Azure Monitor allows an Azure Administrator to maximize the availability and performance of applications and services by collecting, analyzing, and acting on telemetry using two fundamental data types: Metrics and Logs.
**Metrics** are numerical values that describe an aspect of a system at a spec…Azure Monitor allows an Azure Administrator to maximize the availability and performance of applications and services by collecting, analyzing, and acting on telemetry using two fundamental data types: Metrics and Logs.
**Metrics** are numerical values that describe an aspect of a system at a specific point in time. Think of them as the lightweight 'vital signs' of your resources. Examples include CPU percentage, memory usage, or network throughput. Metrics are collected at regular intervals and stored in a time-series database. Because of their numerical nature and low latency, metrics are ideally suited for near real-time alerting and fast visualization on dashboards. They answer operational questions like 'Is the server response time high right now?' or 'Has the CPU load spiked?' Administrators primarily use metrics to trigger autoscaling events or fire alerts based on specific numeric thresholds.
**Logs** typically contain different kinds of data organized into records with distinct properties. They can vary from simple text messages to structured blobs of data, encompassing events, traces, and audit trails. Logs are stored in Log Analytics workspaces. Unlike metrics, logs provide deep context about *what* happened and *why*. For instance, while a metric tells you HTTP errors are increasing, a log tells you specific code exception details or which user initiated a change. To analyze logs, administrators use the Kusto Query Language (KQL), which enables complex joining, filtering, and aggregation across diverse data sources.
In summary, utilize Metrics for monitoring general health, creating visual dashboards, and setting up real-time alerts. Utilize Logs for deep troubleshooting, auditing, security analysis, and complex reporting. Mastering both is essential for effectively maintaining Azure resources.
Mastering Azure Monitor: Metrics vs. Logs
What is Azure Monitor? Azure Monitor is a comprehensive solution for collecting, analyzing, and acting on telemetry from your cloud and on-premises environments. It helps you maximize the availability and performance of your applications and services. At the core of Azure Monitor lies the distinction between its two fundamental types of data: Metrics and Logs.
1. Azure Monitor Metrics (The Numerical Data) What it is: Metrics are numerical values that describe some aspect of a system at a particular point in time. They are lightweight and capable of supporting near real-time scenarios. How it works: Metrics are stored in a time-series database. This is most effective for analyzing performance data like CPU usage, memory utilization, or network throughput. Key Characteristics: - Numerical: Only stores numbers. - Real-time: Very low latency, making them ideal for alerting. - Automatic: Most Azure resources emit standard metrics by default without configuration. - Retention: Generally stored for 93 days.
2. Azure Monitor Logs (The Contextual Data) What it is: Logs contain different kinds of data organized into records with different sets of properties. They are useful for complex analysis using the Kusto Query Language (KQL). How it works: Logs are stored in a key-value pair format in a Log Analytics Workspace. They can include events, traces, and performance data that require deeper query capabilities. Key Characteristics: - Rich Data: Can store text, complex structures, and descriptive data. - Queryable: Uses KQL to correlate data across multiple sources. - Retention: Configurable (typically 31 days to 2 years).
Why is this important? Understanding the difference is crucial for the AZ-104 exam and real-world administration because the usage scenarios differ completely. If you need to know "Is the server up?" you look at Metrics. If you need to know "Why did the server crash?" you look at Logs. Metrics drive automated scaling and alerting, while Logs drive root cause analysis and security auditing.
How it works: The Data Flow 1. Collection: Data is collected from applications, operating systems (via agents), Azure resources, and the Azure subscription. 2. Routing: - Metrics flow into the Azure Monitor Metrics store. - Logs (and log-based metrics) flow into a Log Analytics Workspace, Azure Storage, or Event Hubs. 3. Visualization/Action: Metrics appear in Azure Metrics Explorer; Logs are analyzed in Log Analytics. Both can trigger Alerts.
Exam Tips: Answering Questions on Azure Monitor metrics and logs When facing questions about monitoring in the AZ-104 exam, look for specific keywords to determine the correct answer:
Choose METRICS if the scenario involves: - Real-time alerting: You need to be notified within under a minute of a CPU spike. - Autoscaling: You are configuring a Virtual Machine Scale Set to scale out based on CPU > 75%. - Dashboards: You need simple numerical graphs showing throughput over the last hour. - Retention of 93 days: The question specifically mentions standard metric retention limits.
Choose LOGS (Log Analytics) if the scenario involves: - Complex Queries: You need to correlate data from multiple VMs or different resource types. - Deep Analysis: You are investigating a specific error message or pattern of failure. - KQL: The question mentions writing a query using Kusto Query Language. - Text-based data: You need to analyze syslog entries, IIS logs, or custom application traces. - Diagnostic Settings: Remember, platform logs (like activity logs) are often viewed typically, but to query them or keep them long-term, you must configure Diagnostic Settings to send them to a Log Analytics Workspace.