Digital Experience Monitoring is a category of performance analysis technologies that provides visibility into the end-user experience, or what analyst firm Gartner calls the “omnichannel user journey.” That’s a fancy way of saying how the users behave as they interact with on-prem and cloud applications to do their job.
Application developers are beginning to recognize the value that DEM can bring to the end-user experience. For this reason, many DevOps teams are building in APIs early in the software development life cycle as part of the testing process of new releases. These APIs allow DEM systems to properly measure the performance of the end-user experience and the underlying application components. These more modern solutions are especially sought after by infrastructure and operations leaders because they want to use DEM to regain insight into the performance of applications as they migrate to the cloud.
Network engineers also recognize the value of DEM. The performance of the network directly impacts the digital experience of application users. For this branch of DEM, synthetic traffic is generated to proactively measure network performance for packet loss, latency and jitter.
Since DEM can be used to measure the performance from the user’s point of view, the data collected can help uncover the impact that degraded performance can have on the business. We’re talking about everything from revenue generation to brand reputation and customer loyalty.
There are three primary technology components that make up DEM:
Synthetic monitoring uses agents to proactively test services such as SaaS applications like Salesforce and API endpoints. Unlike Real User Monitoring (described below), STM isn’t generally run against active users, although it could be. Its mission is usually intended to test the hosted or SaaS application (e.g., Salesforce, Office 365).
Synthetic monitoring techniques typically involve running a mix of HTTP commands (POST, GET, PUT or DELETE) on a regular and periodic basis. However, deeper testing can also be done on connection times and database query speeds. Depending on the synthetic monitoring solution in use, the frequency of such testing can vary from daily, hourly, or even down to one second intervals.
Metrics on response times, packet loss, jitter, and transaction times are gathered and sent off to the DEM collection platform where correlations are performed. With integrated DEM and NPMD (Network Performance Monitoring and Diagnostics), tests can be performed across different forms of telemetry like NetFlow, sFlow, VPC logs and even SNMP counters. AIOps techniques can be applied to get deeper insights as to why there is an application performance problem.
Endpoint Monitoring provides visibility into the user devices and performance testing from the endpoint. This includes things like the version of the operating system, CPU and memory usage, storage space and network metrics. While it can seem similar to desktop inventory software, the focus is on continued performance and availability.
DEM and synthetic monitoring technologies can be applied to solve a variety of application and network infrastructure problems, reduce costs, and improve visibility into network and application performance. Key use cases include:
Synthetic tests conducted by a DEM solution will ideally be performed from multiple geographic locations in order to identify problems with specific network links and understand performance metrics with respect to users in different regions.
For example, Kentik has built out a global network of synthetic testing agents that are used by customers to verify performance levels of all major public or private cloud-based applications and SaaS applications. These agents have been located inside Amazon Web Services, Google Cloud Platform, Microsoft Azure, Alibaba Cloud, IBM Clouds and these vantage points keep growing.
The Kentik Network Observability Cloud offers a modern, SaaS-based approach to digital experience monitoring. Kentik delivers network performance monitoring and diagnostics that combine flow-based monitoring, cloud network observability and synthetic monitoring features to enable for proactive monitoring of all types of networks.
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