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When application issues arise, they impact customers and business operations. Teams rely on cloud observability and cloud monitoring to quickly identify and resolve these issues.
Monitoring and observability are two approaches for identifying the root causes of problems. Monitoring alerts you when something goes wrong, whereas observability tells you about the ‘what,’ ‘why,’ behind the issues, and ‘how’ to resolve them. Let’s explore their functionalities and roles in modern software development to know which tool wins this cloud observability vs. cloud monitoring battle.
Observability is the capacity to comprehend the inner workings of a complex system by scrutinizing its external results. When a system demonstrates observability, users can pinpoint the root cause of a performance problem by analyzing the data it produces without needing extra testing or coding.
This concept came from control theory, an engineering principle that signifies the capability to diagnose internal issues from the outside. For example, automotive diagnostic systems provide observability for mechanics, allowing them to understand why a car fails to start without taking it apart.
Monitoring in DevOps involves assessing a system’s health by collecting and analyzing data from IT systems using predefined metrics and logs. It helps measure the application’s health by setting alerts for critical thresholds, like 100% disk usage, to prevent downtime. Additionally, monitoring provides valuable insights into long-term trends and usage patterns, not just mere functioning.
While monitoring is effective for detecting known failures and system performance, it has limitations. To be effective, you must know which metrics and logs to track. Otherwise, you can miss critical production failures and other problems.
Cloud observability vs. Cloud monitoring: The difference lies in detecting expected and potential issues. At its core, monitoring is reactive, while observability takes a proactive approach. Both rely on the same type of telemetry data, often called the three pillars of observability.
These three pillars of observability include:
During monitoring, teams use this telemetry data to define metrics internally, create predefined dashboards, and set up notifications. Moreover, they identify and document dependencies, revealing how each component of an application relies on other components, applications, and IT resources.
Observability and monitoring tools delve beyond tracking internal states and addressing problems. These platforms are crucial to quickly solving problems, streamlining pipelines, and enabling increased focus on core business activities and innovation.
Let’s delve deeper into various types of tools and approaches to observability and monitoring:
Observability Platforms: These platforms enable teams to seamlessly integrate monitoring, logging, and tracing across their IT environment, offering a comprehensive view of the system’s status, even in distributed systems. Some platforms may include user experience and business context to provide a more comprehensive performance assessment. Depending on the platform, they are designed to visualize both on-premises systems and complex multi-cloud environments.
Open Source: Open-source data observability tools, such as OpenTelemetry, help teams in monitoring and debugging applications, gathering log and metric data, and performing tracing. While these tools offer certain observability functions, they may only cover some aspects and are often combined with other tools.
Automation: Observability automation extends existing automation within the CI/CD pipeline, further freeing DevOps teams to focus on core responsibilities. For example, IBM Instana Observability offers advanced automation features that improve the CI/CD pipeline. It achieves this by automating the discovery of applications, infrastructure, and services, eliminating the requirement for developers to manually code application and service links with each update. Additionally, leveraging AI-assisted troubleshooting, IBM Instana vs dynatrace can predict incidents and automate remediation. This fully automated application performance management system meticulously monitors each service, traces every request, and profiles every strategy.
IBM Instana provides a comprehensive automated enterprise observability platform that delivers the context for informed decision-making and ensures optimal application performance. For instance, IBM Instana offers the following features and advantages:
IBM Instana offers various use cases for observability across multiple industries and IT environments:
The decision between observability and monitoring is more than a one-size-fits-all choice for businesses. It helps you analyze your organization’s needs, goals, and infrastructure. Observability offers proactive, in-depth insights for long-term optimization, while monitoring excels at immediate issue detection and response. To make the right choice, consider the strengths of each approach and, in many cases, opt for a balanced combination that aligns with your business objectives. This strategic approach ensures that you are well-equipped to maintain your IT systems’ health and performance effectively.