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Observability vs Monitoring, What Are The Key Differences & Similarities?

Application performance monitoring is an important aspect of managing modern digital environments. Imagine encountering unexpected issues with your application that block performance and disrupt user experience. Understanding the difference between observability and monitoring is vital in addressing such a difficult situation.

Alerty's free APM solution offers a valuable resource for those seeking to understand the difference between observability and monitoring. This tool facilitates a better understanding of your application performance, aiding you in identifying and addressing potential issues effectively.

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Table of Contents

What Is Observability?

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Observability is understanding a complex system’s internal state based on external outputs. When a system is observable, a user can identify the root cause of a performance problem by looking at the data it produces without additional testing or coding.

Observability in Engineering

The term comes from control theory, an engineering concept that refers to the ability to assess internal problems from the outside. For example, car diagnostic systems offer observability for mechanics, allowing them to understand why your car won’t start without having to take it apart.

IT Observability in Action

In IT, an observability solution analyzes output data, assesses the system’s health, and offers actionable insights for addressing the problem. An observable system is one where DevOps can see the entire IT environment with context and understanding of interdependencies. The result? It allows teams to detect problems proactively and resolve issues faster.

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What Is Monitoring?

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Monitoring refers to gathering and analyzing data from applications and infrastructure to track performance and identify, mitigate, and resolve issues. This is established by tracking metrics that provide insight and help guide business decisions—for example, monitoring the availability and responsiveness of the service by measuring network metrics like connectivity and latency. The beauty and benefits of monitoring lie primarily in analyzing long-term trends and alerting. It shows you how your applications are functioning, growing, and being used over time.

Most companies today use five or more observability tools, and monitoring & observability is typically the second-largest infrastructure spend in a company after cloud infrastructure itself, with a market size of ~$17B.

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How Do They Work: Observability vs Monitoring

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Monitoring: The Core of System Health Checks

Monitoring computing systems is a practice as old as running computing systems themselves. The monitoring practice involves collecting data about a system to check if the system is operating as expected. This practice includes:

  • Reports and alerts on errors
  • Faults
  • Anomalous data values

Monitoring tools can collect data to measure the time to deploy an application release. If the time taken falls outside an expected window, the monitoring tools can alert users, indicating that something has likely gone wrong. DevOps monitoring covers the full software development lifecycle (SDLC). Application performance monitoring (APM) is a specialized subset of DevOps monitoring that focuses on applications running in production. It prioritizes metrics that apply to user experience.

Observability: Elevating Monitoring to a Wider Scope

Observability brings a wider scope and visibility to traditional monitoring tools, incorporating extra situational and historical data and system interactions. It enables investigation into the root cause of monitoring alerts, alongside the ability to investigate issues that arise due to multi-component interactions. 

You can use observability tools to debug distributed application architecture-based systems themselves. You can also use them to observe the overall health of the system and the interactions between system components. You can use observability software to map an entire interconnected system, its dependencies, and real-time interactions.

Catch issues before they affect your users with Alerty's free APM solution today!

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What Are The Similarities Between Observability And Monitoring?

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Metrics

Metrics are system data measurements. For instance, a metric could be network throughput or the number of application errors in a week. Monitoring reports on metrics and observability looks for ways to improve their values.

Events

Events are discrete actions that occur in a system at any time. An example might be a user changing a password or an alert indicating many password attempts. Events trigger monitoring and support observability in investigating incidents.

Logs

Logs are software-generated files containing information about the system's operations, activities, and usage patterns. They include a historical record of all processes, events, and messages and additional descriptive data, such as timestamps, to contextualize this information. Monitoring generates logs that observability uses for further system analysis.

Traces

Traces are the full path of a single operation across its various interrelated systems. For fully distributed tracing, signals must be emitted from every transaction in the microservice architecture for tracking. Monitoring enables tracing, which is an important function of observability.

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Observability vs Monitoring: The Differences

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Contrary to popular belief, some critical distinctions exist between observability and monitoring. One of the main differences is that monitoring serves more as an operational function. It looks at a system's internal performance and flags any issues. Monitoring doesn't provide insight into the myriad of factors that could be causing the problem. It simply alerts the DevOps team to the presence of an issue.

