Survol is a Python agent and a web interface aiming to help the analysis and investigation of a legacy application.
A set of machines, processes, databases, programs etc ...
all communicating with each other, manipulating your data,
and whose software architecture has become, with time, complicated, difficult to understand, and undocumented.

Survol is designed for two classes of users:

* Managers in charge of software projects, who must to follow development tasks, infrastructure evolutions,
by looking directly into what's being developed.
They need a non-technical tool, to extract information from a running application at a synthetic level.
* Consultants, newly-comers on legacy software, who must be grasp quickly an existing information system,
using many, too many technologies.

These users have something in common: They must quickly grasp a large software architecture, maybe constantly changing:
With its visual interfaces, _Survol is also a team-building tool_, bringing clarity, helping to give the same names to the same things.

Survol allows to display any software entity or resources running on a computer.
Simply said, it is a library of Python scripts, each of them displaying a particular facet of an information system.

These scripts are run on Survol agents, these agents running on one or several machines of the user application network.
The web interface then displays and summarizes all the information coming from the agents.
It is not necessary to have an agent on all machines because many scripts can get information
from other machines than the one they are running on. Strictly said, it is possible to run without an agent at all,
just with a static Javascript page which connects to the target machines.
The agents are very lightweight and can also run on an **Internet of Things** (IoT) network.

The data model of Survol is based on classes, each of them defining a type of computer resources: Processes, machines, files etc...
It can display for example the tree of processes and subprocesses or a directory and its subdirectories: Each file is displayed with some basic properties.
One can click on each box to get further information, as no keyboard is needed. No special technical skills are needed to use Survol.
The general details one can graps about the various interaction between components of an information system, greatly help its understanding:
Links between machines, processes, databases and any other components are visible. Useful dependencies are extracted without documentation.

Survol fully respects the security policy of the network it is running on:
If the agent runs on a privileged account, it will extract many information.
But even with a dummy account, it will still be able to retrieve useful data about the analysed system.
Survol does not ever modify or change anything on the machines it is running on, so it is very safe.

Everything can be combined in graphic reports, everyone can understand.
The data model borrows extensively its ontology and terminology from **Common Information Model** (CIM), an existing industrial standard.
Therefore, it interacts freely with CIM implementations such as **Microsoft WMI**, **OpenLMI**, **OpenPegasus** and **WBEM**, and any other software based on this standard.

It is very easy to add new scripts, to display a specific kind of information, only your application defines.
When resources types are not defined by CIM, Survol adds its own resource classes, in a very simply way.
If a user application defines its resources classes, it is very easy to add ones, along with associated scripts,
in open or proprietary source code, without complicated setup. Just create a directory and add a new script at the right place, that's it.

The internal data model built by Survol agents, is a set of triples: Subject, relation, object,
homogeneous to **Resource Description Framework** (RDF), the core data type found in the Semantic web,
a standard which provides a framework allowing data to be shared and reused across applications.
RDF, especially appropriate for Artificial Intelligence applications, is an abstract model for Survol data,
which are extracted from heterogenous sources information system. Survol displays these data in several modes:

* Interactive mode, fully interactive, designed for investigating, browsing, drilling into applications internals.
It uses **D3**, a nice JavaScript library for manipulating graphs.
* A print mode, where the rendered view cannot be modified but is designed to be nicely printed for reporting or presentations.
The appearance is similar to the interactive one, but the layout does not depend on User interaction.
It uses Graphviz, an open source graph visualization software.
* The plain HTML mode, convenient to generate reports in plain text, reports which can be saved, and compared.

Survol can have add-ons: It is very easy to customize Survol by adding new scripts and classes:
One just need to add Python scripts at the right place:
Their returned information can now fully integrate with the rest of Survol model.
Survol fully uses Python documentation features to expose your add-on and its integrated documentation.

[See Survol page on Primhill Computers web site.](http://primhillcomputers.com/survol.htm)
