Datadog Case Studies Complete Observability of IoT Systems

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	Complete Observability of IoT Systems Datadog

Complete Observability of IoT Systems

Datadog

Technology Category	Analytics & Modeling - Real Time Analytics Processors & Edge Intelligence - Embedded & Edge Computers
Applicable Industries	Cities & Municipalities Transportation
Applicable Functions	Logistics & Transportation Maintenance
Use Cases	Edge Computing & Edge Intelligence Real-Time Location System (RTLS) Vehicle Telematics
Services	Cloud Planning, Design & Implementation Services Data Science Services System Integration
Challenge	Automotus, a curb management company, was facing challenges with their IoT devices and scaling cloud resources. They needed a robust monitoring solution that would provide visibility into their IoT devices, as well as their scaling cloud resources. Their manual and reactive approach to monitoring was proving to be inefficient. They were unable to collect important hardware metrics, such as network throughput, I/O load, and memory, which meant they often missed the first signs of degraded device performance. If their devices stopped sending messages, they were forced to SSH into the system and sort through logs by hand, which was an extremely time-consuming process that required all hands on deck. They also didn't have visibility into the management and backend services that are crucial to their system, such as AWS IoT Core. These problems were compounded by the absence of a centralized platform to view and analyze this data in context. The resulting blind spots stymied their troubleshooting process, leaving them to cross their fingers that nothing would go wrong. Read More
About Customer	Automotus is a curb management company that leverages computer vision software running on edge devices to help cities, fleets, and businesses increase revenue while making streets less congested, more sustainable, and more equitable. The core of Automotus's business relies on IoT devices, and if those devices fail, their business grinds to a halt. It's therefore essential for Automotus to have total visibility into the health and performance of these devices, as well as the downstream applications and services that support them. Harris Lummis, CTO and Co-founder of Automotus, recognized this need and began the search for a comprehensive monitoring solution for Automotus's growing IoT system. Read More
Solution	Automotus decided to contact Trek10, a Datadog Gold tier partner and an AWS-focused service provider with specialized expertise in next generation infrastructure. It was through their conversations with Trek10 that Automotus first realized how Datadog's minimal overhead, low-maintenance approach to IoT monitoring could transform their engineering organization. Datadog's IoT Agent, together with IoT integrations with technologies such as AWS IoT Core, would allow them to view critical performance data from their NVIDIA Jetson-based devices alongside metrics, traces, and logs from their entire IoT ecosystem. Additionally, Datadog's unified platform would allow them to eliminate blind spots and streamline their troubleshooting process, freeing up their engineers to spend more time building and enhancing their core product. With the help of Trek10, Automotus was able to onboard and ramp up with Datadog in no time. Trek10 deployed the Datadog IoT Agent to Automotus’s devices and enabled the integrations for the AWS services they rely on, giving them unprecedented visibility into their entire system. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Real Time Analytics

Processors & Edge Intelligence - Embedded & Edge Computers

Applicable Industries

Cities & Municipalities

Transportation

Applicable Functions

Logistics & Transportation

Maintenance

Use Cases

Edge Computing & Edge Intelligence

Real-Time Location System (RTLS)

Vehicle Telematics

Services

Cloud Planning, Design & Implementation Services

Data Science Services

System Integration

Challenge

Automotus, a curb management company, was facing challenges with their IoT devices and scaling cloud resources. They needed a robust monitoring solution that would provide visibility into their IoT devices, as well as their scaling cloud resources. Their manual and reactive approach to monitoring was proving to be inefficient. They were unable to collect important hardware metrics, such as network throughput, I/O load, and memory, which meant they often missed the first signs of degraded device performance. If their devices stopped sending messages, they were forced to SSH into the system and sort through logs by hand, which was an extremely time-consuming process that required all hands on deck. They also didn't have visibility into the management and backend services that are crucial to their system, such as AWS IoT Core. These problems were compounded by the absence of a centralized platform to view and analyze this data in context. The resulting blind spots stymied their troubleshooting process, leaving them to cross their fingers that nothing would go wrong.

About Customer

Automotus is a curb management company that leverages computer vision software running on edge devices to help cities, fleets, and businesses increase revenue while making streets less congested, more sustainable, and more equitable. The core of Automotus's business relies on IoT devices, and if those devices fail, their business grinds to a halt. It's therefore essential for Automotus to have total visibility into the health and performance of these devices, as well as the downstream applications and services that support them. Harris Lummis, CTO and Co-founder of Automotus, recognized this need and began the search for a comprehensive monitoring solution for Automotus's growing IoT system.

Solution

Automotus decided to contact Trek10, a Datadog Gold tier partner and an AWS-focused service provider with specialized expertise in next generation infrastructure. It was through their conversations with Trek10 that Automotus first realized how Datadog's minimal overhead, low-maintenance approach to IoT monitoring could transform their engineering organization. Datadog's IoT Agent, together with IoT integrations with technologies such as AWS IoT Core, would allow them to view critical performance data from their NVIDIA Jetson-based devices alongside metrics, traces, and logs from their entire IoT ecosystem. Additionally, Datadog's unified platform would allow them to eliminate blind spots and streamline their troubleshooting process, freeing up their engineers to spend more time building and enhancing their core product. With the help of Trek10, Automotus was able to onboard and ramp up with Datadog in no time. Trek10 deployed the Datadog IoT Agent to Automotus’s devices and enabled the integrations for the AWS services they rely on, giving them unprecedented visibility into their entire system.

Impact #1	Datadog's integrations with key IoT technologies, such as AWS IoT Core, PostgreSQL, and RabbitMQ, enabled Automotus to get immediate visibility into the services that are crucial to their system.
Impact #2	Trek10 helped Automotus build custom dashboards for device-level data collected by the IoT Agent. By viewing crucial system and performance metrics alongside logs and events, they are now able to get a high-level overview of device health and activity across their fleet.
Impact #3	With Datadog, Automotus could set up sophisticated alerts for their entire fleet of devices, as well as their downstream services, ensuring that they only receive alerts for sustained, legitimate failures.

Impact #1

Datadog's integrations with key IoT technologies, such as AWS IoT Core, PostgreSQL, and RabbitMQ, enabled Automotus to get immediate visibility into the services that are crucial to their system.

Impact #2

Trek10 helped Automotus build custom dashboards for device-level data collected by the IoT Agent. By viewing crucial system and performance metrics alongside logs and events, they are now able to get a high-level overview of device health and activity across their fleet.

Impact #3

With Datadog, Automotus could set up sophisticated alerts for their entire fleet of devices, as well as their downstream services, ensuring that they only receive alerts for sustained, legitimate failures.

Benefit #1	3x Increase in firmware release cadence.
Benefit #2	50% Reduction in troubleshooting time for edge devices.
Benefit #3	100% Increase in the number of devices in production.

Benefit #1

3x Increase in firmware release cadence.

Benefit #2

50% Reduction in troubleshooting time for edge devices.

Benefit #3

100% Increase in the number of devices in production.

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Overview

Complete Observability of IoT Systems

Operational Impact

Quantitative Benefit