Shares of Datadog Inc. popped after the application monitoring software firm crushed Wall Street’s expectations with its first-quarter financial results today and followed up with strong guidance.

The stock gained more than 30% during the regular trading session today, and also helped to boost the price of other software firms. Datadog’s gains, which came after impressive results from Twilio Inc. last week, sparked a broader rally among software stocks. Shares of Snowflake Inc. and MongoDB Inc. both gained more than 10% today, while Dynatrace Inc. and Elastic N.V. were up just over 5%.

The company reported earnings before certain costs such as stock compensation of 60 cents per share, easily beating the Street’s consensus estimate of 51 cents. Revenue rose 32% from a year earlier to $1 billion, well above the analyst target of $931.8 million. Those numbers helped to more than double Datadog’s overall profit, with net income reaching $52.6 million in the quarter, up from $24.6 million in the same period one year ago.

Looking forward, Datadog said it’s expecting full-year earnings of between $2.36 and $2.44, well up from its prior forecast of between $2.08 and $2.16. It also lifted its revenue guidance to a range of $4.3 billion to $4.34 billion, up from a prior forecast of $4.06 billion to $4.1 billion. For the current quarter, Datadog sees earnings of between 57 and 59 cents on revenue of $1.07 billion to $1.08 billion. Wall Street is targeting earnings of just 50 cents per share on sales of $994.4 million.

Datadog’s stock had barely moved the needle so far in 2026, but is now up more than 38% in the year to date. The company has emerged as a rare bright spot in a software industry that has been rocked by the artificial intelligence boom, with investors worried that AI models may end up eating their businesses.

Datadog specializes in selling monitoring systems for AI chips and also AI models and agents, and boasts the likes of OpenAI Group PBC and Amazon Web Services Inc. as customers. Its growth is linked to the AI industry, because models require massive volumes of data for both training and inference, and that necessitates increasingly complex infrastructure systems, creating more potential for problems. As a result, companies need a way to monitor those systems.

With Datadog’s observability tools, companies can see what’s happening across their entire digital estates, gauging things such as cloud usage, application, server and database health. They can also monitor their networks and identify security threats using its tools. And with the rise of autonomous AI agents, companies also need specialized tools to monitor their activities.

Holger Mueller of Constellation Research told SiliconANGLE that AI adoption is clearly adding to Datadog’s momentum this year. “It has introduced observability tools for both the agentic AI infrastructure and the AI agents themselves, and these products are proving to be popular with enterprises,” the analyst said. “This is the result of Datadog’s heavy spending on R&D, which is now more than the combined amount it spends on sales, marketing and general and administrative costs. It’s the right approach, because companies are going to have to spend to keep up with the pace of innovation in the AI era.”

AI agents require constant observation, Datadog Chief Executive Oliver Pomel (pictured) said on a call with analysts. “There is no change to our overall view that digital transformation and cloud migration are long-term secular growth drivers for our business,” he said. “But we now have an additional secular growth driver with AI as we help our customers deliver more value with this transformative new technology.”

Pomel talked about the value his company provides in more detail. He discussed its work with a Fortune 500 insurance firm, which was previously reliant on a “fragmented” observability stack that wasn’t up to the job. As it employed more AI in its network and systems, it was seeing numerous outages and complaints from customers. Datadog installed its incident detection systems and broader observability tools and quickly helped to address those issues, Pomel revealed.

The company’s work has resulted in increased customer traction, the CEO added. He said it recently signed deals with the AI research divisions of two of the world’s largest technology firms, worth seven figures and eight figures, respectively. It has also signed up new customers including hyperscalers, hedge funds, banks and federal government agencies.

Photo: Barrchives Podcast/YouTube