Datadog, Inc. (DDOG) | The Buildout — AI Infrastructure

The Verdict

Datadog is a software layer, not an infrastructure operator. It provides an AI-powered observability and security platform that monitors cloud applications, infrastructure, logs, AI workloads, and security events in one place. For the AI buildout, Datadog makes new infrastructure legible: GPU fleets, LLM chains, agents, and training runs become monitored workloads, and customers consolidate legacy tools onto one platform.

Earnings Beat

Datadog reported Q2 FY2026 revenue of $1.12B, up 36% year-over-year and 11% sequentially, with a record $115M sequential dollar add. Non-GAAP gross margin was 79.6%, down from 80.2% in Q1 and 80.9% a year ago; non-GAAP operating income was $257M (23% margin), and free cash flow was $279M (25% margin). Non-AI customer revenue growth reached the high-20s percent, up from mid-20s in Q1 and 18% a year ago.

Management tone: Management’s tone on the Q2 call was confident and deliberately transparent, especially on the largest customer. The shift from Q1 is that the largest customer went from an abstract conservatism item to a concrete disclosed usage reduction, while management framed the rest of the business as booming and highlighted five quarters of acceleration excluding that customer.

Management Guidance

For Q3 FY2026, management guided revenue to $1.135B–$1.145B (+28–29% y/y) and non-GAAP operating margin to 23–24%. For FY2026, revenue guidance was raised to $4.45B–$4.47B (~30% y/y) and non-GAAP operating margin to ~23%. Management reiterated capex plus capitalized software of 4–5% of revenue and held gross margin expectation at 80% plus or minus; the Q3 sequential guide deliberately reflects the largest customer’s usage reduction.

Trajectory

Reported revenue growth accelerated from 32% y/y in Q1 FY2026 to 36% in Q2, with the $115M sequential add the largest on record. Non-AI customer revenue growth reached the high-20s percent, up from mid-20s in Q1 and 18% a year ago, and new-customer contribution to y/y growth rose to ~30%. Gross margin slipped to 79.6% from 80.2% and 80.9% a year ago on cloud-hosting cost growth, while non-GAAP operating margin expanded to 23% from 20% a year ago on OpEx leverage.

The Model

The model projects FY+1 revenue of $4,490M and EBITDA of $189M (4.2% margin), and FY+2 revenue of $5,700M with EBITDA of $428M (7.5% margin). The FY+1 revenue figure sits just above the midpoint of management’s raised FY2026 revenue guide of $4.45B–$4.47B and reflects the largest-customer derisking in guidance; FY+2 assumes continued broad-based growth and operating leverage as new-logo ramps and AI/agentic usage convert.

Projections are the median of 5 independent model runs. The model’s revenue sits 9.3% above analyst consensus.

For Q3 FY2026, management guided revenue to $1.135B–$1.145B (+28–29% y/y) and non-GAAP operating margin to 23–24%. For FY2026, revenue guidance was raised to $4.45B–$4.47B (~30% y/y) and non-GAAP operating margin to ~23%. Management reiterated capex plus capitalized software of 4–5% of revenue and held gross margin expectation at 80% plus or minus; the Q3 sequential guide deliberately reflects the largest customer’s usage reduction.

What Could Go Right — and Wrong

Looking Ahead

The next twelve months turn on whether the derisked Q3 step-down is followed by the implied Q4 reacceleration and whether non-AI growth holds in the high-20s. Management also pointed to a product wave still rolling out from DASH (100+ capabilities), the integration of Adaptive ML for time-series and post-training models, BYOC metrics/traces expansion, and an early federal pipeline after FedRAMP High; none of these carries a precise revenue date in the source.

Financials

Annual Summary

Key Ratios (Trailing)

The Company

Datadog is a SaaS platform for AI-powered observability and security across cloud applications. It integrates infrastructure monitoring, application performance monitoring, log management, user-experience monitoring, cloud security, service management, and many adjacent capabilities into one real-time view of a customer’s technology stack. That consolidation is the core promise: instead of running separate tools for APM, logs, RUM, and SIEM, customers see the whole stack and increasingly adopt more Datadog products, with 58% of customers using at least four products and 37% using at least six.

The model is usage-based and cloud-run. Management has repeatedly said most workloads run in the cloud, so costs appear in operating expenses rather than heavy capital expenditure; FY2026 capex plus capitalized software is guided at 4–5% of revenue. The 10-K lists only leased office facilities — the principal executive office in New York (~395,000 sq ft, leases to June 2033) and other leased offices in Boston, Denver, San Francisco, Paris, Dublin, Amsterdam, Sydney, Tokyo, Singapore, and Seoul. Datadog does not report formal operating segments.

Business Segments

Competitive Landscape

Datadog’s competitive dynamic is fragmented across categories. The 10-K names IBM, Microsoft, and SolarWinds in on-premise infrastructure monitoring; Cisco, New Relic, and Dynatrace in APM; Cisco and Elastic in log management; and native cloud-monitoring solutions from AWS, Microsoft Azure, and Google Cloud Platform. In disclosed deals, replacement direction has run toward Datadog — four tools displaced at an online media company, three legacy APM tools at an insurer, an entire on-prem layer at a hedge fund — while competitive pressure comes from hyperscaler native tools and the named APM/log vendors.

Supply Chain

Datadog is a software layer, not an infrastructure operator. Its primary input is third-party cloud infrastructure, disclosed in the Q1 10-Q as a driver of cost of revenue.