Thousands of customers love & trust Datadog
Amazon Web Services (AWS) is a widely adopted cloud platform for building and managing global-scale applications. It’s used by companies of all sizes—from start-ups looking to reduce upfront infrastructure cost, to enterprises aiming to build and release products to market faster. AWS provides the ability to deploy distributed, scalable infrastructure, but it also introduces complexity as companies need visibility into every layer of their infrastructure to efficiently diagnose performance issues.
Datadog collects and unifies all of the data streaming from these complex environments, with a 1-click integration for pulling in metrics and tags from over 70 AWS services. Companies can deploy the Datadog Agent directly on their hosts and compute instances to collect metrics with greater granularity—down to one-second resolution. And with Datadog's out-of-the-box integration dashboards, companies get not only a high-level view into the health of their infrastructure and applications but also deeper visibility into individual services such as AWS Lambda and Amazon EKS.
When migrating applications to AWS or other platforms, companies often refactor them to leverage the flexibility and scalability of the cloud. This requires teams to choose the right services to support their architecture in order to decrease friction during the migration. Datadog enables teams to seamlessly track the performance of their services side-by-side in every stage of a migration, so they can ensure expected benchmarks are met. And with 400+ integrations, Datadog can monitor even more of the application services companies rely on during a migration, including those not deployed on AWS.
Teams can use the Host Map to monitor real-time data such as CPU utilization and network throughput for all hosts across availability zones to visualize performance before, during, or after a migration.
With machine learning–driven features such as forecasting, teams can address problems with applications before they significantly impact customers. For instance, teams can forecast memory usage on newly migrated EC2 instances and scale their infrastructure resources accordingly.
As organizations migrate from on-premise to hybrid or multi-cloud environments, they often rely on multiple monitoring tools for end-to-end visibility. This can create data silos and limits teams in their ability to troubleshoot issues and successfully migrate to another platform. Datadog unifies observability data from any host and service, providing comprehensive, cross-platform visibility into critical applications. Teams can visualize the dependencies between databases, APIs, containers, and more with Datadog's Service Map, enabling them to easily monitor the data flowing from on-premise to AWS or multi-cloud architectures.
Ephemeral infrastructure platforms such as Amazon ECS and AWS Lambda can auto-scale to support application traffic, creating new resources to meet demand or downsizing them to remove excess capacity. Legacy monitoring tools are often not able to capture data from these dynamic environments without additional configuration. Datadog integrates with services like AWS Lambda and Fargate to collect real-time data for full visibility, and automatically scales with infrastructure by monitoring resources as soon as they spin up. And with native integrations for services such as AWS CloudFormation, Chef, and Terraform, organizations can leverage their existing tools to deploy and configure Datadog on new application resources instantly.
Having the ability to share critical information and context across the organization is key for ensuring customer satisfaction and strengthening internal buy-in for adopting AWS services. A single source of truth instills confidence in an organization's ability to rapidly resolve incidents. Datadog offers comprehensive, collaboration-friendly tools that every team within an organization can use to review and share information. This enables them to easily visualize the connections between their application services, collaborate on real-time data, and troubleshoot issues faster.