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Companies managing large fleets of distributed IoT devices must contend with a torrent of telemetry data from individual devices, which are often globally dispersed and built on multiple software and hardware platforms. In these environments, interruptions in the flow of data from any one source may indicate a device failure, an application-level performance problem, or a regional network issue.
To reliably operate their IoT fleets, companies need a comprehensive view of the health of their devices in aggregate, as well as the ability to drill down to troubleshoot a particular region, device type, software version, or individual device. Datadog provides top-to-bottom IoT monitoring for device fleets, with the ability to aggregate performance metrics by any dimension and at any level of granularity. Companies can monitor IoT software performance, device hardware metrics, application logs, network performance data, and more, all in a single pane of glass.
With comprehensive tags that apply to all telemetry data, Datadog enables companies to aggregate, slice and dice, and correlate performance data across the fleet. Datadog's host map provides a bird's-eye view of the entire IoT device fleet, grouped by any tag for a visual comparison of performance by region, software version, or operating system. Alerts, graphs, and dashboards can be precisely scoped with user-specified tags to provide visibility and actionable notifications for any subset of devices. And when issues arise, unified tagging provides seamless correlation between system-level metrics, distributed traces, network performance data, and logs for rapid troubleshooting.
Datadog's fully hosted SaaS platform enables companies to start monitoring IoT devices in minutes, without extensive configuration or setup, then scale to tens of thousands of monitored devices effortlessly.
The sheer volume of telemetry data from IoT devices, coupled with the intermittent connectivity issues of a distributed fleet, pose a challenge for traditional alerting tools. Datadog's alerting capabilities for IoT monitoring are sophisticated and customizable enough for even the most dynamic, decentralized networks of devices. IoT fleet operators can build alerts that trigger only on sustained or widespread device failures, so that responders are not overwhelmed by meaningless alerts for transient issues. Machine learning algorithms such as anomaly detection and outlier detection automatically determine normal ranges and alert only on unusual occurrences, such as latency slowdowns affecting a particular software version.
IoT devices rarely run off-the-shelf software but instead perform functions that are unique and vital to the business. Whether they serve as point-of-sale terminals, distributed sensors, or industrial machinery, IoT devices often collect mission-critical operational data or handle custom business logic. Datadog enables companies to collect, analyze, and visualize this business-level data from IoT devices alongside health and performance metrics from the devices themselves. With robust APIs and telemetry libraries for virtually every language and framework, Datadog makes instrumentation simple and efficient. By adding just a few lines of code, developers can start collecting and analyzing custom business metrics in the same platform that they use to monitor IoT devices, distributed applications, and the rest of their IT infrastructure.
To bring visibility to diverse IoT fleets, Datadog can be installed on nearly any hardware platform and operating system, including Linux, Windows, Android, and ARM devices. On every device, the lightweight Datadog Agent collects metrics, distributed traces, logs, and more for centralized monitoring and analytics. Datadog's Logging without Limits™ enables companies with large device fleets to manage and monitor their logs cost-effectively. Companies can send all their logs to Datadog for real-time visibility, then generate metrics that summarize log contents and dynamically retain high-value logs for long-term analytics.
Organizations that run IoT devices using a managed cloud service can visualize all their data using Datadog's fully supported integrations for IoT monitoring, including Amazon IoT, Google Cloud IoT, and Azure IoT Hub. Regardless of the source, Datadog brings together all the operational data required for monitoring IoT devices in an intuitive platform for visualization, analytics, correlation, and alerting.
