Real User Monitoring (RUM) Vs Application Performance Monitoring (APM) Difference

In the heart of the end user experience in an application, where every click, swipe, and tap weaves the fabric of modern experiences, there lies often-unseen intermittent performance problems. Moreover, as data volumes and infrastructure complexity skyrocket, enterprises recognize their traditional monitoring tools need to be updated and more for clickstream analysis. 

Meet Alex, a seasoned IT administrator whose day-to-day life is a testament to the page load or UI render issues. The challenges come with ensuring an optimal and real-world observability into web performance, service availability, user experience and maintaining application performance.

As the holiday shopping season approaches, the pressure of heavy traffic mounts on the company website and web application, and the fragility of the balance Alex must maintain becomes all too apparent.

Alex understands that in the digital arena, loyalty is won and lost at the speed of a page load. 

A slow, unavailable, or difficult-to-navigate application doesn’t just represent a temporary hiccup in the user experience; it’s an open invitation for the user to seek alternatives. Competitors are always lurking, ready to offer a smoother, more engaging digital experience to those disillusioned by less-than-optimal interactions. 

To collect and analyze a deluge of data from myriad user interactions—each click, hover, and scroll offering insights to identify and rectify user-facing issues, backend metrics, traces, logs, optimize content delivery, network performance data, and tailor experiences to meet user expectations.

On the other side of the spectrum lies the labyrinthine workings of backend resources, i.e., the intricate dance of:

  • servers, 
  • databases, and 
  • external services. 

The complexity of modern applications, with their microservices and distributed architectures, makes pinpointing performance and multi-tiered analysis bottlenecks akin to finding a needle in a haystack. 

Amidst the highs and lows of Alex’s quest to safeguard the digital realm, we come across two pivotal allies in his journey: 

  1. Real User Monitoring (RUM) and 
  2. Application Performance Monitoring (APM). 

Though distinct in their focus and methodologies, these technologies unite under the standard banner of observability, serving as the twin pillars of understanding and enhancing the digital experience.  

RUM vs. APM – What is the connection?

Real User Monitoring (RUM) and Application Performance Monitoring (APM) are two pivotal technologies in digital observability, each playing a distinct yet complementary role in ensuring the optimal performance and user experience of web applications. 

Source

Understanding the nuances of RUM and APM highlights their differences and illustrates how they work together to create a holistic view of application health.

So, what is Real User Monitoring (RUM)?

Real User Monitoring technology refers to measurement, analysis and performance monitoring  the user’s interaction journey with a website or web application in real-time. 

Using small bits of JavaScript, it captures data directly from the user’s browser or device as they interact with an application, offering insights into how real-world conditions—such as device type, browser, network speed, and geographical location—affect the user experience. 

RUM focuses on end-to-end transaction reporting and metrics like:

  • page load times, 
  • user interactions (clicks, scrolls), 
  • visual renderings
  • DNS resolution
  • Network requests etc.

Also known as browser monitoring (as all happens on a user’s browser), RUM provides direct-from-the-source monitoring that allows teams to identify and address issues that specifically impact the end-user experience, satisfaction, and engagement.

And what is Application Performance Monitoring (APM)?

On the other hand, application Performance Monitoring (APM) delves into an application’s internal workings, offering a behind-the-scenes view of the application’s architecture. 

APM tools monitor the performance of various components, including:

  • servers, 
  • databases, and 
  • external services

to identify bottlenecks and failures that could impact the user experience. 

RUM vs. APM – Where’s the Difference?

Real User Monitoring (RUM) and Application Performance Monitoring (APM) are two pivotal technologies in the realm of digital observability, each playing a distinct yet complementary role in ensuring the optimal performance and user experience of web applications. 

Source: ITIC 2021 Hourly Cost of Downtime Survey

Understanding the nuances of RUM and APM highlights their differences and illustrates how they work together to create a holistic view of application health.

Key Differences Between RUM and APM

Below is a tabular comparison that delineates the distinct functionalities and advantages of RUM and APM, shedding light on how they synergize to offer a holistic observability solution.

Feature/AreaRUMAPM
FocusRUM is user-centric and it focuses on the end-user experience and interaction with the application.APM is Application-centric and it covers a broad spectrum of monitoring including server-side, application dependencies, and infrastructure health.
CapabilitiesProvides real-world insights into how users interact with the application, including page load times, user paths, and engagement with specific features.Offers comprehensive insights into application performance, including response times, system health, and error rates.
Predictive NatureRUM is reactive i.e. it highlights current user experiences and issues based on actual user interactions without predicting future performance issues.APM can be predictive as it uses synthetic testing and other strategies to forecast potential future performance bottlenecks or scalability issues.
Use CasesIdeal for understanding user behavior, preferences, and identifying UI/UX improvements. Answers questions like what users click on first, how long they engage with features, and the last interaction before leaving.Suited for identifying, diagnosing, and resolving technical performance issues. Ensures the application scales effectively and remains healthy under varying loads.
Complementary BenefitsEnhances customer satisfaction by identifying what’s working and what isn’t directly from the user’s perspective. Valuable for marketing strategies and feature development.Ensures operational excellence by keeping the application running smoothly and efficiently, directly impacting user satisfaction from a performance standpoint.