Beyond Alerts, Unveiling Root Causes

To illustrate, monitoring might notify your SRE teams about an unresponsive server. It can furnish data on metrics like the system's memory, network performance, and CPU—but it doesn't reveal the root cause of these spikes. Meanwhile, an observability platform takes things a step further. It analyzes server logs, traces, events, and metrics and correlates this data, potentially discovering that a runaway process is the reason for the spike in CPU usage. The observability platform then pinpoints this process as the root cause.

Data-Driven Insights

Monitoring tells you something is amiss, while observability uses data collection to inform you about what is amiss and why it happened. While monitoring gathers metrics, DevOps teams must manually sift through this information, link it to the issue, and pinpoint the error. 

Automating DevOps Workflows

Observability streamlines these laborious tasks, offering a much-appreciated helping hand to the team involved in identifying and resolving the issue. Observability boasts advanced features such as data correlation, which sometimes involves the application of AI to deliver contextual clues, distributed tracing, and sophisticated anomaly detection.

Proactive Problem Detection

Another notable difference is that observability can solve the problem. These are issues that the DevOps team may not even have been aware of, whereas monitoring is more centered on unveiling a system's status.

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Observability vs Monitoring: When Use Each

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Monitoring helps catch issues aggressively, while observability helps you understand what you don’t know. Monitoring allows for reactive and real-time error-catching, ensuring you know about issues before they become dire. For example, monitoring tools will alert you if your AWS costs unexpectedly spike from your application. A monitoring tool will also alert you if user latency suddenly spikes. These tools are your first layer of defense in catching errors before they become expensive.

Observability is where you want to turn when trying to understand the unknown unknowns. Observability can help you answer questions such as: 

  • What is impacting my error rate? 
  • Is it impacting all customers or just those uploading profile pictures? 

These questions don’t have obvious answers, and analyzing logs and traces can help answer them. Observability helps you understand the health of your applications and their impact on your users. It is also a key tool for debugging complex systems and resolving issues.

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How They Compare With Telemetry And APM

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Observability vs Telemetry

Observability focuses on using telemetry data to debug system issues and integrate various forms of telemetry data to provide deeper insights into infrastructure operations. 

Telemetry, on the other hand, refers to the automated collection of data from diverse environments to centralized locations for analysis, encompassing traces, metrics, and logs to understand system behavior and performance.

Monitoring vs Telemetry

Monitoring utilizes telemetry data to track a system's health across different environments. Beyond collecting data, telemetry provides visibility essential for real-time alerting and monitoring. The key distinction between monitoring and telemetry lies in monitoring's use of collected telemetry data to alert the team of metrics falling outside specified thresholds.

Observability vs APM

Application performance monitoring (APM) aims to manage and monitor issues impacting application performance and availability, offering insights into user experience as workloads increase. Observability provides more technical and contextual insights than APM, aiding in issue debugging and giving a comprehensive picture of overall system health.

Monitoring vs APM

Monitoring offers a comprehensive view of the infrastructure, including setting alerts and taking actions using telemetry data. In contrast, APM focuses on end-to-end application performance, making it narrower. Traditional APM can be challenging in modern IT environments due to their focus on applications, especially in the context of cloud-native applications and microservices.

Comprehensive Monitoring & Incident Management

Alerty is a cloud monitoring service for developers and early-stage startups, offering:

  • Application performance monitoring
  • Database monitoring
  • Incident management

It supports technologies like NextJS, React, Vue, and Node.js, helping developers identify and fix issues. 

  • Alerty monitors databases such as Supabase, PostgreSQL, and RDS
  • Tracking key metrics like CPU usage and memory consumption
  • It features quick incident management and Real User Monitoring (RUM) to optimize user experience
  • Its universal service monitoring covers dependencies like Stripe API, OpenAI, and Vercel. 

Alerty uses AI to simplify setup, providing a cost-effective solution compared to competitors. It is designed for ease of use, allowing quick setup, and integrates with tools like Sentry, making it ideal for developers and small teams needing efficient, affordable monitoring. 

Catch issues before they affect your users with Alerty's free APM solution today!

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Between Observability And Monitoring, Which Is Better?

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In DevOps, observability and monitoring tools are crucial for ensuring your systems' stability and performance. Both observability and monitoring are essential for understanding how your applications behave in production. Monitoring mainly focuses on collecting metrics and alerting you when something goes wrong, while observability provides a more comprehensive view of the system by:

  • Collecting traces
  • Metrics
  • Logs for enhanced debugging and troubleshooting capabilities

Nevertheless, when choosing the right tools to support your team, you might have to choose between monitoring and observability platforms.

