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The Value of Observability in an Enterprise

The Value of Observability in an Enterprise

The Value of Observability in an Enterprise

Solutions Review’s Premium Content Series is a collection of contributed articles written by industry experts in enterprise software categories. In this feature, Capgemini Americas‘ Isaac Rousso offers commentary on the value of observability in an enterprise setting, with examples.

More and more, an essential requirement for managing IT operations in today’s complex digital enterprises is the availability of high-quality monitoring data, programmatic analysis, incident correlation and systematic response formulation. This is where observability comes into play.

Research shows that by 2026, seventy percent of organizations that successfully applied observability will achieve shorter latency for decision-making, enabling competitive advantage for target business or IT processes.

What is Observability?

Observability is the ability to gain insight into the internal workings of a system and business processes by analyzing operational data from its outputs and then correlating insights. Observability in an enterprise is important because it allows developers and IT teams to quickly detect and diagnose issues and make improvements – through programmatic corrective measures, to the system over time. Ninety one percent of IT decision makers see observability as critical at every stage of the software lifecycle, citing the biggest benefits to planning and operations.

Essential to observability are three types of data, referred to as “three pillars”:

  1. Logs are files that keep track of events, warnings, and errors as they occur within a software environment. Most logs include contextual information, such as the time an event occurred.
  2. Metrics are quantifiable measurements that allow organizations to keep track of the overall health and performance of applications.
  3. Traces track a request or action as it moves through the different parts of a distributed system.

Having access to these pillars might not make systems more observable, but the analysis and pattern correlation of the data offers powerful tools that, if understood well and done correctly, can open the door to build stronger and more resilient systems across the technology business landscape, and can adopt a culture to drive a highly effective observability capability.

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The Value of Enterprise Observability

Monitoring vs. Observability

Monitoring is the continuous observation and measurement of a system or application to ensure that it is performing as expected. This includes collecting data on key performance indicators (KPIs) such as response time, error rates, and throughput, and alerting business and IT teams when these metrics fall outside of desired ranges. Monitoring is important because it provides visibility to operating anomalies in business and IT systems. With this awareness, teams ensure that systems are always up and running, and that any issues are identified and resolved before they have an impact across the business ecosystem(s).

However, monitoring does not explain why a system is not working properly. It provides transparency to situations and system characteristics that are foreseen in advance (known knowns). Without this complete overview, it is impossible to find the exact root cause since there might be several hundreds, or even thousands, of processes in place. It is also not sufficient to measure performance since it won’t measure a business or system operation from end to end.

On the contrary, observability goes the extra mile and enables the identification of the “unknown unknowns.” Utilizing the three types of data, it anticipates failures before they occur by analyzing trends and patterns and alerting teams before failures occur, proactively recommends actions (the next best step) ahead of failures using advanced analysis, and initiates “self-healing” capabilities for tasks that can be performed based on regular previously observed and corrected events. Additionally, observability provides insights and early warnings to events and failures in business processes that may be early warnings to a system or other underlying conditions.

These observability behaviors can occur to mitigate multiple types of anomalies and conditions, which lead us to multiple types of observability:

  • Digital Experience is aimed at verifying the desired digital experience for the customer, employee, and partner and can be achieved relying on pre-production testing and production monitoring.
  • Business is monitoring and collecting data pertaining to business activities, such as business transaction monitoring, business KPI monitoring, business activity anomalies, and process monitoring.
  • Process is targeted at monitoring for process anomalies that could impact some aspect of business execution, which includes monitoring the various systems utilized in the execution of a business process or sub-process.
  • Application relies on the three types of data, which are metrics, logs and traces pertaining to the “current” health of an application. This type anticipates and mitigates potential disruption in a business application that could impact the performance of business activity.
  • Data is the type that is concerned about eliminating data downtime and marshalling real time response to data anomalies at the point of data processing. This includes data reliability, systematic identification of data quality and data integrity issues.
  • Security is aimed at threat detection, isolation and response and includes monitoring for different types of threats across the ‘attack surface area’. This includes monitoring potential access points but also business information. Securing confidential and sensitive data is not only critical for business, but also for meeting regulatory or compliance requirements.
  • Infrastructure relies on the three types of data, which are metrics, logs and traces collected via monitoring mechanisms and includes recognizing server and serverless anomalies that may impact the health of running infrastructure services.

All in all, monitoring can also assist in managing, but observability allows you to organize data and applications, providing even more clarity into your environment. Together, observability and monitoring provide IT teams with the visibility and insights they need to manage complex digital ecosystems and ensure that they are always performing at their best, end to end.

How to Gain Observability Success

To help an enterprise succeed in their observability initiatives, below are important objectives that leaders should take into consideration:

  • Predict and proactively resolve issues before they occur
  • Monitor on prem and cloud services
  • Minimize response time through programmatic response
  • Respond as incidents occur or are identified
  • Adopt industry standards to drive adoption of observability practices across the system landscape
  • Instrument applications based on a “Code for monitoring” principle
  • Simplify the technical landscape to aid in responsiveness
  • Develop a data strategy to facilitate collection, management, and analysis of operational data

Observability is more than simply a fancy name for monitoring. As enterprises step into a more decentralized IT operating platform, it’s clear that observability is becoming a fundamental necessity. Without the capability to combine and analyze the data across the operating platform(s), issues may arise ranging from incomplete application performance to major security problems. For organizations to succeed, it will be critical for them to implement an observability platform of robust monitoring, systematic correlation analysis and programmatic response to differentiate themselves from their competitors and perform in a highly dynamic and complex digital world.

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Isaac Rousso
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