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  1. Stackups
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  4. Monitoring Tools
  5. Azure Monitor vs Kibana

Azure Monitor vs Kibana

OverviewDecisionsComparisonAlternatives

Overview

Kibana
Kibana
Stacks20.6K
Followers16.4K
Votes262
GitHub Stars20.8K
Forks8.5K
Azure Monitor
Azure Monitor
Stacks60
Followers184
Votes0

Azure Monitor vs Kibana: What are the differences?

Introduction

In this article, we will discuss the key differences between Azure Monitor and Kibana. Azure Monitor is a comprehensive monitoring solution provided by Microsoft for monitoring resources and applications hosted on the Azure cloud platform. On the other hand, Kibana is an open-source data visualization and exploration tool, primarily used for analyzing and visualizing data stored in Elasticsearch.

  1. Data Source: Azure Monitor primarily collects monitoring data from the resources hosted on Azure, such as virtual machines, containers, and Azure services like Azure App Service or Azure SQL Database. It collects and analyzes performance metrics, logs, and diagnostic telemetry data. On the other hand, Kibana requires Elasticsearch as the data source. It is designed specifically to work with Elasticsearch to visualize and analyze data stored in Elasticsearch indices.

  2. Integration with Azure Ecosystem: Azure Monitor is tightly integrated with the entire Azure ecosystem. It seamlessly integrates with other Azure services and provides insights into Azure resources and services. It can also leverage Azure Automation, Azure Functions, and Log Analytics to automate tasks and trigger actions based on monitoring data. In contrast, while Kibana can be used with Elasticsearch on the Azure platform, it does not have the same level of native integration with other Azure services as Azure Monitor.

  3. Built-in Alerting and Action Groups: Azure Monitor provides built-in alerting capabilities, allowing users to create alerts based on customized conditions and thresholds. It also supports action groups, which enable users to define a list of actions to be taken when an alert is triggered, such as sending notifications or running automated remediation tasks. Kibana, on the other hand, does not have built-in alerting capabilities. It focuses more on data visualization and exploration.

  4. Log Analytics and Query Language: Azure Monitor leverages Log Analytics, which provides powerful query and analysis capabilities for log and performance data collected by Azure Monitor. It uses a proprietary query language called Kusto Query Language (KQL) to retrieve and analyze data. Kibana, on the other hand, uses its own query language called Elasticsearch Query DSL. It provides a flexible and powerful way to search and analyze data stored in Elasticsearch indices.

  5. Visualization and Dashboards: Kibana is known for its extensive capabilities for data visualization and creating interactive dashboards. It provides a wide range of visualization options, including bar charts, line charts, pie charts, and maps, to help users explore and present their data effectively. Azure Monitor also provides visualization capabilities, but they are more focused on monitoring specific Azure resources and services, rather than providing a comprehensive range of data visualization options like Kibana.

  6. Ease of Use and Learning Curve: Azure Monitor is designed to be user-friendly and provides a familiar interface for users familiar with the Azure portal and services. It provides predefined monitoring solutions and templates that can be easily configured and deployed. Kibana, on the other hand, has a steeper learning curve and requires some level of expertise in Elasticsearch and data analysis. It requires users to define their own indices and mappings before being able to visualize and analyze data effectively.

In summary, Azure Monitor is a comprehensive monitoring solution tightly integrated with the Azure ecosystem, whereas Kibana is an open-source data visualization tool primarily used with Elasticsearch. Azure Monitor collects monitoring data from Azure resources, while Kibana requires Elasticsearch as the data source. Azure Monitor provides built-in alerting and integration with other Azure services, whereas Kibana focuses more on data visualization and exploration. Azure Monitor uses Log Analytics and Kusto Query Language for data analysis, while Kibana uses Elasticsearch Query DSL. Kibana offers extensive visualization capabilities, while Azure Monitor provides more resource-specific monitoring. Azure Monitor is user-friendly with predefined solutions, while Kibana has a steeper learning curve.

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Advice on Kibana, Azure Monitor

matteo1989it
matteo1989it

Jun 26, 2019

ReviewonKibanaKibanaGrafanaGrafanaElasticsearchElasticsearch

I use both Kibana and Grafana on my workplace: Kibana for logging and Grafana for monitoring. Since you already work with Elasticsearch, I think Kibana is the safest choice in terms of ease of use and variety of messages it can manage, while Grafana has still (in my opinion) a strong link to metrics

757k views757k
Comments
StackShare
StackShare

Jun 25, 2019

Needs advice

From a StackShare Community member: “We need better analytics & insights into our Elasticsearch cluster. Grafana, which ships with advanced support for Elasticsearch, looks great but isn’t officially supported/endorsed by Elastic. Kibana, on the other hand, is made and supported by Elastic. I’m wondering what people suggest in this situation."

