客戶群幾乎一樣。

And seeing this very fast growth, what we do expect, we've seen that before, is we expect optimization at some point and better terms at recommit from those customers because they're all way over, or many of them are way over their last commit with us, which, again, goes back to the other comment on bookings, like their growth doesn't show up at all in the ARPUs and the bookings numbers because they're way over their commit.

看到這種非常快的成長，我們所期望的，我們之前已經看到過，我們期望在某個時候進行優化，並在這些客戶重新承諾時提供更好的條款，因為他們已經全部結束了，或者他們中的許多人超出了他們的預期上次與我們的承諾，這又回到了對預訂的其他評論，就像他們的增長根本沒有出現在ARPU 和預訂數量中，因為它們遠遠超出了他們的承諾。

The analogy I would give there is what we've seen with cloud native in the late '10s and early '20s, where we had these numbers of cloud native consumer companies that were growing very fast.

我將給出的類比是我們在 10 年代末和 20 年代初所看到的雲端原生，當時我們擁有大量成長非常快的雲端原生消費公司。

With two differences, the first one is that the AI cohort is growing faster and there are larger individual ACVs for these customers.

有兩個區別，第一個區別是人工智慧群體成長得更快，而這些客戶的個人 ACV 更大。

And the second difference is that it's a much smaller fraction of our total ARR.

第二個區別是它占我們總 ARR 的比例要小得多。

So at the time, we had a very large number, a very large amount of our revenue that was cloud native companies and consumer companies in the late '10s and early '20s.

所以當時，我們有很大一部分收入來自 10 年代末和 20 年代初的雲端原生公司和消費公司。

Today, we just have 6% of our ARR in that bucket.

如今，我們的 ARR 僅有 6%。

So we made that comment because we don't have anything to say in terms of where it's going.

所以我們發表這樣的評論是因為我們對它的發展方向沒有什麼好說的。

We don't, there's nothing we see in October that tells us like there's big changes.

我們沒有，十月沒有看到任何重大變化。

But we do think there can be volatility there.

但我們確實認為那裡可能存在波動。

Especially, this can move the numbers in the short term, while the mid to long-term growth, or the mid to long-term dominant motion we'll see is growth with that customer base.

特別是，這可以在短期內改變數字，而中長期成長，或者我們將看到的中長期主導運動是客戶群的成長。

So that's why we made that comment.

這就是我們發表這一評論的原因。

Yes.

是的。

And as to fourth quarter, I echo the comments we make.

至於第四季度，我同意我們的評論。

Overall, which is we take conservative assumptions relative to usage growth that are lower than we've seen in providing our guidance.

總體而言，我們對使用量成長採取保守假設，該假設低於我們在提供指導時看到的情況。

Of course, where we are in the year, the effect on Q4 is more limited than it would be on next year.

當然，就今年的情況而言，對第四季的影響比明年要有限。

And as we report Q4 and give guidance, we will update everybody on any trends that we do see in this cohort at that time.

當我們報告第四季度並提供指導時，我們將向所有人通報我們當時在該群體中看到的任何趨勢。

We didn't change guiding principles for this.

我們沒有為此改變指導原則。

We made an extra comment on it because we want to be transparent.

我們對此做了額外的評論，因為我們希望保持透明。

We've seen that.

我們已經看到了。

And we see some customers are wherever they commit.

我們看到一些客戶無論在哪裡。

And, but we didn't make anything specific in the guidance.

而且，我們沒有在指南中做出任何具體說明。

Okay.

好的。

That's all very helpful.

這一切都非常有幫助。

Kirk Materne, Evercore ISI.

柯克·馬特納，Evercore ISI。

Yes, thanks very much.

是的，非常感謝。

Oli, you mentioned the one federal customer this quarter, larger federal customer this quarter.

奧利，您提到了本季的一個聯邦客戶，本季更大的聯邦客戶。

Can you just talk on broader trends for you all within the federal government and sort of the opportunity there and what you're seeing?

您能否談談聯邦政府內部更廣泛的趨勢以及那裡的機會和您所看到的情況？

And I guess, if it had any positive impact?

我想，這是否有任何正面影響？

Obviously, it's their fiscal year-end in September.

