Datadog Entered India Late; Now it Wants to Make up for Lost Ground

Datadog may have entered India later than some of its competitors, but the observability company is now betting heavily on the market, expanding its workforce, customer base and partner ecosystem.

The company launched its India operations a little over two years ago, initially establishing its presence in Bengaluru before expanding its sales footprint to Delhi and Mumbai. It now has more than 400 customers, over 40 active partners and more than 140 employees in the country.

"If you look at total revenue, we are actually number two in core observability. Now that means that obviously, the market recognises the value of the platform, but it also means that India doesn't just buy because of the product. India buys because you need feet on the street, you need relationships, you need a partner ecosystem, you need adoption, success, and so on.

“Even though Datadog entered the market late, we have invested heavily in local resources and now have the largest India employee base among competitors, with a full-fledged go-to-market organisation. We see India as a major growth market and will continue investing and hiring,” Namit D'Cruz, Datadog Regional VP, Enterprise- India & SAARC, told The Left Shift during a media roundtable in Bengaluru on August 11, 2026.

Indeed, the late entry has its disadvantages. Competitors had already established relationships and customer bases in India when Datadog arrived, but the company believes its product breadth and willingness to invest locally can help it close that gap.

Betting on India's software economy

The company is growing its India business at more than 30%, roughly matching its global growth rate. Customer retention and adoption are also tracking closely with Datadog's more mature markets.

The company sees India's developer ecosystem as a major reason for optimism. The country is already home to the second-largest developer ecosystem in the world, after the United States. According to the GitHub Octoverse 2025 report, India added more than 5.2 million developers last year and is poised to overtake the US in the coming years.

AI is making software development faster and cheaper, leading to more applications, platforms, and businesses being built. More software ultimately means more infrastructure to be observed and secured.

That dynamic could be particularly important in India because of its enormous concentration of software engineers and the continued expansion of startups, digital businesses and global capability centres.

Datadog's customer base reflects that diversity. Customers include Zomato, IndiGo, Mindtickle, Motilal Oswal, XpressBees, SG Analytics, and Asian Paints, among others.

The company said it is seeing adoption across modern cloud-native businesses as well as traditional enterprises, with customers spread across industries and regions

Rather than focusing solely on startups, Datadog said its addressable market is closely tied to cloud spending. The more a company digitises and moves critical services online, the greater its potential requirement for observability and security.

Hilal Ahmad, Liminal Custody CISO & VP, and a Datadog customer, also praised the platform during the roundtable, particularly its security capabilities and unified approach.

AI gives Datadog another opening

Datadog is also using the AI boom to broaden its pitch beyond traditional observability. At its recent Dash event, the company announced a plethora of product releases, with AI playing a central role. Its new capabilities are designed to detect incidents, investigate their causes and increasingly help remediate them.

For example, Bits Investigate is Datadog’s autonomous AI SRE agent that investigates production incidents, tests multiple root-cause hypotheses using telemetry, and helps engineers identify and remediate problems faster.

The company also announced Bits Code which helps developers identify and fix production code issues by using Datadog’s observability data. It can recommend code changes based on real-world performance, generate fixes, and create pull requests directly, helping teams move from identifying an issue to remediation faster.

However, the question that arises is how Bits Code compares with other coding tools such as OpenAI Codex and Anthropic’s Claude Code, which are already widely used by developers and enterprises—including many of Datadog’s own customers? The competition also extends to coding tools from enterprise data platforms such as Snowflake and Databricks, which similarly have significant overlap with Datadog’s customer base.

Anupam Kumar Jha, Datadog Technical Solutions Engineering Manager, who previously was with New Relic, one of Datadog's biggest competitors, argues that its access to production telemetry gives these capabilities an advantage over general-purpose coding assistants.

“Bits Code is not designed to replace other coding tools. Its difference is that it operates with Datadog’s production telemetry. While other tools look at code in isolation, we know its error rate, latency and performance in production. That allows us to recommend fixes based on actual performance data. We also integrate with IDEs and coding agents, making them more effective by adding production context," Jha told The Left Shift.

The company is also seeing demand for Agent Observability, which helps customers monitor their own AI applications, including performance, token consumption and GPU costs. Datadog said 10% of its global annual revenue now comes from AI-related business.

Interestingly, when The Left Shift asked Ahmad whether Liminal would adopt Datadog’s newer products, Ahmad did not give a definitive answer. He also highlighted cost as an important consideration when evaluating and expanding the platform’s use.

For Datadog, India's opportunity is therefore bigger than simply selling another monitoring tool. The company arrived after rivals had already established themselves, but believes India's accelerating software and AI development gives it a second chance to build a major market.

The challenge will be turning that opportunity into sustained adoption. Datadog appears to believe the answer lies in combining its expanding product portfolio with something it says Indian customers value just as much– people on the ground, local partnerships and long-term customer support.