Azure Application Insights vs Splunk

Overview

Splunk

Stacks772

Followers1.0K

Votes20

Azure Application Insights

Stacks343

Followers288

Votes12

Azure Application Insights vs Splunk: What are the differences?

Introduction

Azure Application Insights and Splunk are both popular tools used in the field of application monitoring and management. While they serve similar purposes, there are several key differences that set them apart. In this article, we will explore the main differences between Azure Application Insights and Splunk.

Data Storage: One of the primary differences between Azure Application Insights and Splunk is their data storage approach. Azure Application Insights stores its data in the cloud, providing scalability and easy access for analysis. On the other hand, Splunk offers on-premises data storage, giving organizations full control and privacy over their data.
Integration with Azure: Azure Application Insights is deeply integrated with the Microsoft Azure cloud platform. It provides out-of-the-box integration with Azure services and resources, making it seamless to gather telemetry data from various Azure applications. In contrast, Splunk is a standalone tool that can be integrated with different systems and platforms, including Azure, but requires additional configuration and setup.
Ease of Use: Azure Application Insights is designed with ease of use in mind. It offers a user-friendly interface, pre-built dashboards, and quick setup options, allowing users to start monitoring their applications with minimal effort. Splunk, on the other hand, has a steeper learning curve and may require more technical expertise to set up and configure.
Query Language: Another significant difference lies in the query language used by the two tools. Azure Application Insights utilizes a query language called Kusto Query Language (KQL), which is specifically designed for querying large amounts of structured, semi-structured, and unstructured data. Splunk uses its proprietary search language, which has its own syntax and features, making it different from other query languages.
Pricing Model: The pricing models of Azure Application Insights and Splunk also differ. Azure Application Insights follows a consumption-based model, where you pay for the amount of data ingested and stored, as well as additional features used. Splunk, on the other hand, follows a data volume-based pricing model, where the cost is based on the amount of data indexed and the retention period.

In summary, Azure Application Insights and Splunk differ in their data storage approach, integration with Azure, ease of use, query language, and pricing model. Azure Application Insights is cloud-based, tightly integrated with Azure, user-friendly, uses KQL, and follows a consumption-based pricing model. Splunk, on the other hand, offers on-premises data storage, can be integrated with various systems, has a steeper learning curve, uses its own search language, and follows a data volume-based pricing model.

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Detailed Comparison

Splunk	Azure Application Insights
It provides the leading platform for Operational Intelligence. Customers use it to search, monitor, analyze and visualize machine data.	It is an extensible Application Performance Management service for developers and DevOps professionals. Use it to monitor your live applications. It will automatically detect performance anomalies, and includes powerful analytics tools.
Predict and prevent problems with one unified monitoring experience; Streamline your entire security stack with Splunk as the nerve center; Detect, investigate and diagnose problems easily with end-to-end observability	Extensible Application Performance Management (APM) service; Monitor your live applications; Automatically detect performance anomalies
Statistics
Stacks 772	Stacks 343
Followers 1.0K	Followers 288
Votes 20	Votes 12
Pros & Cons
Pros 3 Alert system based on custom query results 3 API for searching logs, running reports 2 Splunk language supports string, date manip, math, etc 2 Query engine supports joining, aggregation, stats, etc 2 Custom log parsing as well as automatic parsing Cons 1 Splunk query language rich so lots to learn	Pros 6 Focus in detect performance anomalies and issues 3 Integrated with Azure 1 User flow 1 Live Metrics 1 Availability tests (Heart Beat check) Cons 2 Difficult to surface information 1 UI is clunky and gets in the way 1 Custom instrumentation via code only

What are some alternatives to Splunk, Azure Application Insights?

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 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!

Papertrail

Papertrail helps detect, resolve, and avoid infrastructure problems using log messages. Papertrail's practicality comes from our own experience as sysadmins, developers, and entrepreneurs.

Logmatic

Get a clear overview of what is happening across your distributed environments, and spot the needle in the haystack in no time. Build dynamic analyses and identify improvements for your software, your user experience and your business.

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.

Loggly

It is a SaaS solution to manage your log data. There is nothing to install and updates are automatically applied to your Loggly subdomain.

Apache Spark

Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.

Logentries

Logentries makes machine-generated log data easily accessible to IT operations, development, and business analysis teams of all sizes. With the broadest platform support and an open API, Logentries brings the value of log-level data to any system, to any team member, and to a community of more than 25,000 worldwide users.

Logstash

Logstash is a tool for managing events and logs. You can use it to collect logs, parse them, and store them for later use (like, for searching). If you store them in Elasticsearch, you can view and analyze them with Kibana.

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.

Related Comparisons

Azure Application Insights vs Splunk: What are the differences?

Introduction

Data Storage: One of the primary differences between Azure Application Insights and Splunk is their data storage approach. Azure Application Insights stores its data in the cloud, providing scalability and easy access for analysis. On the other hand, Splunk offers on-premises data storage, giving organizations full control and privacy over their data.
Integration with Azure: Azure Application Insights is deeply integrated with the Microsoft Azure cloud platform. It provides out-of-the-box integration with Azure services and resources, making it seamless to gather telemetry data from various Azure applications. In contrast, Splunk is a standalone tool that can be integrated with different systems and platforms, including Azure, but requires additional configuration and setup.
Ease of Use: Azure Application Insights is designed with ease of use in mind. It offers a user-friendly interface, pre-built dashboards, and quick setup options, allowing users to start monitoring their applications with minimal effort. Splunk, on the other hand, has a steeper learning curve and may require more technical expertise to set up and configure.
Query Language: Another significant difference lies in the query language used by the two tools. Azure Application Insights utilizes a query language called Kusto Query Language (KQL), which is specifically designed for querying large amounts of structured, semi-structured, and unstructured data. Splunk uses its proprietary search language, which has its own syntax and features, making it different from other query languages.
Pricing Model: The pricing models of Azure Application Insights and Splunk also differ. Azure Application Insights follows a consumption-based model, where you pay for the amount of data ingested and stored, as well as additional features used. Splunk, on the other hand, follows a data volume-based pricing model, where the cost is based on the amount of data indexed and the retention period.

Azure Application Insights vs Splunk

Overview

Azure Application Insights vs Splunk: What are the differences?