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SURVOL





Survol is Primhill Computer's Software Intelligence tool to analyse and investigate information systems.

With time, software development and maintenance increase in complexity. Existing systems and new technologies compete with each other at fast rate, creating an instable multi-dimensional environment, which challenges systems' continuity and evolution.

For development teams, understanding the existing IT environment is a critical need. Among analysis techniques, the most reliable is the automatic collection of information on running systems, based on industrial standards.

Survol creates intelligence in complex architecture by identifying the conceptual and engineering objects hidden in critical applications, across different languages and frameworks, when they run. It provides IT leaders and engineers with semantic analysis and insight in existing or legacy information systems.

Survol is a Python agent and a web interface aiming to help understand an existing information system, perhaps legacy applications. 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.

WHO IS IT MADE FOR?

Survol is designed for two classes of users:
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.

WHAT DOES IT DO?

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 facet of an information system.

These scripts are run by Survol agents, these agents running on one or several machines of the user application network. The web interface then displays and aggregates  the heterogeneous information coming from the agents. It is not necessary to have an agent on all machines because many scripts can get information from different machines than their own. 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... Heterogeneous data are modelled into a single dramework, then aggregated with an RDF inference engine, creating a global vision of the business information processing. 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 grasp 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.



Here, this displays the shared memory segments and the processes mapping them. Everything can be combined in graphic reports, everyone can understand. The data model borrows extensively its ontology and terminology from Common Information Model, 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:
Survol, is an open-source project: Everyone can freely download and use it. 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.

CAN I TRY?

Survol is installed on these machines, in different configurations:
Here, you will find some use cases.

HOW MUCH DOES IT COST?

Survol is free and open-source, and will stay so. But users might invest into its installation, consulting, training. Or possibly into proprietary development of specific scripts, adapted to their own needs.

QUESTIONS?

See the FAQs, the architecture, installation notes, use cases, or Doxygen-generated pages here.

Please contact us for any question.