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What is observability? Observability defined

Observability is a practice that delivers a holistic view of your entire IT estate to improve operations, security, and AI adoption. It goes beyond simple, rules-based monitoring to give you a broader and deeper picture of your IT environment and assets.

Observability: An Overview

As IT architecture becomes more complicated, organizations have realized they must go beyond simple monitoring and develop a deeper understanding of their IT estate.

Observability provides a holistic view of an application, system, network, or a full IT environment. A mature observability practice will offer both a broad view of the assets or environment being investigated, and the ability to drill down to the code level of any asset or component of the IT estate. When implemented properly, observability lets an organization understand security and operational incidents, take proactive measures to prevent incidents, and remediate vulnerabilities and incidents faster.

Read on to learn how observability provides holistic visibility and control, and combines with AI to create a more efficient and resilient IT stack.

Observability key statistics

Observability is growing at a rapid rate. The market is projected to expand from just $278 million in 2022 to $2+ billion by 2026 (650 group).

This growth is fueled by a wide range of use cases, including adopting AI, improving security and operations, accelerating digital transformation, moving to the cloud, and better managing everything from customer experience to the software lifecycle.

Observability has been shown to produce significant improvements to a wide range of IT and business outcomes. IBM found that observability can reduce breach lifecycles by 74 days, saving $3+ million per incident. In a separate report, IBM found that combining observability with AIOps can create:

  • 50% reduction in incidents
  • 80% reduction in time remediating false-positives
  • 75% issue resolution

While reducing application downtime and increasing visibility into an application’s performance. No wonder 90% of respondents to a recent survey stated data observability was either very important or critically important to DataOps initiatives. (ESG)

Observability matters—and every organization must develop it. Here are practical lessons, tips, and technology solutions that can help you reliably adopt observability at your organization.

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Data observability vs observability data

Data observability is a relatively new and complex topic. Before we dig too deep into this topic, let’s clear up a few areas of confusion that often surround it.

First, the difference between data observability vs observability data. These terms are sometimes interchanged and cause confusion. However, the difference is very simple.

“Observability data” refers to the actual piece of data that you collect that contributes to your ability to observe your environment. When you collect observability data, you have the building blocks needed to create a holistic picture of your environment. The three classes of observability data are typically metrics, logs, and traces (explained in greater detail below), which can include application, network, and security logs; server response time, memory usage, and error rates; and distributed traces.

“Data observability” refers to that holistic picture of your environment created by stitching all of those individual pieces of observability data together. When you do so and achieve data observability, your teams can see, monitor, dig into, and manage the data within your environment. For example, an IT team with a mature observability practice can receive an alert of a potential cyber attack with security logs and distributed traces to map how a threat infiltrated and moved through their system.

Observability vs monitoring: Four differences to understand

“Observability” and “monitoring” are two more terms that executives and IT teams often mistake for each other. Many of them believe “observability” is just a new word for “monitoring”, and that they already have it established. However, there are some critical differences between the two. Let’s look at the key points of observability vs monitoring.

Action vs a property

Monitoring is something you do. You continuously collect data from an application, system, or network. You then set rules to automatically analyze that data against certain parameters that indicate an issue. Finally, you receive alerts when something in those rules gets triggered (e.g. you receive an alert when a threshold for safe, high-performance CPU percent usage is breached by a workstation you are monitoring).

Observability is a property. You don’t “do” observability; you either have observability within an application, system, or network or you don’t. To have observability within an asset — or your environment as a whole you need the data that’s generated from monitoring, but you also need the ability to analyze and interpret this data in an unstructured manner that goes beyond set rules.

Reacting to alerts vs proactive investigations

Monitoring is inherently reactive. After a monitoring system is set up, there’s nothing to do until an issue occurs, a rule is triggered, and an alert is sent to the appropriate team. Monitoring not only keeps you in firefighting mode, but it can only resolve known issues — those clear, established operational or security problems that you can set clear, well-defined rules to check for.

Observability is inherently proactive. While it provides big benefits to incident response activities, it also lets teams proactively search for potential issues within a system before problems occur. Observability takes you out of firefighting mode, and also lets you find the “unknown unknowns” in your environment by finding problem patterns that don’t conform to standard rules.

Symptoms vs root causes

Monitoring can only spot the symptoms of deeper problems. The rules you check an assets performance against are just signs that something deeper might be wrong with it. Monitoring can tell you when a CPU percentage usage threshold is crossed, but it can’t tell you whether it’s because a laptop has too many applications open or because malicious code is consuming its resources.