Key Challenges for RUM

While RUM provides an external, user-focused perspective, highlighting how actual users experience the application under real-world conditions, APM offers an internal, system-focused view, uncovering the technical reasons behind performance issues. 

In other words, RUM tells you “what” is happening from the user’s point of view, and APM shows you “why” it’s happening from the system’s perspective.

Real-world observability, empowered by Real User Monitoring and Application Performance Monitoring, becomes Alex’s sword and shield in this fight, although not without its challenges.

Challenge #1: Limited to Live Environments

A primary limitation of RUM is its operation exclusively within live production settings. This means RUM’s insights are gathered only when real users interact with an application or website that is fully operational. As insightful as this is for monitoring actual user experiences, it restricts RUM’s utility in the earlier development and testing phases. Organizations can only rely on RUM to foresee user experience impacts due to changes or updates once those changes are implemented in the live environment.

Alex’s Plight:

Alex rolls out a new feature designed to streamline the checkout process on his e-commerce platform. Despite thorough testing in development and staging environments, RUM data reveals an unexpected increase in abandoned carts upon deployment. 

Had Alex been able to assess real user interactions before going live, he might have identified and resolved the usability issue, mitigating the negative impact on sales.

Challenge #2: Dependence on User Traffic Volume

The effectiveness of RUM is directly tied to the presence of substantial user traffic. Many users must interact with the application or website for meaningful data and insights. This presents a challenge, particularly for startups or newly launched digital products, which may still need to attract more traffic. In such cases, RUM’s ability to provide comprehensive insights into user experiences is significantly diminished.

Alex’s Plight:

Alex oversees the launch of a new mobile app designed to complement the existing web platform. Early RUM data suggests low engagement with the app’s personalized notification feature, a key component to boost user retention. 

The challenge here is twofold:

  • The app’s nascent user base is too small for RUM to provide comprehensive insights
  • Alex needs help determining whether the low engagement is due to design flaws or the lack of a sufficient user pool to validate the feature’s effectiveness.

Challenge #3: No Insight into Server-Side Performance

While RUM excels at capturing the nuances of user interactions from the front end, it needst peer into the server-side or the intricacies of distributed application architectures. 

If issues arise from the back end or within the complex web of service interactions, RUM falls short of pinpointing these problems. 

Consequently, to achieve a holistic view of an application’s performance landscape, RUM must be complemented with additional tools that offer visibility into server-side and architectural performances.

Alex’s Plight:

Users report intermittent slowdowns during peak usage, but RUM data shows no significant changes in client-side performance metrics. 

Without visibility into the backend, Alex initially overlooks server resource saturation as the root cause. In short, there are blind spots as without integrating APM tools to monitor backend performance, he lacks the complete picture necessary to diagnose and address the issue efficiently. Only after deploying complementary server-side monitoring does he identify and resolve the capacity constraints, restoring optimal performance.

How does RUM Monitoring help?

By integrating deep error insights across the stack, RUM simplifies debugging, reduces noise, and accelerates resolution times.

Say Hi 5 to Error Handling:

  1. Streamlined Error Management: RUM monitoring tools elevate frontend error detection, quickly linking errors across the stack to their sources and simplifying error handling by categorizing similar issues.           

This clarity enhances understanding error patterns, streamlining resolution without requiring complex query knowledge.

  1. Error Mapping for Insightful Analysis

A RUM offers clear insights into the connection between frontend errors and backend anomalies, mapping out the relationships and impacts across services. Intuitive correlations across data points deepen root cause analysis.

  1. Efficient Debugging with Source Mapping

By utilizing source maps, RUM facilitates a quick transition from identifying to fixing code issues, directly pinpointing problematic code lines, and speeding up the debugging process.  More here.

  1. Comprehensive Error Analysis: Gain a complete overview of prevalent error types, their triggers, and affected technology layers, from network requests to operating systems, enabling a detailed understanding of the error landscape.
  1. Proactive Error Alerting: A RUM allows for anticipating errors through:
  • customizable alerts, 
  • keeping teams informed and 
  • responsive with integrations like Slack and MS Teams, 

thus enhancing user experience proactively.

Key Challenges for APM

The evolution of technology with the advent of microservices, containers, and cloud computing has significantly complicated the application landscape. These advancements have turned applications into complex networks of interdependent components, challenging the traditional approaches to performance monitoring. 

