en.Wedoany.com Reported - US cloud computing company DigitalOcean has secured multiple nine-figure annual commitments for AI inference and cloud services, while simultaneously adding future data center capacity. These customer commitments cover multi-year AI infrastructure services, boosting the visibility of the company's long-term contract revenue and signaling that the AI cloud market is shifting from simply competing for GPU resources to locking in long-term computing power, software platforms, and enterprise-grade AI demand.
The direct impact of these commitments is increased certainty for DigitalOcean's future revenue. The company expects its remaining performance obligations to grow more than tenfold from the second quarter of fiscal 2025, exceeding $800 million; the average contract term is also expected to extend from 1.6 years to over 3 years. For AI cloud service providers, long-term contracts mean that customers are not just short-term trial users of computing power, but are integrating inference, model deployment, application operation, and cloud service capabilities into more stable business plans.
DigitalOcean is positioning itself as an AI-native cloud platform, not just a GPU leasing provider. The AI infrastructure market has been highly competitive over the past two years, with many companies initially focusing on GPU models, supply speed, and rental prices. However, as AI applications enter production environments, customers are beginning to prioritize model scheduling, inference costs, network capabilities, development experience, operational simplicity, and long-term capacity delivery. Software capabilities like DigitalOcean's Inference Router are designed to schedule across different proprietary and open-source models based on cost, performance, and invocation efficiency, helping customers choose more suitable inference paths among multiple models.
Physical capacity remains the foundation of AI cloud competition. DigitalOcean has added 20 megawatts of future data center capacity, expected to come online between late 2027 and early 2028, bringing its committed data center capacity to approximately 155 megawatts. Demand for AI inference and cloud services is growing rapidly, but data center construction, power access, liquid and air cooling facilities, network deployment, and server delivery all require long lead times. After customers sign multi-year commitments, cloud service providers must secure facilities, power, and equipment resources in advance to deliver computing power consistently over the coming years.
This also indicates that the bottleneck in AI infrastructure is no longer just GPUs. High-density AI clusters require stable power, network architecture, cooling systems, rack space, operations teams, and long-term colocation arrangements to work together. DigitalOcean's continued search for more data center capacity reflects that AI cloud providers are competing around power, land, cooling, interconnection networks, and long-term facility contracts. Those who can secure future capacity earlier will have greater ability to absorb demand as enterprise customers expand their AI deployments.
On the financial side, DigitalOcean expects second-quarter revenue to grow approximately 29% year-over-year, with adjusted EBITDA margins and non-GAAP earnings per share likely to meet or exceed the upper end of previously provided guidance. The company also expects current customer demand to improve its previously disclosed exit revenue growth expectations for 2026. While remaining performance obligations are essentially contractual and not equivalent to recognized revenue, they provide a clearer demand basis for future capacity expansion, procurement, and customer delivery.
The AI cloud market is entering a phase that places greater emphasis on delivery capabilities. When selecting a service provider, enterprise customers will not only look at the availability of a certain batch of GPUs but will also evaluate inference platforms, network performance, model ecosystems, cost control, contract stability, and future capacity roadmaps. After securing nine-figure AI cloud annual commitments and adding 20 megawatts of data center capacity, DigitalOcean's AI infrastructure business will continue to advance around customer contracts, inference software, and data center expansion.