顯然，九月是他們的財政年度結束日。

So just any comments more generally on Fed would be great.

因此，任何關於美聯儲的更普遍的評論都會很好。

Thanks.

謝謝。

Look, it's a huge opportunity for us.

看，這對我們來說是一個巨大的機會。

And we're, I would say, quite early with some interesting successes.

我想說，我們很早就取得了一些有趣的成功。

So we have some exciting logos there, like this one that we mentioned this quarter, which is an agency we all interact with and which has tremendous opportunity for growth and upsell with us.

因此，我們有一些令人興奮的標誌，就像我們本季提到的這個標誌，這是一個我們都與之互動的機構，並且與我們有巨大的成長和追加銷售機會。

There's another agency that already has a very large multimillion dollar ACV footprint with Datadog that we didn't talk about this quarter, but that's been a long-term customer.

還有另一家機構已經與 Datadog 建立了價值數百萬美元的 ACV 業務，本季我們沒有談論該機構，但那是我們的長期客戶。

So there's plenty of opportunity.

所以有很多機會。

We're still very early in terms of capacity building, channel building and go-to-market in general in government.

就政府的能力建構、通路建設和市場進入而言，我們總體上還處於早期階段。

So I would say it's still a small part of our overall business, but we see that there's tons of upside in it.

所以我想說，這仍然只是我們整體業務的一小部分，但我們看到它有很多好處。

And we're working hard on the product side so that we can capture that fully.

我們正在產品方面努力工作，以便我們能夠充分捕捉到這一點。

So we, over the past few years, we worked on our FedRAMP compliance, and we are working further on getting into more regulated, even tougher to get into workloads with FedRAMP and (inaudible) and other certifications like that.

因此，在過去的幾年裡，我們致力於 FedRAMP 合規性，並且我們正在進一步努力，透過 FedRAMP 和（聽不清楚）以及其他類似認證，使工作負載變得更加規範、更加嚴格。

So we have a long road map there and big plans to build and a lot of upside.

因此，我們在那裡有一個漫長的路線圖和宏偉的計劃，還有很多好處。

Thank you.

謝謝。

Mike Cikos, Needham.

麥克·西科斯，尼達姆。

Hey, thanks for getting me on the on the call here, guys.

嘿，謝謝你們讓我接聽電話，夥計們。

I just had two quick questions for you.

我只是想問你兩個簡單的問題。

The first on gross margin.

首先是毛利率。

Just wanted to get a better understanding.

只是想獲得更好的理解。

Is there anything you can speak to as it relates to those AI native customers, the intensity of those workloads and then how your products feed into it or maybe even the broader portfolio and the product expansion you've seen.

您有什麼可以談談的，因為它與那些人工智慧原生客戶、這些工作負載的強度以及您的產品如何融入其中，甚至是您所看到的更廣泛的產品組合和產品擴展有關。

I'm just wondering if those newer products maybe are detracting from gross margin near term here versus some expansion that we can expect as these products scale?

我只是想知道這些新產品是否可能會降低近期的毛利率，而隨著這些產品規模的擴大，我們可以預期會有一些擴張？

That's the first question.

這是第一個問題。

Second question was just great to hear that the usage growth continues to trend higher, especially for those existing customers.

第二個問題很高興聽到使用量成長持續呈上升趨勢，特別是對於那些現有客戶而言。

Does it feel where we sit today in this new environment, like this is par for the course kind of growth when thinking about the usage coming from those existing customers?

當考慮到來自現有客戶的使用情況時，我們今天在這個新環境中是否感覺像是這種成長過程的標準？

Or is there a reason to believe that this can actually accelerate if things can move higher one way or another?

或者是否有理由相信，如果事情能夠以某種方式走高，這實際上會加速？

What would drive that?

是什麼推動了這一點？

Yes.

是的。

So on gross margins, in general, we are happy with where they are.

因此，就毛利率而言，總的來說，我們對它們的現狀感到滿意。

I mean there's some small moves in it.

我的意思是其中有一些小動作。

I wouldn't read too much into moves.

我不會過度解讀動作。

I mean there's, behind the scenes, there's a number of things that underpin that.

我的意思是，在幕後，有很多事情支撐著這一點。

We keep building new functionality.

