Datadog has been named a Leader in Gartner's 2026 Magic Quadrant for Observability Platforms, marking the sixth consecutive year it has received that designation.
According to Datadog, it ranked highest for Ability to Execute among the vendors assessed in the report.
Observability software helps technology teams monitor applications, infrastructure and digital services. The market is drawing increased attention as companies deploy more artificial intelligence tools and large language model applications. Vendors are increasingly pitching products that help customers track system performance, investigate failures and monitor the behaviour of AI systems.
Datadog said the latest recognition reflected its spending on products designed to help customers manage the complexity of AI- and LLM-based software. It invests more than USD $1 billion a year in research and development on a non-GAAP basis, according to the company.
That work includes support for open-source projects such as OpenTelemetry and OpenLineage, as well as tools for incident investigation, application performance monitoring and oversight of AI agents.
Yanbing Li, Chief Product Officer at Datadog, linked the ranking to that broader investment strategy.
"We believe being recognised as a Leader for the sixth consecutive year reflects the depth of investment Datadog has made in helping teams navigate the complexity of building AI- and LLM-powered applications," said Li. "Datadog invests more than $1 billion in R&D (non-GAAP) annually - from contributions to OpenTelemetry and OpenLineage to the capabilities we ship every day - because our customers need answers, not more complexity."
Customer use
Datadog also pointed to customer examples to show how its products are being used in production environments. Experian Consumer Services said it uses Datadog's software to monitor customer-facing products and assess the performance of its AI chatbot, EVA.
"Datadog gives our teams real-time visibility into how customers experience our products, allowing us to identify and resolve issues before they impact end users," said Daniel Perschonok, VP of Cloud, Data, & Security Services at Experian Consumer Services. "When we launched our AI chatbot, EVA, LLM Observability provided immediate insight into model performance and customer interactions, helping us deliver a stable, high-quality AI experience from day one."
Datadog also cited user reviews posted on Gartner Peer Insights. One Software Developer at a healthcare and biotech company described the product as a way to consolidate monitoring tools.
"Datadog has been a game changer for us as we moved from a diversified set of products to a single unified platform for all of our observability needs. We are better, faster and more aligned as a technology org throughout the entire development lifecycle and beyond."
Other reviews highlighted AI-related features and the pace of product updates. An IT Associate at an IT services company said Datadog's Bits AI tool had improved troubleshooting and debugging, while a Director of IT at a travel and hospitality company said new AI-related features had made the product more useful over time.
Product focus
Among the products Datadog highlighted were Bits Investigation, which examines alerts and seeks to identify root causes, and Agent Observability, which monitors the performance, quality, security and cost of AI agents and LLM applications. It also pointed to its application performance monitoring tools and digital experience monitoring products, which connect front-end user activity with back-end systems.
Datadog's broader pitch is that a single platform can bring together development, IT operations, security and business teams around a shared set of system data. That approach reflects a wider trend in enterprise software, where suppliers are trying to reduce the number of separate monitoring and security tools customers need to manage.
The observability market has become more crowded as established infrastructure software groups compete with cloud-native vendors and newer AI-focused entrants. Rankings such as Gartner's Magic Quadrant remain closely watched by large corporate buyers, even though suppliers often use them as a marketing tool and the methodology is sometimes debated within the industry.
For Datadog, a sixth straight Leader ranking provides another reference point as it competes for customers seeking to monitor increasingly complex software estates spanning cloud infrastructure, applications, data systems and AI models.
"The product has become more useful every year and with the age of AI, we are seeing more useful features being introduced almost monthly. We also appreciate that the account team is very engaged with the enterprise and the product engineering team turns around feedback quickly."