Companies that use Datadog

lululemon Fidelity Investments Capital One U.S. Bank Wells Fargo SoFi ZoomInfo Samsara Block Procore Technologies

We dug into our own data to find which companies are using DataDog in production. We also corroborated and asked engineers in these companies to tell us how they're using Datadog. Here are real-world examples of how they use it.

lululemon

Retail -Vancouver, British Columbia

lululemon is a global athletic apparel company with stores and ecommerce operations across North America, Europe, and Asia. Running localized shopping experiences across dozens of markets means a lot of moving parts that need to stay healthy at all times.

Datadog is the primary observability platform across lululemon's entire engineering organization. The international digital commerce team uses it to watch over the infrastructure powering global shopping experiences. But it doesn't stop there. Datadog is also the observability layer behind their API gateway, mobile apps, inventory systems, CI/CD pipelines, and content delivery. Basically every engineering team at lululemon is running Datadog. Besides Datadog, Splunk sits alongside it for log analysis, and Quantametrics handles performance benchmarking.

Fidelity Investments

Financial Services -Boston, Massachusetts

Fidelity is one of the largest financial services companies in the US, managing trillions in assets for tens of millions of customers. With that many systems running in parallel, observability isn't a nice-to-have.

Datadog is woven through Fidelity's engineering stack across divisions. The most critical use is in brokerage recordkeeping, where it monitors Tier 0 and Tier 1 production systems, the ones where an outage is a serious incident. Beyond that, database engineers use it to watch over Oracle, Snowflake, and distributed database infrastructure. Software engineers use it to debug microservices. Network engineers use it for DNS traffic steering and load balancer health. And lastly, SRE teams use it for chaos engineering observability and incident response. Datadog is basically the observability layer the whole company runs on.

Capital One

Financial Services -McLean, Virginia

Capital One is one of the largest banks in the US, with tens of millions of credit card customers and a reputation for being unusually technology-forward for a financial institution. They went all-in on AWS years ago, and their engineering culture reflects that.

Datadog is a standard part of the observability stack across the organization. Software engineers use it to monitor and debug microservices across enterprise platforms that handle hundreds of millions of transactions. When something goes wrong, SRE teams lean on it for incident response and reliability monitoring.

It goes beyond just keeping things running though. Performance engineers use it for distributed tracing to debug cross-service workflows, and network engineers use it to monitor traffic routing and load balancer health. Even ML and DevOps teams use it to watch over model governance pipelines.

The footprint spans consumer banking, payments, the global payment network, and enterprise platform infrastructure. Splunk sits alongside it for log aggregation.

U.S. Bank

Financial Services -Minneapolis, Minnesota

U.S. Bank is the fifth largest commercial bank in the US, serving consumers, businesses, and institutions across thousands of branches and digital products.

Datadog runs across a wide range of engineering teams. The card management team uses it to monitor API performance and reliability for credit card lifecycle operations. From there it spreads into performance engineering, where teams use Datadog APM specifically to track microservice latency and run root cause analysis on mobile and online banking applications.

Data engineers use it to monitor AWS-based pipelines, while reliability engineering teams use it for APM and logging across distributed systems. Their fintech spend management product for small businesses uses it for observability, and DevOps teams use it for synthetic transaction monitoring.

Splunk and AppDynamics sit alongside it depending on the team, but Datadog shows up consistently as the core monitoring layer across divisions.

Wells Fargo

Financial Services -San Francisco, California

Wells Fargo is one of the largest banks in the US, serving roughly one in three American households across consumer banking, commercial banking, wealth management, and payments.

Datadog runs across a wide range of engineering teams. Software engineers use it to monitor and debug microservices across core banking and enterprise platforms. When incidents occur, SRE and DevOps teams lean on it for observability, alert tuning, and SLI/SLO tracking -the kind of work that keeps high-stakes production systems from quietly degrading.

Infrastructure engineers use it alongside Grafana and Prometheus to monitor the health of large-scale middleware platforms, including Kafka and Solace messaging systems that route transactions across the bank. Performance engineers use it for APM across mobile and online banking applications, tracking latency and bottlenecks before customers feel them.

It also shows up in Wells Fargo's growing AI and automation engineering work, where teams building GenAI-powered workflows use it as part of their observability stack. Splunk and AppDynamics sit alongside it depending on the team, but Datadog appears consistently as a core layer across divisions.

SoFi

Financial Services -San Francisco, California

SoFi is a next-generation bank and personal finance company serving millions of members across lending, investing, credit cards, and banking. Unlike traditional banks, they built their technology stack from scratch, which means they get to choose their tools carefully.

Datadog is baked into the standard engineering stack across the organization. Software engineers use it to monitor microservices across lending, credit card, and identity platforms. When the Digital Identity team -the group that handles who every customer is and what they can access -built their foundational services, Datadog was part of the core tech stack from day one alongside Kubernetes and Snowflake.