我們不斷建立新功能。

At the same time, we keep optimizing our code and use it.

同時，我們不斷優化我們的程式碼並使用它。

We actually use our products to optimize that quite a bit.

實際上，我們使用我們的產品來優化這一點。

And then we also keep getting better and better agreements with our cloud providers as we scale.

隨著規模的擴大，我們也不斷與雲端供應商達成越來越好的協議。

So it's a combination of all that is what you see in the gross margin number.

因此，它是您在毛利率數字中看到的所有內容的組合。

We, internally, we have to make a call always on whether we direct more effort at building new functionality or optimizing.

我們在內部必須始終決定是否將更多精力用於建立新功能或最佳化。

And the way we manage that is when gross margins get a little bit low, we put more effort on optimizing.

我們的管理方式是，當毛利率有點​​低時，我們會投入更多精力進行最佳化。

And when we are in a happier zone, like we redirect more effort on new products and new functionality into that.

當我們處於更快樂的狀態時，我們就會將更多精力投入到新產品和新功能上。

There's not a lot of change or that product mix doesn't really matter all that much on a gross margin perspective.

沒有太多變化，或從毛利率的角度來看，產品組合就沒那麼重要。

And so there's no particular worries there.

所以沒有特別擔心的地方。

We think long term, there are plenty of opportunities to improve margins.

我們認為從長遠來看，有許多機會提高利潤率。

But right now, the focus is on really shipping enough products to enough customers, making sure that those products get, provide them with as much value as possible while staying within a certain happy zone on the overall margin.

但現在的重點是真正向足夠多的客戶運送足夠的產品，確保這些產品為他們提供盡可能多的價值，同時將整體利潤率保持在某個滿意的範圍內。

In terms of the growth of workloads, look, I mean, as we said, we see growth across the customer base pretty much.

就工作負載的成長而言，我的意思是，正如我們所說，我們看到整個客戶群的成長相當大。

We see growth of classical workloads in the cloud.

我們看到雲端中經典工作負載的成長。

We see large growth, very large growth on the AI native side.

我們看到人工智慧原生的巨大成長，非常巨大的成長。

We think that the one big catalyst for future acceleration will be those AI native applications or AI applications, I should say, going into production for non-AI native companies for a much broader set of customers than the customers that are deploying these kind of applications to their, in production.

我們認為，未來加速的一個重要催化劑將是那些人工智慧原生應用程式或人工智慧應用程序，我應該說，為非人工智慧原生公司投入生產，為比部署此類應用程式的客戶更廣泛的客戶群服務對他們來說，在生產中。

And as they do, they will also look less like just large cluster of GPUs and more like traditional applications because the GPU needs a database, it needs core application in front of it, it needs layers to secure it and authorize it and all the other things.

正如它們所做的那樣，它們看起來也不像大型GPU 集群，而更像傳統應用程序，因為GPU 需要資料庫，它需要前面的核心應用程序，它需要層來保護它並授權它以及所有其他應用程序事物。

So it's going to look a lot more like a normal application with some additional more concentrated compute and GPUs.

因此，它看起來更像是一個普通的應用程序，帶有一些額外的更集中的計算和 GPU。

Thank you very much,

非常感謝，

Gray Powell, BTIG.

格雷·鮑威爾，BTIG。

All right.

好的。

Great.

偉大的。

Thanks for taking my question.

感謝您提出我的問題。

Maybe just a follow-up on Datadog on call.

也許只是 Datadog on call 的後續行動。

It was good to hear the commentary on that earlier in the call, and it has been coming up more in our field work.

很高興在電話會議早些時候聽到對此的評論，並且在我們的現場工作中越來越多地出現這種情況。

So I'm just curious like how should we think about the opportunity there?

所以我很好奇我們應該如何看待那裡的機會？

Is that something that could completely displace a product like PagerDuty?

這是否可以完全取代 PagerDuty 這樣的產品？

Or is it more of an add-on feature since my understanding is it mainly works with the Datadog ecosystem versus other tools?

或者它更像是一個附加功能，因為我的理解是它主要適用於 Datadog 生態系統而不是其他工具？

Thanks.

謝謝。

Look, we'll take it where the demand takes us.

