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  1. Stackups
  2. DevOps
  3. Performance Monitoring
  4. Performance Monitoring
  5. AppDynamics vs Grafana

AppDynamics vs Grafana

OverviewDecisionsComparisonAlternatives

Overview

AppDynamics
AppDynamics
Stacks305
Followers629
Votes68
Grafana
Grafana
Stacks18.4K
Followers14.6K
Votes415
GitHub Stars70.7K
Forks13.1K

AppDynamics vs Grafana: What are the differences?

Introduction

In this markdown, we will provide the key differences between AppDynamics and Grafana, two popular tools used in monitoring and visualization of application performance. Both tools offer powerful features and capabilities, but they differ in several aspects.

  1. Data Sources: One key difference between AppDynamics and Grafana is the source of data they utilize. AppDynamics primarily focuses on gathering performance data directly from applications and infrastructure. It offers a comprehensive set of built-in agents and integrations to collect this data. On the other hand, Grafana is more flexible as it can connect to a wide range of data sources including databases, cloud platforms, and various monitoring systems.

  2. Real-Time Monitoring vs. Historical Analysis: AppDynamics excels in real-time monitoring and provides deep insights into application performance in real-time. It can closely track and analyze transactions as they occur and quickly identify bottlenecks or issues. Grafana, on the other hand, is more suited for historical analysis and visualizing trends over time. It empowers users to create customized dashboards with historical data points and perform in-depth analysis.

  3. Alerting and Notification: AppDynamics offers robust alerting capabilities to notify users about performance issues or anomalies in real-time. It supports configurable thresholds, intelligent baselining, and can send alerts via various channels. Grafana, although primarily a visualization tool, also supports alerting but its capabilities are not as extensive as AppDynamics. Grafana's alerting is more focused on connecting with data sources and triggering alerts based on specific conditions.

  4. Intelligent Analytics: AppDynamics leverages advanced analytics and machine learning techniques to provide intelligent insights into application performance. It can automatically baseline the performance of applications and detect anomalies or deviations from normal behavior. Grafana, on the other hand, doesn't have built-in intelligent analytics capabilities. It relies on the data and metrics provided by connected data sources and displays them in customizable dashboards and graphs.

  5. User Interface and Customization: AppDynamics offers a comprehensive and intuitive user interface with pre-built UI components specifically designed for monitoring and troubleshooting applications. It provides ready-to-use dashboards, topology maps, and transaction flow maps. Grafana, being a highly customizable tool, allows users to create their own dashboards and visualizations using its flexible UI elements. It provides a wide range of plugins and community-driven dashboards for additional customization options.

  6. Licensing and Pricing: Another notable difference is the licensing and pricing models. AppDynamics is a commercial product with a subscription-based pricing model. It offers different tiers and licensing options based on the scale and features required. Grafana, on the other hand, is an open-source tool with a permissive Apache 2.0 license. It can be used and modified freely, making it a cost-effective option for organizations.

In summary, AppDynamics and Grafana differ in their data sources, real-time vs. historical analysis capabilities, alerting and notification features, intelligent analytics, user interface and customization options, as well as licensing and pricing models.

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Advice on AppDynamics, Grafana

Leonardo Henrique da
Leonardo Henrique da

Pleno QA Enginneer at SolarMarket

Dec 8, 2020

Decided

The objective of this work was to develop a system to monitor the materials of a production line using IoT technology. Currently, the process of monitoring and replacing parts depends on manual services. For this, load cells, microcontroller, Broker MQTT, Telegraf, InfluxDB, and Grafana were used. It was implemented in a workflow that had the function of collecting sensor data, storing it in a database, and visualizing it in the form of weight and quantity. With these developed solutions, he hopes to contribute to the logistics area, in the replacement and control of materials.

402k views402k
Comments
Farzeem Diamond
Farzeem Diamond

Software Engineer at IVP

Jul 21, 2020

Needs adviceonDatadogDatadogDynatraceDynatraceAppDynamicsAppDynamics

Hey there! We are looking at Datadog, Dynatrace, AppDynamics, and New Relic as options for our web application monitoring.

Current Environment: .NET Core Web app hosted on Microsoft IIS

Future Environment: Web app will be hosted on Microsoft Azure

Tech Stacks: IIS, RabbitMQ, Redis, Microsoft SQL Server

Requirement: Infra Monitoring, APM, Real - User Monitoring (User activity monitoring i.e., time spent on a page, most active page, etc.), Service Tracing, Root Cause Analysis, and Centralized Log Management.

Please advise on the above. Thanks!

1.59M views1.59M
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

Detailed Comparison

AppDynamics
AppDynamics
Grafana
Grafana

AppDynamics develops application performance management (APM) solutions that deliver problem resolution for highly distributed applications through transaction flow monitoring and deep diagnostics.

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.

End User Monitoring;Real-Time Business Transaction Monitoring;Visualize & Manage your Entire Application;Detect Business Impact and Performance Spikes;Isolate Bottlenecks in your Application;Identify Root Cause with Complete Code diagnostics;Kickass for Business: Reports;Kickass for Ops: Dashboards;Kickass for Dev: Agile Comparison
Create, edit, save & search dashboards;Change column spans and row heights;Drag and drop panels to rearrange;Use InfluxDB or Elasticsearch as dashboard storage;Import & export dashboard (json file);Import dashboard from Graphite;Templating
Statistics
GitHub Stars
-
GitHub Stars
70.7K
GitHub Forks
-
GitHub Forks
13.1K
Stacks
305
Stacks
18.4K
Followers
629
Followers
14.6K
Votes
68
Votes
415
Pros & Cons
Pros
  • 21
    Deep code visibility
  • 13
    Powerful
  • 8
    Real-Time Visibility
  • 7
    Great visualization
  • 6
    Easy Setup
Cons
  • 5
    Expensive
  • 2
    Poor to non-existent integration with aws services
Pros
  • 89
    Beautiful
  • 68
    Graphs are interactive
  • 57
    Free
  • 56
    Easy
  • 34
    Nicer than the Graphite web interface
Cons
  • 1
    No interactive query builder
Integrations
Rackspace Cloud Servers
Rackspace Cloud Servers
Microsoft Azure
Microsoft Azure
Amazon EC2
Amazon EC2
RightScale
RightScale
CloudBees
CloudBees
HP Cloud Compute
HP Cloud Compute
Boundary
Boundary
PagerDuty
PagerDuty
Graphite
Graphite
InfluxDB
InfluxDB

What are some alternatives to AppDynamics, Grafana?

New Relic

New Relic

The world’s best software and DevOps teams rely on New Relic to move faster, make better decisions and create best-in-class digital experiences. If you run software, you need to run New Relic. More than 50% of the Fortune 100 do too.

Datadog

Datadog

Datadog is the leading service for cloud-scale monitoring. It is used by IT, operations, and development teams who build and operate applications that run on dynamic or hybrid cloud infrastructure. Start monitoring in minutes with Datadog!

Kibana

Kibana

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.

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.

Raygun

Raygun

Raygun gives you a window into how users are really experiencing your software applications. Detect, diagnose and resolve issues that are affecting end users with greater speed and accuracy.

Nagios

Nagios

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

AppSignal

AppSignal

AppSignal gives you and your team alerts and detailed metrics about your Ruby, Node.js or Elixir application. Sensible pricing, no aggressive sales & support by developers.

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.

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