DigitalOcean’s Q2 Preview: RPO Surges Toward $800 Million as AI-Native Cloud Expands Capacity

Ticker: DOCN • EPS concepts in focus (non-GAAP EPS) • revenue forecast • earnings surprise considerations • EPS consensus

Executive snapshot: a backlog story with capacity for more

DigitalOcean Holdings, Inc. (NYSE: DOCN) signaled a confident lane ahead for Q2 2026, projecting record remaining performance obligations (RPO) exceeding $800 million. That figure would mark a more than tenfold increase versus the second quarter of fiscal year 2025, underscoring the company’s ability to lock in AI-centric workloads over multi-year horizons.

The company also guided for a 29% year-over-year revenue growth in Q2 2026—quite the acceleration relative to the mid-teens pace of 2025. Management framed this as a bulwark against volatility in shorter-cycle revenue, with the RPO backlog acting as a visible tailwind for future quarters.

Operational highlights and capacity buildout

DigitalOcean disclosed the addition of 20 MW of committed data center capacity for 2027–2028, lifting total committed capacity to roughly 155 MW. This is presented as a deliberate step to sustain demand for its AI-native cloud platform, which is pitched as optimized for inference and agentic workloads.

The company also noted ongoing momentum in its product suite, including capabilities like an Inference Router designed to balance price and performance across closed and open-source models. The strategy appears to hinge on tying customers into a scalable, integrated stack—an early signal of what the company hopes will translate into longer-lived contracts and a steadily rising revenue forecast.

Guidance, margins, and earnings framing

In addition to topline strength, DigitalOcean said Q2 2026 could include an aEBITDA margin and non-GAAP Net Income per Share at or above the high end of prior guidance. In practical terms, this aligns with a positive EPS trajectory on a non-GAAP basis, even as GAAP metrics may tell a different story given depreciation, amortization, and other charges that a capital-light hyperscaler might handle differently.

The release also includes the familiar caveat that non-GAAP reconciliations are not available on a forward-looking basis due to uncertainties in future expenses. Investors should map the reported guidance against their own EPS consensus expectations and consider whether any anticipated earnings surprise might materialize when the company reports.

What the narrative signals about DigitalOcean and the AI-native cloud market

DigitalOcean frames itself as the AI-native cloud—built to serve inference workloads and agentic applications with an emphasis on simplicity, scale, and total cost of ownership. The narrative positions the company as a facilitator for developers and enterprises seeking to deploy AI workloads without the complexity of bespoke GPU rental arrangements or ad hoc infrastructure stitching.

The nine-figure annual commitments cited in the press release suggest a customer base willing to commit capital on a multi-year horizon, which bodes well for predictability in the revenue forecast and for a more stable earnings trajectory over time.

Implications for sector peers and the AI cloud competitive landscape

If the Q2 trajectory holds, DigitalOcean’s emphasis on capacity expansion and higher RPO growth could push peers to double down on AI-native capabilities, multi-year commitments, and integrated inference tooling. The combination of strong backlog growth and targeted capacity investments hints at a broader sectoral shift toward cloud platforms positioning themselves as indispensable AI accelerants rather than generic compute providers.

For competitors and potential entrants, the message is clear: to secure enterprise-scale AI workloads, players will need clearer value propositions around performance, cost, and the ability to convert contracted backlogs into reliable revenue streams. A meaningful earnings surprise would likely hinge on maintaining or expanding the pace of customer wins while delivering the promised margin expansion, which is not a given in a capital-intensive frontier.

Risks and forward-looking considerations

The press release explicitly frames the forward-looking statements as subject to risks, uncertainties, and assumptions. In practice, that means macroeconomic shifts, demand for AI-native services, execution of capacity expansions, and potential delays in data-center deployment could influence actual results.

Investors should monitor how real-world metrics—like RPO conversion rates, gross margin progression as the company scales, and the impact of any capital expenditure—translate into the EPS and EPS consensus against the revenue forecast embedded in the guidance. The absence of a published, current EPS consensus for Q2 2026 in the release invites caution: an actual earnings surprise could come as much from margin discipline as from top-line resilience.

Takeaways: what to watch as DOCN moves toward its earnings release

RPO > $800 million, >10x growth YoY, signals durable revenue visibility beyond the current quarter.
Revenue growth guidance of 29% for Q2 2026 points to accelerating demand for AI-native cloud services.
20 MW of additional capacity planned for 2027–2028, with a total of ~155 MW committed, indicating a meaningful capex commitment to sustain growth.
Non-GAAP EPS and aEBITDA margin guidance at the high end suggests optionality for upside if execution remains on track.
Forward-looking caveats emphasize uncertainty; analysts will gauge how closely actual results align with consensus expectations and how RPO converts into realized revenue.

Conclusion: a proof-of-concept for the AI-native cloud thesis?

DigitalOcean’s pre-announcement paints a cohesive picture: a fast-growing revenue engine backed by a robust RPO backlog and meaningful capacity expansion aimed at serving AI-native workloads. The near-term optics look favorable—an above-consensus tilt on profitability metrics within a quarter that also promises strong revenue growth—but the longer arc depends on the company’s ability to convert RPO into sustained cash generation while managing the capital required to scale.

For investors, the core question remains: will DOCN’s AI-native stack continue to differentiate enough to justify the capex and to produce earnings above street expectations, or will the backdrop of AI compute demand prove more cyclical than anticipated? Either way, the sector’s mood ring is pointing toward backlogs turning into bookings and bookings into predictable revenue, with EPS visibility walking a fine line between optimism and discipline.