It goes well beyond just keeping services up. The ML platform team uses it to monitor model pipelines for fraud detection and risk. The risk data engineering team uses it to enforce data quality SLAs and catch pipeline reliability issues before they become problems. Compliance data scientists even use it for data monitoring on their anti-money laundering systems.

Cloud platform engineers use it for observability across their AWS and Kubernetes infrastructure. The loan originations team uses it alongside Kafka and Kubernetes for production monitoring. It runs deep across lending, identity, fraud, risk, and compliance -pretty much wherever SoFi builds something critical, Datadog is there watching it.

ZoomInfo

Software Development -Waltham, Massachusetts

ZoomInfo is basically a giant database of business contacts and company info that sales teams use to find customers. Think of it like a supercharged LinkedIn for prospectors. Over 35,000 companies use it, and keeping that running means a big multi-cloud setup across AWS and GCP.

Datadog is how they watch all of it. DevOps and infrastructure engineers use it to keep tabs on their Kubernetes clusters and data pipelines. SRE teams use it for incident management and real-time dashboards -basically their "is everything on fire right now" screen.

Backend engineers use it to instrument their microservices and debug production issues. The data platform team uses it specifically for the streaming pipelines -Kinesis, Pub/Sub, BigQuery -the stuff that actually powers the intelligence product.

But here's the thing that stood out to me. It's not just an engineering tool at ZoomInfo. The customer support team uses Datadog too -directly. When a customer calls in saying something looks broken, support staff are literally opening Datadog to figure out what's going wrong on the application side. That's pretty rare. Most places keep observability tools firmly inside engineering. ZoomInfo uses it across the whole org.

Samsara

Software Development -San Francisco, California

Samsara makes software that connects physical operations to the cloud. Think fleets of trucks, construction equipment, food delivery vehicles. Over 2.3 million IoT devices send data through their platform in real time, and tens of thousands of companies depend on it to keep workers safe and operations running. When something breaks, it's not just a website going down. It's a fleet of trucks going dark.

That context makes observability a serious investment. Samsara has a dedicated Operational Excellence team inside their Developer Experience organization, and their job is specifically to build monitoring frameworks, SLO platforms, and automated reliability systems across the engineering org. Datadog is the named tool of choice for that work.

From there it reaches across engineering. Data engineers use it to monitor AWS-based pipelines that feed analytics and operational data across the company. The data platform team uses it alongside CloudWatch to keep their Databricks workspaces and underlying AWS infrastructure healthy. Operations and support teams use it to watch over their ecommerce and go-to-market systems.

The scale of what Samsara monitors makes Datadog's footprint here genuinely meaningful. They're not just tracking microservice latency, they're watching systems that directly affect whether physical operations in the real world stay online.

Block

Financial Services -San Francisco, California

Block is the company behind Square, Cash App, Afterpay, and a handful of other financial products. Think of it as a family of fintech brands all built on the same underlying infrastructure. Square helps small businesses take payments. Cash App lets 50 million people send money, invest, and borrow. Together they're processing billions of dollars every week.

With that kind of money moving through their systems, reliability isn't optional. Datadog is how Block watches all of it. It's listed as a core technology on pretty much every engineering team across the company -Cash App payments, bank rails, lending, the card product, bitcoin trading, trust and safety, customer support tooling, CI infrastructure. It's not a departmental tool, it's the standard.

The SRE team uses it to run on-call for Block's most critical Tier 0 services. When something goes wrong at 3am with a payment system handling millions of transactions, Datadog is what's on the screen. The bitcoin trading team specifically calls it out as how engineers maintain visibility into systems and business operations during on-call shifts.

What's interesting about Block is the breadth. It's not just infrastructure engineers using Datadog, it's product engineers building Cash App Card, engineers managing the ledger that processes millions of transactions daily with zero tolerance for errors, and embedded engineers monitoring Bitcoin mining hardware. Wherever Block builds something that needs to stay up, Datadog is watching it.

Procore Technologies

Software Development -Carpinteria, California

Procore makes the software that runs construction projects. Over 3 million projects across 150 countries have been managed on their platform -skyscrapers, hospitals, airports, housing developments. When a general contractor on an active job site loses access to Procore, work stops. That kind of customer base makes reliability a serious priority.

Datadog sits at the center of how Procore watches their systems. Incident commanders use it directly when managing major production incidents across their global infrastructure. Platform engineers use it as a core tool alongside Terraform and Kubernetes. DevOps engineers use it for monitoring CI/CD pipelines and mobile infrastructure. Performance engineers use it to profile and debug bottlenecks. There's even a whole dedicated team of Observability Analysts running 24x5 out of Bangalore and Pune, whose entire job is monitoring the platform and keeping it healthy.

What really stands out about Procore is how seriously they've invested in observability as a discipline. They have a dedicated Observability Enablement team whose job is to embed with product engineering teams across the company and help them instrument their services with OpenTelemetry, piping everything into Datadog. The explicit goal is moving teams from "blind" to "informed" and Datadog is the destination.

It's a meaningful use case for an industry most people don't associate with cutting-edge software infrastructure. Construction companies don't think about SLOs. Procore does, on their behalf.