APM vs. Observability & the best solution
The APM journey begins
Digital transformation is accelerating. IT environments are becoming more powerful, more adaptable, and more complex. Therefore, enterprises are turning to application performance monitoring (APM) and observability to deliver reliable, real-time visibility across technology stacks.
But APM isn’t a silver bullet. To deliver on its potential, organizations need to recognize key challenges, understand their impact, and implement strategies that help to unlock the power of APM and drive the journey toward observability.
What is application performance monitoring (APM)?
Application performance monitoring is the process of tracking and collecting key software metrics to pinpoint potential problems and identify opportunities for improvement. Historically, APM platforms have provided insight into application traces and spans so IT teams can increase system availability, optimize service performance, reduce response times, and improve the user experience. More recently, companies have turned to observability technologies, which include traces and spans and further incorporate other telemetry sources, such as metrics, logs, and business events.
APM is a core aspect of observability that helps companies shift from observing their IT environments to acting. While continual monitoring of application telemetry data helps organizations understand what’s happening across software stacks, monitoring tools enable teams to identify targeted actions that address existing problems or optimize current processes.
Capabilities of APM and Observability Tools
According to the research company Gartner, the capabilities of APM and Observability Tools include:
- The observation of an application’s complete transactional behavior
- Native integration capabilities with automation and service management tools, as well as native integration with public cloud providers
- Automated discovery and mapping of an application and its infrastructure components (including cloud services)
- Analysis of key performance indicators (KPIs) and user journeys — for example, login to check-out
- Monitoring of applications running on mobile (native and browser) and desktop browsers
- The ability to perform interactive interrogation of multiple telemetry types (such as traces, metrics, and logs) to detect “unknown unknowns” — that is, the ability to indentify underlying issues to unexpected events and gaps in telemetry coverage
- Identification and analysis of application performance problems and their impact on business outcomes
- Application security functionality delivered via a common agent or framework for APM
How does APM compare to observability?
While APM and observability are similar, they’re not identical. Observability is the ability to measure a system’s current state based on the data it generates, such as logs, metrics, and traces. It requires the real-time collection of data from multiple sources, the analysis of this data, and the resulting investigative action taken once patterns in data are identified. Observability is a dynamic practice that changes over time in response to both current conditions and evolving operations. It is critical to ensure consistent software and service performance.
Meanwhile, APM is one process within the larger scope
of observability. By collecting and curating data about application performance, connections, and interactions, APM tools make it possible to pinpoint potential problems and streamline application integration. As a result, even the most advanced APM capabilities can take companies only so far if they’re not connected to larger observability frameworks. Put another way, while APM offers visibility into the operation of critical components, observability provides the big picture.
Challenges for effective Application Performance Monitoring
APM is a framework to improve application monitoring and management and is typically paired with observability to get the most complete coverage and benefits. However, it isn’t a cure-all. The sheer volume of cloud-connected services, mobile applications, and local devices provide a near-infinite reservoir of data that can help companies identify what’s happening across their application stack and make changes that improve overall performance. However, the transition from framework to function comes in using this data to the best effect. In practice, five challenges can frustrate APM efforts:
- Inconsistent instrumentation and maintenance
If services aren’t consistently maintained and updated, APM data could be inaccurate and out of date, in turn reducing their value to the organization - Reliance on siloed tools
While it often makes sense for teams to use customized tool sets that help them achieve specific goals, individual tool sets can fuel a larger problem: silos. - Lack of decision-making context
Simply collecting data about what entities are doing and the data they’re exchanging is the first step to better decision making. But if teams don’t understand the why behind the what, it’s almost impossible to see the bigger picture. - Missing links to business impacts
APM data offers insight into current operations: How are applications performing? Where are conflicts occurring? What issues are isolated, and which are repetitive?
What APM can’t tell companies is how much of an impact these issues have on end users. If teams can’t get their work done because apps aren’t working as intended, businesses may lose time and money. - Separation of symptoms and root causes
It’s critical to go beyond basic APM with integrated AI capable of finding relevant data quickly and jumping the gap between cause and effect.
The solution
APM is now a must-have for organizations to understand incidents within disparate technology stacks — but challenges remain. With the Dynatrace observability platform, companies can tackle these challenges head-on. Key components of Dynatrace APM include the following:
- Integrated observability platform
APM tools are often standalone services that capture key data about application and microservice operations and little else. Meanwhile, the Dynatrace platform captures metrics, traces, logs, and business data to provide complete coverage. It uses artificial intelligence and automation to deliver a precise, context-aware analysis of the complete application environment, regardless of app or service location. - End-to-end visibility
While APM provides key insights into service operations, traditional logs and metrics are also critical for companies to gain complete visibility. Dynatrace PurePath automatically captures and analyzes transactions end to end across every tier of your application stack to provide code-level visibility into web apps, mobile apps, microservices, and serverless functions. At the same time, Dynatrace also captures metrics and log data and automatically contextualizes all these telemetry sources to provide instant answers — not just more data. - AI-enabled analysis
Data without context won’t deliver desired outcomes. Powered by the Davis AI engine, the Dynatrace observability platform lets companies connect the dots to discover key dependencies, visualize app topologies, and automatically detect anomalies.
You want to know more about APM and Observability? Or do you consider implementing the Dynatrace solution in your company but you don’t know how to start? Then contact us – we will be glad to support you with our expertise as Dynatrace Premier Partner!
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