Observability can tell you the root cause of a problem by collecting and correlating a wide range of data related to an asset. Observability gives you the detail and flexibility to explore everything going on with an impacted asset to see what caused a symptom to manifest — including whether other assets share the same root cause, or if the root cause lies in a different asset altogether.

Simple, stable systems vs complex, dynamic environments

Monitoring can only be applied to a relatively predictable application, system, or network — one where “good” performance and security parameters can be established and verified, and potential issues are well-defined.

For example, a server can be monitored effectively on its own because it is a simple machine with a limited range of behaviors and potential problems. An IT team can set thresholds for metrics like CPU utilization, response time, memory consumption, etc., and then perform simple troubleshooting when one of those thresholds is crossed.

Observability is required for today’s IT environments, which that include high volumes of assets that are interconnected, always changing, and constantly interacting with each other in myriad ways. In these environments, performance and security parameters and problems are not always clear — or known at all — and require complete visibility and flexibility to identify and investigate.

For example, with a mature observability capability you can dig into more complex architecture — like Kubernetes clusters — to better understand how resources are being utilized and how they may be better allocated, before an issue arises to improve performance and prevent thresholds from being crossed.

In sum: Monitoring is part of observability, but the two are not the same thing. Monitoring provides the raw data that observability requires, but observability goes a few steps further by centralizing and correlating a large volume of monitoring data — from many sources — to provide a holistic view of today’s environments.

Observability vs monitoring is not an either/or choice, but a both/and scenario. Observability and monitoring are both needed to establish a modern IT technology stack. Yet while most organizations already have some monitoring in place, few have elevated this visibility into a truly mature observability practice.

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Three pillars of observability

Observability is a broad concept that can fold in anything that provides a broader, deeper, and more interconnected picture of how your entire environment functions. However, there are three pillars of observability that every organization must first collect and connect to establish meaningful observability.


Metrics are the basic numerical measures of an application, system, or network’s performance, that quantify its behavior, events, and components. They can include everything from classification records — like the date and time of an event — to KPIs like memory, CPU usage, and error rates. Metrics can be collected from a wide range of external and internal sources, and then correlated, visualized, and analyzed any number of ways.


Logs are records of all activities, events, and behaviors within an application, system, or network. They are typically text-based descriptions of an incident, and include a date and time stamp for when it occurred. They provide both detail and context for anything that occurs within your environment, and are usually queried, during a security or operational incident to determine what happened, when it happened, and how it might be mitigated.


Traces are records of the end-to-end path of user requests — from the browser, application, or UI where the request originated, down to its fulfillment (or termination). Traces provide a code-level view of how requests flow through your environment and how your applications connect with each other. They investigate user requests that lead to incidents, either because they were malicious requests, or because they triggered an operational incident.

Combined, these three pillars of observability create a comprehensive view of, — and into, — your environment, providing both a broad view of your environment and detail down to the code-level to, aid in reactive and proactive investigations.

Why observability tools matter

The right observability tools will give you visibility and control over your applications, systems, and networks. With this visibility and control, you will gain a few key capabilities, including the following.

Provides an overview of operating systems

Observability tools give you both a broad and detailed view of your entire IT estate.

The right tools will give you a birds-eye view of your IT infrastructure, as well the ability to ask granular questions about what’s working and what isn’t.

This view will help you do two things.

First, it will help you define a complete, accurate, and up-to-date picture of what a “good” operating and security state looks like in your environment.

Second, it will help you identify any applications, systems, or networks that are behaving improperly, and quickly remediate them.

Third, it will help you spot potential vulnerabilities and fragilities ahead of time, and let you address them before they are exploited or break and cause an incident.

The result? You can develop a more robust operating and security environment — and collect the data needed to demonstrate these improvements over time.

Reduces MTTR

Observability tools make it faster and easier to resolve IT incidents.

The right tools will paint a clear picture of any incident that occurs, including what caused it, how far it spread, and how to best remediate it across your entire IT estate.

This comprehensive visibility will help you do a few things.

First, you can detect incidents much faster, and map their full scope — identifying every asset they touched that need to be remediated.

Second, you can perform a root cause analysis and identify what caused an incident and how to best remediate it much faster.

Third, you can effectively collaborate between teams to remediate the incident, and have complete visibility into whether your remediation actions were effective.

The result? You will lower your mean time to repair (MTTR), your remediations will be more effective, and you will have more confidence that you resolved incidents in full.

Provides context for success

Observability tools provide context for security or operational incidents.

