Monitoring and observability are closely related but serve different purposes in managing and understanding systems like applications, infrastructure, and networks. Here’s a breakdown of each:
Monitoring:

Definition: Monitoring refers to the process of collecting, analyzing, and acting on data about a system's performance and health. It's typically predefined with specific metrics or logs that are collected.
Purpose: Monitoring aims to track known issues or key performance indicators (KPIs) like CPU usage, memory consumption, error rates, or response times. It helps teams ensure systems are running within expected thresholds.
Scope: Monitoring is often focused on specific, predefined events and conditions, allowing you to alert or react to specific, known issues. For example, a sudden spike in CPU usage or a server going down.
Tools: Prominent tools include Prometheus, Nagios, Zabbix, and New Relic.
Use Case: Monitoring answers the question, “Is my system working as expected?” It tells you when something goes wrong based on pre-configured alerts or metrics.

Observability:

Definition: Observability is a broader concept that refers to the ability to infer the internal state of a system based on the data (logs, metrics, and traces) it generates. Unlike monitoring, observability focuses on exploring unknown or emergent issues that have not been anticipated.
Purpose: The goal of observability is to understand why something is happening, even if the problem wasn’t previously foreseen. It deals with investigating the behavior of complex systems, identifying patterns, and diagnosing problems across multiple components.
Scope: Observability is based on three pillars:
Metrics (quantitative data like response times or error rates)
Logs (qualitative data on discrete events)
Traces (end-to-end tracking of requests across services)
Tools: Tools include Grafana, Datadog, Elastic Stack (ELK), Jaeger, and Honeycomb.
Use Case: Observability answers the question, “Why did something go wrong?” It helps in deep analysis, troubleshooting, and understanding systems' internal workings.

Key Differences:

Proactive vs Reactive: Monitoring is more proactive, ensuring systems behave as expected, while observability is reactive, helping diagnose issues when they arise.
Predefined vs Dynamic: Monitoring relies on predefined metrics and thresholds. Observability is more dynamic and investigative, enabling you to explore unknowns.
Specificity vs Holistic View: Monitoring provides a specific, focused view of certain metrics. Observability offers a holistic view of system behavior through various types of data (logs, metrics, traces).

In short:

Monitoring is about tracking known issues and system health.
Observability is about understanding complex system behaviors and diagnosing the unknown.



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Security #Observability with #eBPF

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Security #Observability with #eBPF

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