​Developer Efficiency

Observability is essential for developers to perform root cause analysis and debug their systems effectively. With observability software, developers can do this work more easily than relying solely on monitoring tools, including telemetry and APM. Regarding DevOps, observability tools may be better than monitoring tools to quickly detect, troubleshoot, and solve issues in a modern IT environment. 

Modern IT Environments

In a modern IT environment, all these tools can work together to support different IT teams and offer substantial insight into:

  • Health
  • Performance
  • Availability of various systems, servers, environments, and applications across your IT infrastructure

Monitoring tools are essential for monitoring system health, while observability tools are useful for debugging and understanding system behavior, particularly in complex and dynamic systems.

Beyond Thresholds

Monitoring tools will tell you when a metric has exceeded a predetermined threshold, while observability tools provide insights into the system's behavior. They help you discover why a particular metric has exceeded a threshold or a set of services is not working correctly. Observability tools, such as distributed tracing and log management tools, can provide insights into complex systems, helping you identify performance bottlenecks and diagnose issues that significantly impact your system’s performance. 

Debugging Complex Systems

Observability tools allow you to gain insights into your systems and applications by collecting granular data and connecting the dots between different components. This makes identifying issues related to code, infrastructure, or performance easier. By contrast, monitoring tools primarily alert you when certain thresholds are crossed, making them critical for incident response but less suitable for debugging complex systems.

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How Observability And Monitoring Can Work Together

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Observability and monitoring are two critical functions in application performance management. Although they serve different purposes, they can work together to provide a more comprehensive solution when issues arise.

Early Detection and Quick Resolution

Monitoring is essential for capturing and reporting small, known problems within a system. It can alert SRE teams to issues before they escalate, providing basic information for quick resolution. Monitoring is invaluable for addressing straightforward issues that don't require deep analysis.

On the other hand, observability comes into play when repeated incidents occur without a clear root cause. Observability tools can delve into the system to identify one or multiple root causes of a problem. Once the root cause is identified, engineers can adjust monitoring tools to capture additional metrics, send new alerts, or modify alarm conditions accordingly.

Working Together for System Optimization

While monitoring is excellent for solving known problems and confirming planned changes, observability excels in helping with operations such as capacity planning, cost optimization, patching, upgrades, and developing fixes. Monitoring may not be equipped to perform these tasks, but they can validate the success of actions taken based on observability findings.

Combining observability and monitoring can provide a powerful approach to application performance monitoring, offering a comprehensive solution for addressing a wide range of issues that may arise in complex systems.

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Catch Issues Before They Affect Your Users with Alerty's Free APM Solution

Alerty is a cloud monitoring service designed specifically for developers and early-stage startups. Alerty provides a robust solution to help users monitor, identify, and fix issues efficiently with its:

  • Comprehensive application performance monitoring,
  • Database monitoring
  • Incident management offerings

Application Performance Monitoring with Alerty

Alerty supports a wide range of technologies commonly used by developers, such as:

  • NextJS
  • React
  • Vue
  • Node.js

By monitoring these technologies, Alerty allows developers to track and optimize the performance of their applications, ensuring a smooth user experience.

Database Monitoring Capabilities

For databases, Alerty covers popular options like:

  • Supabase
  • PostgreSQL
  • RDS

Users can monitor key metrics, such as CPU and memory usage, which are essential for maintaining the health and performance of their databases.

Incident Management and Real User Monitoring (RUM)

Alerty offers quick incident management features, enabling timely responses to issues as they arise. The Real User Monitoring (RUM) functionality helps optimize the user experience by providing insights into how real users interact with applications.

Universal Service Monitoring

The universal service monitoring feature extends Alerty's monitoring capabilities to include external dependencies like:

  • Stripe API
  • OpenAI
  • Vercel

This approach ensures developers can keep tabs on all aspects of their applications' performance.

AI-driven Setup and Cost-effectiveness

Alerty simplifies the setup process using AI technology, making it easy for users to monitor their applications. Compared to competitors in the market, Alerty provides a cost-effective solution, offering valuable monitoring features at an affordable price point.

Integration with Tools like Sentry

To enhance its usability, Alerty integrates with popular tools like Sentry. This integration further streamlines the monitoring process, making it ideal for developers and small teams needing efficient and affordable monitoring solutions.

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