Azure Monitor - Modern Observability Tools | Microsoft Azure (2024)

FAQs

Is Azure Monitor an observability tool? ›

Gain end-to-end observability for your applications, infrastructure, and network.

1. Azure Monitor. It is a comprehensive Azure monitoring tool for the Azure cloud platform. It provides a unified view of your application and infrastructure health, with features such as log analytics, metrics, and alerts.

Azure Monitor is a comprehensive monitoring solution for collecting, analyzing, and responding to monitoring data from your cloud and on-premises environments. You can use Azure Monitor to maximize the availability and performance of your applications and services.

Azure Monitor uses Kusto Query Language (KQL) for querying and analyzing data. CloudWatch is a cloud-based service and can be deployed on AWS. It is available in both SaaS and on-premises deployment models. CloudWatch integrates with other AWS services including Amazon EC2, Amazon RDS, Amazon VPC, AWS Lambda, and more.

You're monitoring for known or predictable failures. Observability: The ability to understand what's happening inside a system by looking at the output data. An observability solution helps you analyze this data to assess the system's health and find ways to fix problems in your IT infrastructure.

In this article

Observability is the ability to understand the internal state of a system from the data it produces and the ability to explore that data to answer questions about what happened and why. Azure API Management helps organizations centralize the management of all APIs.

Features of Azure Monitor that are enabled by default don't incur any charge. This includes collection and alerting on the Activity log and collection and analysis of platform metrics. Several other features don't have a direct cost, but you instead pay for the ingestion and retention of data that they collect.

To put it simply - Azure Monitor is a set of services and features to monitor Azure and non-Azure resources. One of these services in Azure Monitor is Log Analytics. Log Analytics is a service to store and query logs and metrics. Azure Sentinel is using certain features of Azure Monitor as a platform.

Benefits of Azure Monitor

Visualizations, including charts and graphs for insights into resource performance. Application Insights, built-in metrics for understanding resource use, including inbound and outbound data, state, and application performance. Easy-to-create alerts.

In conclusion, Azure Monitor and Log Analytics collectively offer a robust solution for monitoring Azure resources. While Azure Monitor provides a lot of features including aggregation of logs, real-time insights and performance metrics, Log Analytics allows advanced query capabilities and extensive log data analysis.

Does Azure Monitor collect logs? ›

Azure Monitor Logs is a feature of Azure Monitor that collects and organizes log and performance data from monitored resources.

Log Analytics is a tool in the Azure portal to edit and run log queries from data collected by Azure Monitor logs and interactively analyze their results. You can use Log Analytics queries to retrieve records that match particular criteria, identify trends, analyze patterns, and provide various insights into your data.

On 31 August 2024, we'll retire the Log Analytics agent that you use in Azure Monitor. Before that date, you'll need to start using the Azure Monitor agent to monitor your VMs and servers in Azure. The Azure Monitor agent provides new features and capabilities, including: Centralized configuration for multiple VMs.

Monitoring is a critical core component of observability. Comprehensive monitoring creates descriptive metrics, events, logs, and traces that measure what is essential in an easily identifiable and retrievable manner. Historic records are stored alongside current measurements to build a broad picture of the system.

ML monitoring primarily answers "what" is happening within the ML system, tracking key metrics and indicators to identify deviations and issues. On the other hand, ML observability delves into the "why" and "how" aspects, providing in-depth insights into the internal workings of the ML pipeline.

DevOps observability enables teams to gain a better understanding of how their systems are performing during the entire development cycle, a vital aspect of system performance.