PIACERE aims to increase the productivity of DevOps teams in the development and operation of IaC through the provisioning of an integrated DevSecOps framework.
DevOps teams can program IaC as if they were programming any software application.
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PIACERE solution consists of an integrated DevSecOps framework to develop, verify, release, configure, provision, and monitor infrastructure as code.
The main characteristics of this solution are:
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PIACERE supports the different DevSecOps activities. Using a single **integrated environment to develop (IDE)** infrastructural code will unify the automation of the main DevSecOps activities and will shorten the learning curve for new DevSecOps teams.
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Thirdly, a **Component Security Inspector** that by analysing also the IaC code, reports the potential vulnerabilities and proposes potential fixes.
Fourthly, a **Canary environment** that allows unit testing of the behaviour of the infrastructural code on an isolated environment, which would enable the simulation of conditions for the production environment and identify some of the most common anti-patterns.
In the Ops part of the DevSecOps lifecycle, PIACERE also presents several key innovations: The **Optimized Platform (IOP)** presents the DevSecOps teams with the most appropriate deployment configurations that best meet their defined constraints out of their catalogue of services, resources and infrastructural elements by means of optimization algorithms. The **Execution Platform** will automatically plan, prepare, and provision the infrastructure and plan, prepare, and install the corresponding software elements needed for the application to seamlessly run. At runtime, PIACERE continuously monitors the metrics associated with the defined measurable NFRs (e.g. performance, availability, and security through the **Runtime Security Monitoring**) and be able to **self-learn**, implementing machine-learning algorithms, and realizing an incremental learning strategy by continuously analysing divergences in the decision boundaries and detecting anomalies in the metrics being collected while retaining only the most up to date data to avoid model degradation. Whenever these self-learning mechanisms detect an anomaly or a potential SLA violation, an alarm is triggered, and a self-healing mechanism launched. A **self-healing** mechanism will entail to launch again an optimization algorithm for the actual problem domain and an automatic execution platform, monitoring and so on.
## Repository structure
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@@ -38,9 +42,15 @@ The Public repository of PIACERE project is organized as follows:
Three branches **Y1**, **Y2**, **Y3** gather the versions delivered in the three main milestones of the project (at M12, M24 and M30). The **main** branch stores the final version of the components, as some development and code fixes could continue until the end of the 36-months long project.
Different tools of the PIACERE framework are employed by the user in each of these phases. The list of tools and the respective repository can be seen in the following table:
