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AppDynamics provides a rich source of information about your monitored applications, including the performance of individual business activities, dependency flow between application components, and details on every business transaction in an instrumented environment.
AppDynamics APM provides a rich toolkit for turning the vast corpus of data captured by AppDynamics into valuable insights.
AppDynamics DEXTER (Data Extraction and Enhanced Reporting) can make this process even faster and simpler. DEXTER provides new ways to unlock the data stored in the AppDynamics platform. You can analyze this information in a number of data warehousing and visualization applications, and combine it with your own data to generate customized reports.
If you’re familiar with data warehousing terminology, think of DEXTER as an extract/transform/load (ETL) utility for AppDynamics data. It extracts information from the AppDynamics platform, transforms it into an enriched, query-able form for faster access, and loads it into variety of reports for:
By extracting the data from AppDynamics, converting it into queryable format and storing it locally, the data can be preserved with full fidelity indefinitely and interrogated in new and novel ways.
Here are some scenarios that are possible with data provided by AppDynamics DEXTER:
The 3 part Walkthrough gives an overview and screenshots of the tool in action.
"Entity Timeline View" is part of Entity Details report that is generated for Application and all of its Tiers, Nodes, Business Transactions, Backends, Service Endpoints and Errors. It provides a single-pane view into many things, including:
If you ever were presented with a large Controller (or several) full of unknown number of Applications, Tiers and Nodes, you will like the detail provided by Detected Entities report.
Entity Metrics report shows summary and graphs for all Metrics for each and every detected Application, Tier, Node, Business Transaction, Backend, Service Endpoint, Errors and Information Point. This makes it very valuable in times when you want to rapidly assess hundreds of Applications, Tiers and Business Transactions and see which ones need your attention.
A scatterplot of Calls per Minute vs Average Response time is provided for all types of Entities, allowing you to see what items are both slow and frequently called:Per minute breakdown with ART vs CPM scatter:
All Nodes JVM GC metrics
Have you ever wanted to find a snapshot that calls a specific Tier, Backend or Application?
How about the one that uses specific SQL query?
And how about the one that has a real Call Graph?
Or maybe also a special Data Collectors?
Or how about finding out how many times that special Query was slow in a given time range?
Or discover which classes and methods are called in which Snapshots?
How about all of the above, combined?
In Snapshots report you can do all of that, and more. Snapshot Exit Calls broken by time and duration:Snapshots with multiple Segments have an enhanced Waterfall view, with “^” caret character indicating exactly when in the Segment execution the Exit Calls occurred
Using Flame Graphs and Flame Chart reports, is an ingenious and useful way to visualize many call graphs in single screen. Sum of all calls in Application for entire time rangeSum of all calls in Application with Time grouping /
Configuration report provides information about Controller Settings and Application configuration. Here is an example showing non-default Agent Properties set on multiple Applications in multiple Controllers
If you are new to AppDynamics DEXTER and want an introduction, read through 3 part Walkthrough.
Learn how the tool works by reading Documentation in the project wiki.
Install Application, create Job File to specify what to do, and Run Application.
You will see the results in the Output folder.
To understand what you are looking at, read Description of Excel Reports.
If you need help with issues and/or intepretation of results, read Getting Support.
AppDynamics DEXTER is hosted on AppDynamics GitHub area.
Download latest release from Releases section or from attachments to this article.