663k views663k
Comments
abrahamfathman
abrahamfathman

Jun 26, 2019

ReviewonKibanaKibanaSplunkSplunkGrafanaGrafana

I use Kibana because it ships with the ELK stack. I don't find it as powerful as Splunk however it is light years above grepping through log files. We previously used Grafana but found it to be annoying to maintain a separate tool outside of the ELK stack. We were able to get everything we needed from Kibana.

2.29M views2.29M
Comments

Detailed Comparison

Kibana
Kibana
Azure Monitor
Azure Monitor

Kibana is an open source (Apache Licensed), browser based analytics and search dashboard for Elasticsearch. Kibana is a snap to setup and start using. Kibana strives to be easy to get started with, while also being flexible and powerful, just like Elasticsearch.

It provides sophisticated tools for collecting and analyzing telemetry that allow you to maximize the performance and availability of your cloud and on-premises resources and applications.

Flexible analytics and visualization platform;Real-time summary and charting of streaming data;Intuitive interface for a variety of users;Instant sharing and embedding of dashboards
Store and analyze all your operational telemetry in a centralized, fully managed, scalable data store that’s optimized for performance and cost; Test your hypotheses and reveal hidden patterns using the advanced analytic engine, interactive query language, and built-in machine learning constructs; Integrate with popular DevOps, issue management, IT service management, and security information and event management tools
Statistics
GitHub Stars
20.8K
GitHub Stars
-
GitHub Forks
8.5K
GitHub Forks
-
Stacks
20.6K
Stacks
60
Followers
16.4K
Followers
184
Votes
262
Votes
0
Pros & Cons
Pros
  • 88
    Easy to setup
  • 65
    Free
  • 45
    Can search text
  • 21
    Has pie chart
  • 13
    X-axis is not restricted to timestamp
Cons
  • 7
    Unintuituve
  • 4
    Elasticsearch is huge
  • 4
    Works on top of elastic only
  • 3
    Hardweight UI
No community feedback yet
Integrations
Logstash
Logstash
Elasticsearch
Elasticsearch
Beats
Beats
Jira
Jira
Azure DevOps
Azure DevOps
PagerDuty
PagerDuty
BindPlane
BindPlane

What are some alternatives to Kibana, Azure Monitor?

Grafana

Grafana

Grafana is a general purpose dashboard and graph composer. It's focused on providing rich ways to visualize time series metrics, mainly though graphs but supports other ways to visualize data through a pluggable panel architecture. It currently has rich support for for Graphite, InfluxDB and OpenTSDB. But supports other data sources via plugins.

Prometheus

Prometheus

Prometheus is a systems and service monitoring system. It collects metrics from configured targets at given intervals, evaluates rule expressions, displays the results, and can trigger alerts if some condition is observed to be true.

Nagios

Nagios

Nagios is a host/service/network monitoring program written in C and released under the GNU General Public License.

Netdata

Netdata

Netdata collects metrics per second & presents them in low-latency dashboards. It's designed to run on all of your physical & virtual servers, cloud deployments, Kubernetes clusters & edge/IoT devices, to monitor systems, containers & apps

Zabbix

Zabbix

Zabbix is a mature and effortless enterprise-class open source monitoring solution for network monitoring and application monitoring of millions of metrics.

Sensu

Sensu

Sensu is the future-proof solution for multi-cloud monitoring at scale. The Sensu monitoring event pipeline empowers businesses to automate their monitoring workflows and gain deep visibility into their multi-cloud environments.

Graphite

Graphite

Graphite does two things: 1) Store numeric time-series data and 2) Render graphs of this data on demand

Lumigo

Lumigo

Lumigo is an observability platform built for developers, unifying distributed tracing with payload data, log management, and real-time metrics to help you deeply understand and troubleshoot your systems.

StatsD

StatsD

It is a network daemon that runs on the Node.js platform and listens for statistics, like counters and timers, sent over UDP or TCP and sends aggregates to one or more pluggable backend services (e.g., Graphite).

Jaeger

Jaeger

Jaeger, a Distributed Tracing System

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