RECAP targets the automated operation and management of applications / service chains in largescale geographically distributed infrastructure. As such, RECAP components need to operate across distributed infrastructure, which makes the RECAP tooling itself a distributed application. Earlier documents introduced RECAP's initial architecture (D4.2) and described the initial prototype of the platform (D4.6). This document combines both predecessor documents and enhances them with an updated description of the RECAP architecture.
From an architectural point of view, RECAP consists of four functional building blocks (sub systems): (i) landscaping and monitoring, (ii) application and infrastructure optimization, (iii) simulation and planning, and (iv) data analytics and machine learning.
(i) The Landscaping and Monitoring sub-system is responsible for gathering information about the structure of the current infrastructure and application landscape and monitoring their state. This is the main source for both the Data Analytics and Machine Learning as well as Application and Infrastructure Optimization sub-system.
(ii) The Application and Infrastructure optimizers make decisions based on internal models as well as live information provided by the landscaping and monitoring subsystem. Separating between dedicated application and infrastructure optimizers enables the realisation of a 'separation of concerns'.
(iii) The simulation and planning sub-system provides means for supporting the validation of RECAP models, the execution of 'what-if' scenarios, and the long-term planning of the large scale infrastructures.
(iv) The data analytics and machine learning sub system provides tools and means to distil statistical properties and patterns from load traces; particular focus is thereby put on workload prediction.
With regard to integration, RECAP targets a loose coupling between the components fostering independent uptake and re-use of building blocks.
To download this deliverable, please fill in the form.