Here’s a breakdown of the main challenges faced when integrating APM into an organization:

APM Challenge #1: Navigating Complexity: 

The shift from monolithic to microservices architectures and the widespread adoption of containers and cloud-native solutions have added complexity to applications. This complexity necessitates a more refined and comprehensive strategy for monitoring performance that can traverse the intricate web of services and dependencies that constitute modern applications.

Alex’s plight:

Alex’s application is built on a microservices architecture designed to improve scalability and flexibility. However, this architecture introduces its own set of complexities. 

For instance, a simple user request to check out an item from an online store might traverse multiple services—for inventory check, payment processing, and order confirmation. 

Monitoring the performance of each microservice separately and then correlating the data to understand the overall transaction flow becomes a daunting task.

APM Challenge #2: Cost Management: 

The financial investment required for APM solutions can be substantial, posing a significant barrier, particularly for smaller enterprises or startups operating on tighter budgets. The cost of acquiring, implementing, and maintaining advanced APM tools can deter businesses from adopting these essential solutions.

Alex’s plight:

As Alex’s e-commerce platform grows, the volume of monitoring data—ranging from logs and metrics to traces—skyrockets. Storing and analyzing this data in real time becomes increasingly expensive. 

APM Challenge #3:Bridging the Skills Gap:

Another pressing challenge is the need for more professionals proficient in the specifics of APM. Mastery of APM demands an in-depth understanding of diverse application architectures, familiarity with network protocols, and a solid grasp of coding principles. 

The talent pool equipped with these specialized skills needs to be improved, making it difficult for organizations for effective APM deployment.

Alex’s Plight:

The APM tool Alex initially considered requires deep technical knowledge of specific programming languages, network protocols, and cloud infrastructure nuances to set up and utilize effectively. Alex finds this requirement problematic with a small DevOps team not specialized in the intricacies of APM.

How does APM help?

An APM not only elevates your monitoring capabilities but does so in a way that is cost-effective, flexible, open, and supported by an unparalleled customer service team, ensuring that your digital ecosystem remains robust and responsive to your needs.

APM Seamless Observability Across the Stack

An APM introduces a groundbreaking way to easily monitor your entire system’s behavior, offering a deep dive into each application’s health. 

It’s part of a comprehensive observability suite, including Cloud and Infrastructure Monitoring, Real User Monitoring (RUM), SIEM, and more, designed to streamline your monitoring efforts. By centralizing logs, metrics, traces, and security data within a single interface, Coralogix dramatically simplifies the correlation, troubleshooting, and remediation processes, making context-switching a thing of the past.

Cost-Effective Data Management for Smart Savings

It redefines the cost of observability with a unique approach where expenses are tied solely to the volume of data ingested and processed. Thanks to its in-stream analysis, you’re empowered to query and analyze comprehensive data sets—including logs, traces, metrics, and security events—without indexing or relying on hot storage. 

This model facilitates alert generation and insight discovery and ensures that you’re only paying for what you genuinely need, paving the way for significant cost reductions.

Flexible Data Storage and Processing Without Extra Fees

With Coralogix, you can choose how your logs, metrics, and traces are stored and processed, all while accessing the platform’s full range of services and features. 

This includes:

  • seamless integration into low-cost archive storage
  • sophisticated data routing and
  • the capability to swiftly query unstructured data

directly from the Coralogix user interface, it is ensuring efficient data management and direct cost savings.

Embracing Open Source Compatibility and Zero Lock-In

It stands out for its open-source friendliness, allowing you to continue using preferred shipping agents and storing data in open-source Parquet format. This commitment to open standards means zero vendor lock-in, allowing you to choose how and where your data is handled.

Unmatched 24/7 Rapid Response and Support

Beyond its technical prowess, an efficient RUM platform sets a new standard in customer support, offering 24/7 assistance with an average response time of just one minute and resolution times around an hour—at no additional cost. This level of support ensures that any issues you encounter can be swiftly addressed, keeping your operations running smoothly around the clock.

How RUM Stands Out

In the dynamic realm of digital observability, platform teams overseeing multi-tenant systems are searching for a comprehensive solution that consolidates logs, metrics, and traces into a unified observatory suite. Amidst the constellation of observability giants, each offers robust capabilities to navigate complex digital landscapes. 

