Our expertises,

Our technological axes, our Labs

Our vision

OUR QUALITY OF SERVICE REQUIREMENTS

Our vision of good practices in Architecture and Design is essentially to control the quality of service. This quality of service of your applications meets two types of requirements:

a) Quality of service requirements such as availability, performance, reliability, security or capacity.

b) System quality requirements such as maintainability and scalability, usability, or robustness.

This is why we have developed a requirements model common to critical applications. This model allows a detailed and targeted analysis of each of these requirements.

This original approach is summarized in a CEN Workshop Agreement (CWA) entitled “Best Practices for the Design and Development of Critical Information Systems”, resulting from a European working group set up at the initiative of PROLOGISM under the auspices of CEN.(*) and with the assistance of AFNOR. Like any normative document, it results from a broad consensus.

(*) CEN : European Committee for Standardization, Comité Européen de Normalisation, Europäisches Komitee für Normung

“Best Practices for the Design and Development of Critical Information Systems”

FROM DATA TO BIG DATA

Our desire to design and build state-of-the-art systems leads us to focus particularly on data and its measurement. Thus, we have acquired a solid experience in the field of “Data Engineering” in two main types of context:

a) Strategic applications centered on databases with very high volumes and subject to drastic performance constraints.

b) High value-added monitoring and application metrology systems based on massive collection and storage systems for logs and events.

In some cases, we have reached the limits of traditional technologies that are no longer able to respond effectively to new demands of the business lines or IT.

We therefore naturally turned to Big Data technologies to make them a strategic axis of development, always with the ambition of controlling data and the quality of service of the components that use them.

We are proactive in this area, with a view to consolidating our know-how, cementing our reputation and increasing our ability to meet demand:

a) Recruitment of expert engineers & PhD students

b) Training & Certification of our experts

c) Development of a network of partners

d) Cross-fertilization (Organizing an exchange of feedback between our clients)

Big Data:“How to manage semi-structured data”, IT-Expert, Dec. (in French) 2016

TOWARDS A DEVOPS APPROACH

Our desire to monitor and control the quality of service of applications has naturally led us to focus on the industrialization of deployments in particular and good practice DevOps in general.

While in general the term DevOps represents a grouping and an inventory of good practices identified a long time ago, it also defines in our opinion an approach or even a state of mind.

This approach has two main objectives:

a) Reduce Time To Market

b) Improve the QoS of applications

On the first point, this approach follows the Agile (Scrum, Kanban, etc.) and Lean approaches which aim at eliminating long cycles, and favoring efficiency and value. These agile approaches all call for the bringing together of the different teams involved:

a) Build and Run through DevOps

b) Business through BizDevOps promoting a “product” approach to the project

c) Security through the DevSecOps including security requirements in the practices to be put in place

On the second point, this approach meets our primary concern: address the requirements of performance, robustness, usability, security, scalability that contribute to the quality of service of applications in production.

We support our clients in this process by paying particular attention to their identity,and their human, technical and organizational specificities.

Two Labs,

industrialized platforms based on

Virtualization and Cloud technologies (Amazon EC2, S3, EMR)

for

Training our consultants on the use cases encountered by our clients, implementing and continuously testing the new software stacks, identifying les patterns and anti-patterns, performing internal R&D demystifying and proving by example our principles and concepts, providing our clients and our prospects with live demonstrations..

Data Lab, industrialized Big Data R&D platform

Containerization, R&D prototyping,

SQL ++ extension projects for HQL,

MapReduce & Spark client use cases.

DevOps Lab, cloud-based industrialization platform

Provisioning, Continuous Integration, Continuous Deployment,

Software Quality, Configuration Management,

Performance tests, Monitoring