聽著，我們會把它帶到有需求的地方。

So we initially built it as a way for customers within our ecosystem to have a fully integrated experience.

因此，我們最初將其建構成讓我們生態系統中的客戶獲得完全整合體驗的一種方式。

And really as a step stone towards full automation of incident resolution and full ownership from end-to-end.

這實際上是實現事件解決完全自動化和端到端完全所有權的踏腳石。

The part that strategically is the most interesting to us is the automation of the resolution, not physically aging customers.

從策略上講，我們最感興趣的部分是解決方案的自動化，而不是實際老化的客戶。

That being said, the response from customers has been so strong that there is very high demand for integrating with many different other sources and plug ourselves into incident resolution loops that we might not have been a part of before even.

話雖這麼說，客戶的反應如此強烈，以至於對與許多不同的其他來源整合以及將我們自己納入事件解決循環中的需求非常高，而我們以前可能從未參與過這種循環。

And so that's definitely something that we're going to build for customers.

所以這絕對是我們要為客戶打造的東西。

We're just very happy to see the demand there.

我們很高興看到那裡的需求。

Understood.

明白了。

All right, guys.

好吧，夥計們。

Thanks very much.

非常感謝。

Ittai Kidron, Oppenheimer.

伊泰·基德倫，奧本海默。

Thanks.

謝謝。

Nice numbers, guys.

夥計們，數字不錯。

Oli, a question for you.

奧利，問你一個問題。

I think you mentioned in your prepared remarks that 15 of your 23 products are now running over $10 million.

我想您在準備好的發言中提到，您的 23 種產品中有 15 種現在的銷售額超過 1000 萬美元。

Maybe if you look at the ones that are still under $100 million, or under $50 million, where do you see, where are you most excited?

也許如果你看看那些仍然低於 1 億美元或低於 5000 萬美元的項目，你會看到哪裡，你最興奮的地方在哪裡？

Which ones do you think have the highest odds of crossing the $100 million mark?

您認為哪些作品突破 1 億美元大關的幾率最高？

Well, again, I don't want to single out any products for which we didn't disclose metrics in particular.

好吧，再說一遍，我不想挑出任何我們沒有特別揭露指標的產品。

But look, we mentioned in previous calls, like there are products that are growing very fast that we think will reach the scale velocity.

但是，我們在之前的電話會議中提到過，有些產品成長得非常快，我們認為它們將達到規模速度。

We see, we talked about database monitoring, for example, was a product has been growing very fast, very clear value.

我們看，我們講到資料庫監控，比如說，是一個產品一直成長得非常快，價值非常明確。

And we, I actually forgot which number we disclosed last time, but we did disclose a number for it. 1% of revenue is what we disclosed.

我們，其實我忘了上次我們揭露的是哪個數字，但是我們確實揭露了一個數字。我們披露的是收入的1%。

And so this one is clearly headed for north of 50%.

因此，這一比例顯然會超過 50%。

There's a number in the other cohort that I, a number of products across security, user experience that I think are definitely going to get there very soon.

在我的另一組中，有一些涉及安全、用戶體驗的產品，我認為肯定很快就會實現。

So we feel good about all that basically.

所以我們基本上對這一切感覺良好。

(multiple speakers) The point here is pretty much every single one of those products should be above $50 million.

（多位講者）這裡的重點是，這些產品中幾乎每一款產品的售價都應該超過 5,000 萬美元。

Some of them are going to get there faster than others.

他們中的一些人會比其他人更快到達那裡。

Some of them will cross $100 million.

其中一些將超過 1 億美元。

Some of them will cross $1 billion maybe.

其中一些可能會突破 10 億美元。

So I think we feel good about the product set.

所以我認為我們對產品組合感覺良好。

That's great.

那太棒了。

Maybe as a follow-up for both of you.

也許作為你們倆的後續行動。

You didn't provide '25 guidance, of course, but are there any thoughts you want to leave us with as we think about '25 and perhaps given where we are in the year.

當然，您沒有提供“25 年”指導，但是當我們考慮“25 年”以及考慮到我們今年的處境時，您有什麼想法想留給我們嗎？

Oli, your initial conversations with customers and how they think about next year, anything to point out with respect to their behavior or investment areas of focus, which perhaps are different than what they've been in '24?

