Azure IoT Edge is a Microsoft Azure service that allows you to run containerized workloads on IoT devices. With IoT Edge and Azure IoT Hub, Azure’s device-management platform, organizations across science, manufacturing, energy production, and other industries can provision their IoT devices and workloads at the edge of their cloud networks for immediate in-unit computing, a necessity when running AI algorithms or parsing large datasets directly on IoT devices.

Modern datacenters can contain thousands of network appliances, such as routers, switches, firewalls, and servers, so it’s important for your monitoring strategy to provide comprehensive visibility into every piece of your infrastructure. Datadog Network Device Monitoring already allows you to collect a wealth of telemetry from all of your SNMP-managed devices, which are automatically discovered by the Datadog Agent.

Istio is an open source service mesh that provides an abstraction layer for network traffic between applications, so you can run canary deployments, implement circuit breakers, and otherwise manage the architecture of your network using high-level configuration files. As service meshes become increasingly popular among containerized environments, dev and ops teams need to ensure that Istio is healthy, performant, and routing traffic as intended to keep their network infrastructure running smoothly.

Serverless platforms like AWS Lambda have helped accelerate application development by removing the need to provision and manage infrastructure resources. However, serverless architecture presents new monitoring challenges. Because AWS Lambda handles underlying infrastructure for you, you don’t have access to system-level metrics. Instead, you have to monitor your Lambda functions for insight into their performance and resource usage.

NVIDIA Jetson is a family of embedded, low-power computing boards designed to support machine learning and AI applications at the edge. Organizations use Jetson boards for complex video and image processing and analysis, automating build processes in factories, and improving city infrastructures. For example, Jetson-based devices enable cities to analyze traffic patterns with their existing traffic cameras in order to find ways to improve their most congested intersections.

Since 2018, Watchdog has provided automatic, machine learning-based anomaly detection to notify you of performance issues in your applications. Earlier this year, Watchdog started grouping APM anomalies across your services, allowing you to better understand the scope of the issue.

Kubernetes continues to be a popular platform for deploying containerized applications, but securing Kubernetes environments as you scale up is challenging. Each new container increases your application’s attack surface, or the number of potential entry points for unauthorized access. Without complete visibility into every managed container and application request, you can easily overlook gaps in your application’s security as well as malicious activity.

If you are running a user-facing web application, you likely implement some form of authentication flow to allow users to log in securely. You may even use multiple systems and methods for different purposes or separate groups of users. For example, employees might use OAuth-based authentication managed by a company-provided Google account to log in to internal services while customers can use a username and password system or their own Google credentials.

Datadog dashboards provide a unified view of your application, infrastructure, and business data, giving stakeholders the context they need to make decisions. Sharing dashboards publicly is useful when you want to make them easily accessible to a large audience. But oftentimes, your dashboards include sensitive information, which is why you need finer-grained controls over the data you share—and who you share it with.