Coralogix Vs New Relic: A Comparison

Feature / AspectCoralogixNew Relic
Core ObservabilityLogs, metrics, traces, and alerting supported.Logs, metrics, traces, and alerting supported.
Data Correlation & UsabilityExcel at integrating data types into a cohesive user experience.Provides integration across data types but with less emphasis on seamless user experience.
Innovative AlertingFlow Alerts feature orchestrates comprehensive system health alerts.Standard alerting mechanisms without Flow Alerts feature.
Machine LearningAdvanced ML for event correlation; unique Loggregation for efficient data analysis.ML used for alarms and event correlation, but lacks the Loggregation feature.
Security Solutions (SIEM, CSPM)Includes sophisticated SIEM and CSPM solutions.Lacks dedicated SIEM and CSPM solutions, requiring workarounds for similar functionalities.
Archiving & Query CapabilitiesAll customers can archive data with remote queries on unindexed data at no extra cost.Archiving available primarily for enterprise customers, with costs for indexing and re-accessing data.
Pricing ModelTransparent, based on data ingested; no extra charge for queries or users. Affordably priced storage and ingestion.Tiered pricing model; charges per GB ingested and per user, potentially leading to higher costs.
Customer SupportExceptional support with 30-second median response time for all users.Response times start at three hours for enterprise customers; support tiers may limit access for some users.

Coralogix Vs Data Dog: A Comparison

The following tabular comparison emphasizes Coralogix’s strengths in providing a more accessible, cost-effective, and analytically capable platform for long-term data storage and analysis compared to Datadog, particularly highlighting the innovative Remote Query feature as a game-changer in the observability space.

Feature/AspectCoralogixDatadog
Long-term Storage ApproachOffers innovative and cost-effective solutions for long-term storage without compromising accessibility or analytics capabilities.Provides the “Logging without Limits” feature for archiving logs in low-cost storage like S3, but with limitations on accessibility and analysis.
Support & Cost EfficiencyBoasts 30-second response times in customer support and significant cost reductions (40-70%) for customers, enhancing overall affordability.Initial cost savings on log archiving may lead to delayed expenses, particularly with data rehydration costs.
Data UsabilityRemote Query allows for direct querying of archived data without rehydration, enabling immediate insights and analysis with no extra cost for querying.Archived logs require rehydration for querying, incurring additional costs and potentially delaying access to data.
Pre-Archive Data InsightsTransforms and visualizes data before archiving, supporting advanced features like machine learning model training, sophisticated alerts, and dashboard updates.Data is archived without additional analysis or insight generation, limiting pre-archive data utilization.
Query Performance & CapabilitiesSupports fast queries (e.g., 10TB in 10 seconds) and advanced aggregations on archived data using DataPrime syntax, alongside SQL and Lucene, for true data discovery.Lacks the capability for direct queries on archived data without rehydration, impacting the speed and flexibility of data analysis.
Data Discoverability & CostEnables free data exploration and insight generation from archives, with the only cost being S3 hosting fees. Encourages holding less data in frequent search due to efficient Remote Query capabilities.Requires data rehydration for exploration, leading to additional costs and constraints on data discoverability and frequent search data volume management.
Innovation in ArchivingRemote Query represents a next-generation archiving solution, offering unmatched analytics capabilities and performance, setting a high industry standard.While offering basic long-term storage solutions, lacks the comprehensive analytics and performance capabilities found in Coralogix’s Remote Query.

Coralogix Vs Splunk: A Comparison

Feature/AspectCoralogixSplunk
Logs, Metrics, Traces, and AlertingSupports with unique real-time analytics via Streama, enabling long-term trend analysis without indexing.Supports, but focuses more on legacy and security use cases without a specific real-time analysis pipeline.
Cost and Cost OptimizationOffers significant cost savings (40-70%) with a transparent pricing model based on data ingestion. Utilizes TCO Optimizer for further savings.Pricing can be complex and less transparent, often requiring a quote; generally higher costs reported.
Data Correlation and UsabilityExcels in integrating different data types into a seamless user experience with cohesive journeys.Supports ingestion from diverse sources but may lack the seamless integration and usability found in Coralogix.
Unique Alerting CapabilitiesFeatures Coralogix Flow Alerts for comprehensive system health tracking over time.Lacks an equivalent to Coralogix Flow Alerts, potentially limiting alerting capabilities.
Archiving and QueryingEnables querying of remote archived data without reindexing at no additional cost, offering true long-term retention and analysis capabilities.Offers archiving into S3 but requires reindexing for analysis, which can introduce delayed costs.
Customer SupportProvides all customers with 24/7 support, boasting a 30-second median response time and fast resolution.Limited global 24/7 support; response and resolution times can be slower and depend on incident severity.
Dashboards and VisualizationOffers specific technology-focused dashboards (e.g., Kubernetes, Serverless) and supports open-source solutions like Grafana.Lacks prebuilt, technology-specific dashboards, relying on more generic dashboarding capabilities.

Conclusion:

Real User Monitoring (RUM) and Application Performance Monitoring (APM) provide a complete picture of application health and user experience. While APM monitors backend performance, RUM focuses on the user’s interaction with the front end. A RUM tool merges these approaches, enhancing observability with features like advanced error tracking and proactive alerts. This streamlined integration empowers businesses to improve application reliability and user satisfaction efficiently.

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