Monitoring vs. Observability

Modernization of current systems, which have shifted from centralized to distributed models, turned visibility into a complex challenge in any infrastructure, almost an impossible mission. In hybrid, multi-cloud or multi-region environments, measuring, monitoring and parameterizing applications is now an arduous task.

Additionally, with such complex environments, being able to discern between noise and signals is of utmost importance. This is where our saviors come in: monitoring and observability tools.

Visibility into our infrastructures is now crucial. Without it, we’re living a dangerous illusion. Monitoring tools are essential for achieving observability—the ability to predict, prevent, and resolve system issues more effectively, quickly, and concisely.

Imagine navigating a vast, complex cloud landscape without a map. That’s how it feels without proper monitoring. Cloud vendors offer basic tools like Amazon CloudWatch, Google Cloud Monitoring, and Azure Monitoring, but they’re like tiny flashlights in a pitch-black cave. To see the whole picture, we need specialized software that collects and analyzes logs, metrics, and traces—the breadcrumbs left by our applications. It’s like assembling a puzzle to understand how our systems are performing. The choice of tools and level of detail depends on our unique needs and resources.

Observability, often confused with its counterpart, monitoring, is based on the same principles and/or tools, but the limited scope becomes the key factor that differentiates the two. Imagine monitoring your car’s engine temperature. That’s like monitoring. It tells you something’s hot, but not why. Observability is like a mechanic who knows the engine inside out, understanding the root cause of the overheating. It’s about using monitoring data—traces, metrics, and logs—to build a comprehensive picture of how our systems are working.

These three concepts can be defined as:

• Logs/Records: Detailed extracts of an event, serving as the primary source for any troubleshooting, indicating the link where the chain broke.
• Trace: Tracking the path through a system, leaving footprints in the multiple instances through which it travels in our system.
• Metric: A numerical, percentage, or averaged value of the status of a resource, such as the amount of memory used, the percentage of disk available, and the processor.

These become fundamental in the visibility of the distributed systems that we have today. We are changing from a monolithic ecosystem to a distributed environment, such as microservices, which turn our systems into multiple gears and become a challenge when monitoring the traceability of our environment’s flow.

Benefits

The correct use of our monitoring tools in search of being able to implement observability in our system brings with it the following:

• Proactive Detection: This allows you to detect problems from the beginning of the incident, identify them, and work on mitigation before they affect users.
• Reduced Resolution Time: This allows you to reduce incident resolution time by 50% and reduce the impact of the incident.
• In-depth Analysis: Facilitates the understanding of decentralized systems.
• Scalability: Allows you to measure what is necessary for your ecosystem to manage growth correctly.
• Improved user experience
• Process automation

Common Tools

Among the most common tools used today for this arduous task, we have:

• Monitoring and Alerts: Prometheus, Zabbix, Nagios.
• Data Visualization: Grafana, Kibana, Tableau.

To achieve an observable system where there is a deep understanding, it is recommended to follow the following recommendations:

• Data Collection: Ensure that all our systems, services, or applications are configured correctly so that we can collect status information through logs, metrics, and/or traces.
• Data Centralization: Unite the collected information at one point to streamline the data analysis and event correlation process.
• Alerting: Alerts should be configured based on thresholds and abnormal behavior patterns.
• Differentiate alerts and noise: Only place those monitors you want to monitor and receive alerts for instead of receiving a vast amount of information that clouds the view of what is truly important.
• Visualization: It becomes necessary to see clearly and concisely, through a graphical interface, the indicators of our infrastructure.
• Automation of responses: To reduce incident response time, relevant actions such as escalations or service restarts should be automated.
• Staff training: Keeping your staff trained allows you to act immediately in the face of incidents, as well as the ability to perceive them in time.
• Documentation: The efficiency of the response before and during an incident comes from clear documentation of the managed infrastructure.
• Continuous Improvement: Finally, and most importantly, the review of monitoring processes and tools, as well as the optimization of thresholds, becomes essential since this is a continuous improvement process.

Conclusion

Monitoring everything that could affect our services or provide valuable infrastructure insights is a daily challenge. Without an evolving monitoring strategy, our systems can become unpredictable. Remember, no system is perfect. Focusing on constant optimization is key. As Voltaire said, ‘Perfect is the enemy of good.’ Setting unattainable goals can hinder progress. Observability, achieved through diligent monitoring, provides the security of finding incident root causes, not just putting out fires temporarily. This prevents leaving hidden risks in our systems.