Oli，您與客戶的初步對話以及他們對明年的看法，關於他們的行為或投資重點領域有什麼需要指出的嗎？

Look, I think the only thing I would say is, I mean, I won't get into second guessing our guidance or things like that.

看，我想我唯一要說的是，我的意思是，我不會再猜測我們的指導或類似的事情。

And we, in general, also, it's very hard to guess usage ahead of time because that's actually very, it is different or can be very different from the intents that are being manifested by customers or their understanding of what the next year is going to look like.

一般來說，我們也很難提前猜測使用情況，因為這實際上與客戶所表達的意圖或他們對明年的理解非常不同，或者可能非常不同看起來。

But the one thing I will say is we're investing.

但我要說的一件事是我們正在投資。

We're building sales capacity.

我們正在建立銷售能力。

We're definitely investing heavily in engineering.

我們肯定在工程方面投入了大量資金。

I think it's a target investment in the industry.

我認為這是行業的目標投資。

Unlike many others, we don't expect at this point to have outsized investments in compute.

與許多其他公司不同，我們目前預計不會在計算方面進行大規模投資。

We're not building absolutely large GPU clusters, but we are building engineering capacity, and we are building sales capacity.

我們並不是在建立絕對大型的 GPU 集群，但我們正在建立工程能力，我們正在建立銷售能力。

And so you should expect that in the numbers we give for next year.

所以你應該在我們給出的明年的數字中預料到這一點。

Great.

偉大的。

Appreciate it.

欣賞它。

David, anything to add or?

大衛，有什麼要補充的嗎？

No, I think we, I've said that at this point, we've noted that there's been stability to upward trend in usage that many of our clients, particularly in enterprise, are getting back to the work of launching digital applications, and that's creating the pipeline and the results for us.

不，我認為我們，我已經說過，在這一點上，我們注意到使用量呈穩定的上升趨勢，我們的許多客戶，特別是企業客戶，正在重新開始啟動數位應用程式的工作，並且這正在為我們創建管道和結果。

And although we still are in an environment that's careful and wants return on their investments.

儘管我們仍然處於一個謹慎的環境中，並且希望他們的投資得到回報。

And we'll update everybody as to whether that's what we see.

我們將向大家通報這是否是我們所看到的最新情況。

But generally, we're giving comments based on what we see in this environment, which has been good and stable.

但總的來說，我們是根據我們在這個良好且穩定的環境中看到的情況來發表評論的。

Thank you.

謝謝。

Appreciate it.

欣賞它。

Thank you.

謝謝。

This concludes the question and answer session.

問答環節到此結束。

I would now like to turn it back over to CEO, Olivier Pomel for closing remarks.

現在我想將其轉回給執行長奧利維爾·波梅爾 (Olivier Pomel) 致閉幕詞。

Well, thank you all for attending the call.

好的，謝謝大家參加電話會議。

I want to give a few shout-outs.

我想大聲喊幾句。

Firstly, for the product management team for building great products last quarter, the customers that actually spent all this time with us on getting those products to work right, especially for the new products, and I'm talking about LLM observability, for example, or OnCall, and so I know we spent a lot of time with customers to get those right.

首先，對於上個季度打造出色產品的產品管理團隊來說，實際上花了所有時間與我們一起讓這些產品正常工作的客戶，尤其是新產品，我正在談論LLM可觀察性，例如，或OnCall ，所以我知道我們花了很多時間與客戶溝通以確保這些正確。

And I also want to give a special shout out to the go-to-market team.

我還想特別讚揚市場推廣團隊。

We have a very, very, very loaded fourth quarter, very full slate for everyone in the next, let's call it, 1.5 months.

我們有一個非常非常非常繁忙的第四季度，接下來的 1.5 個月裡每個人的日程都非常滿。

And so I know everybody is super hard at work.

所以我知道每個人都非常努力工作。

So thank you, everyone.

謝謝大家。

And on this, I think we'll wrap the call.

關於這一點，我想我們會結束通話。

Thank you for your participation in today's conference.

感謝您參加今天的會議。

This does conclude the program.

這確實結束了該程式。

You may now disconnect.

您現在可以斷開連線。