6.1. SteelScript Application Framework

Welcome to the documentation for the SteelScript Application Framework!

This project makes it easy to:

  • Build a web front end to your metrics
  • Pull metrics from a variety of data sources:
    • NetProfiler
    • NetShark
    • Wireshark
    • Sharepoint
    • Solarwinds
  • Add new data sources with minimal code
  • Design custom reports
    • mix and match widgets and data
    • define custom criteria
  • Custom analysis via Python hooks and Python Pandas
    • compute statistics, pivot tables, merge, sort, resample timeseries
  • Plugin architecture makes it easy to share modules

6.1.1. Overview

The SteelScript Application Framework is a Django application that provides a web front end to metrics collected from available datasources. A primary goal is to focus on extensibilty and modularity:

  • Data is normalized to Python Pandas DataFrames
  • Data sources need not worry about how the data is visualized
  • Visualization modules are independent of data source
../_images/appfwk-arch.png

Getting an application up and running involves the following steps:

  1. Installation
  2. Database configuration
  3. Define a set of devices to query
  4. Define one or more reports in Python:
    1. Define the criteria a user must provide for the report
    2. Define data tables and assign columns of keys and values to report on
    3. Connect data tables to UI widgets for rendering

For more advanced use cases, the output of one or more tables can be fed as input to analysis tables hooked to a Python callback. This allows data to be processed in virtually any conceiveable way. The output of the analysis table is just another table. This can then be connected to one or more widgets for visualization, or in turn be inputs to yet another analysis table for further processing.

6.1.2. Documentation

  • Python Pandas
  • Tutorials
    • Creating a Report
    • Writing an AnalysisTable
    • Wave Plugin Tutorial

SteelScript Application Framework

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