The right tools will show you every asset in your IT environment, including the myriad ways that they interact, interconnect, and are interdependent upon each other.

This deep understanding of your complex IT estate will help you do a few things.

First, during an incident you can better understand what changed, how it changed, when it changed — across every asset directly impacted by the event.

Second, you can understand how a single compromised asset might cause ripples across your entire IT estate due to its interactions with every other asset you deploy.

Third, you can use these contextual views of your IT estate to quarantine impacted assets during an incident, or to proactively harden your IT estate through segmentation.

The result? You will provide context for your incident management activities, and minimize any operational and security disruptions you might incur.

Observability benefits

By developing comprehensive observability, you will generate a wide range of benefits. These include, but are not limited to:

Less downtime

With observability, you can find every instance of known vulnerabilities and fragilities within your entire IT stack. You will also find new patterns that suggest “unknown unknown” issues in your environment causing performance or security issues.

For both known and unknown issues, observability will help you:

  • Discover, troubleshoot, and resolve incidents, vulnerabilities, and fragilities faster — everywhere they occur in your environment.
  • Gain visibility into control of new assets that enter your environment, and map the interconnections they create.
  • Establish predictive analytics and automation to resolve potential incidents before they occur.
  • Harden your environment against security or operational incidents.

Drives faster development cycles

Observability gives development teams more visibility into their work, and the organization’s IT infrastructure. This makes it easier to find and fix potential issues during development, and to push out applications and updates faster and more effectively.

When you establish comprehensive visibility, developement teams will:

  • Spend less time resolving problems and experience less downtime, freeing them to focus on their core work.
  • Gain a broader and deeper understanding of their IT estate, the user experiences it drives, and their applications’ place within it all.
  • Collaborate more effectively with other teams within the organization, during both development and incident resolution.
  • Adjust, improve, and extend their applications without negatively impacting the performance of the environment.

Real time data

With observability, everyone in the organization receives more and fresher data. This will allow nearly everyone in your organization to make better decisions, work more collaboratively, and submit fewer requests to IT teams.

Real-time data generated by observability allows your team to:

  • Create better, more complete, and more accurate visualizations, reports, and dashboards for your teams and executives to work from
  • Develop real-time visibility into the user experience, better understand user journeys, and improve every step that they take.
  • Maintain system uptime and data availability, reducing the volume and burden of help desk tickets and data requests.
  • Respond faster to incidents and opportunities at every level of the organization.

More resilience

With observability, you gain the visibility and control you need to build a more shock-proof organization at every level, which will allow you to prevent potential issues from occurring and withstand and recover from incidents faster.

With observability, your organization will:

  • Increased security, reducing the opportunities for security incidents, and the duration and severity of any incidents that do occur.
  • Improve operations, resolving performance issues proactively across the entire organization at a root cause level.
  • Mitigate potential issues by identifying the interdependencies between your assets, and limiting them to the minimum necessary connections.
  • Manage risk more effectively, by understanding the full impact of all IT operations and security decisions, and making more informed decisions.

Observability gives your teams more visibility, more context, and more confidence in decision-making and multiple layers of the organization.


Observability in AIOps

Observability is becoming even more powerful — and even more critical for every enterprise — due to the rise in AIOps.

AIOps refers to using artificial intelligence (AI) to maintain the uptime of IT infrastructure by detecting and investigating incidents faster. Done right, AIOps will not only accelerate MTTR, but it will also perform more extensive incident mapping, more exhaustive root cause analysis, and overall provide a more accurate and complete picture of an incident.

In addition, AIOps can be leveraged to identify and prevent IT issues by following the same basic process on healthy infrastructure to spot and diagnose potential issues and suggest remediation efforts for security or operational vulnerabilities in the IT estate.

The more data about the environment AIOps receives, the better it works. As such, AIOps and observability go hand-in-hand. By establishing observability across the entire IT environment, you give AI all of the data it needs to scour, analyze, and provide actionable recommendations on every asset in your IT estate.

In short: Leveraging observability and AIOps together helps decision makers like CIOs and site reliability engineers (SREs) make faster, more informed, and more accurate decisions.

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The right tools for observability in AIOps

While establishing both observability and AIOps might seem like a big lift, we’ve made it simple for enterprises. We’ve developed a single solution that combines observability and generative AI to provide AIOps out-of-the-box.

Our BMC Helix for Observability and AIOps solution is a recognized industry leader in its category that provides every essential capability to establish both observability and AIOps within your IT stack.

These core capabilities include:


To learn more about BMC Helix for Observability and AIOps, click here.

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