5 data sources that turn APM data into application performance analytics
In a previous article, we wrote about how Splunk can be used to analyze application performance . And today we will talk about the main sources of data for analytics of application performance, according to the version of Bill Emment, director of marketing solutions at Splunk.
Applications are critical to the success of any organization. But are you doing your best to optimize them? Here are five data sources that can help you improve application performance analytics in a short time.
APM Tool Logs
Examples: logs from Dynatrace, New Relic, AppDynamics, Pulseway, LogicMonitor, Stackify, Boomerang.js, Jmeter, CA Technologies, Idera, Ipswitch
If you already have APM tools, then from their logs you can get excellent information on monitoring end activities users, page errors, bytecode instrumentation. These logs can display infrastructure problems and bottlenecks that are not visible when examining each system separately, for example, a slow DNS resolution that causes a complex web application to fail when trying to access content and modules in different systems. When you track these logs, you can receive early warnings about application problems to fix them before they are seen by users.
Custom Application Logs and Debugs
Example: custom applications
For developers, debug logs and user application logs are often the most requested data sources because they provide the finest information about application status, variables, and errors. Analyzing these logs can help identify the causes of application crashes, memory leaks, performance degradation, and vulnerabilities. In user applications, the exact type of data sources varies by application.
CRM, ERP and other business applications
Examples: SAP, SFDC, Oracle, Microsoft Exchange, Microsoft Dynamics.
Many of the applications integrate with CRM and ERP systems, so getting information about the usage and performance of these systems can give you an idea of how your applications work. CRM can provide complete information and a record of events leading to customer escalation , and when combined with other data sources, CRM can provide indicators of deeper problems. Like other application entries, ERP logs are needed when debugging performance and reliability issues due to complex interactions between many systems. In addition, they are useful for capacity planning.
Automation, configuration and deployment tools
Examples: Puppet Enterprise, Ansible Tower, Chef, SaltStack, Rundeck, API data, web hosts, or launch logs.
These data sources are key because automation tools help you understand the situation when new releases are launched. Monitoring, analyzing and managing this data gives you the opportunity to compare the performance of the application before / after the update, as well as the use and availability of each specific version.
Examples: static analysis and module testing logs (SonarQube, Tox, PyTest, RubyGem MiniTest, Bacon, Go Testing), server creation logs and performance indicators
Monitoring sample data can help you understand:
- How many technical debts and problems are solved
- How ready is your next release
- How many tests are performed per hour and what tests are performed
If you combine test data with assembly data, you can start monitoring the performance of the assembly and release, as well as draw the first conclusions about the release quality. You can understand the trends of the percentage of errors and decide whether an assembly is ready for release. Understanding code quality can also help technical support staff prepare for any additional volume of calls or for any specific problems that may arise. For example, the CSAA uses data from actual operations to determine which user requests they want to send for deeper testing.
There are more data sources that can help you improve your APM application performance analytics can be found in the manual."Essential Guide to Machine Data: User and Application Machine Data"