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\documentclass[a4paper]{jpconf}
\usepackage{graphicx}
\begin{document}
\title{Cloud@CNAF Management and Evolution: placeholder}
\author{C. Duma$^1$, A. Costantini$^1$, D. Michelotto$^1$ and D. Salomoni$^1$}
\address{$^1$INFN Division CNAF, Bologna, Italy}
%\address{$^2$IFCA, Consejo Superior de Investigaciones Cientificas-CSIC, Santander, Spain}
\ead{ds@cnaf.infn.it}
\begin{abstract}
Cloud@CNAF is a project aiming to offer a production quality Cloud Infrastructure, based on open source solutions to serve the different CNAF use cases.
The project is the resultof the collaboration of a transverse group of people from all CNAF departments: network, storage, farming, national services, distributed systems.
If 2016 was for the Cloud@CNAF IaaS (Infrastructure as a Service) based on OpenStack [1], a period of consolidation and
improvement, 2017 was the year of the flood, when an aqueduct pipe located inthe street nearby CNAF, went broke causing the down of the entire datacenter.
This paper presents the activity carried out throughout the year in the migration
from the point of view of stabilityand reliability, in which the activities were focused on the support of the operation of theinfrastructure, definition of monitoring
checks, dashboards and notifications, integration in thegeneral CNAF provisioning and monitoring system. During this period the number of supportedusers and uses cases has increased,
and as a consequence, the infrastructure saw a grouth ofthe resources allocated. Work on the preparation of a parallel cloud infrastructure also started,infrastructure dedicated to the
testing of OpenStack upgrade procedures, usually a complex anddifficult task. This paper presents the activity carried out throughout the year in the directionsmentioned and gives also a
vision on the future evolution foreseen for the cloud infrastructureat CNAF.
The main goal of Cloud@CNAF project is to provide a production quality
Cloud Infrastructure for CNAF internal activities as well as national and
international projects hosted at CNAF:
\begin{itemize}
\item Internal activities
\begin{itemize}
\item Provisioning VM for CNAF departments and staff members
\item Provisioning of VM for CNAF staff members
\item Tutorial and courses
\end{itemize}
\item National and international projects
\begin{itemize}
\item Providing VMs for experiments hosted at CNAF, like CMS, ATLAS, EEE
\item testbeds for testing the services developed by projects like the OpenCityPlatform \& INDIGO-DataCloud
\end{itemize}
\end{itemize}
The infrastructure made available is based on OpenStack, version Juno, with all the
services deployed using a High-Availability (HA) setup or in a
clustered manner (for ex. for the DBs used). During 2016 the infrastructure has been
enhanced, by adding new resources, compute and network, and its operation has been improved and guaranteed by
adding the monitoring part, improving the support, automating the maintenance activities.
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\label{sec:release}
TOCHANGE
The software development lifecycle (SDL) process (Figure~\ref{fig:1}) in INDIGO has been supported by a continuous
software improvement process that regarded the software quality assurance, software maintenance,
including release management, support services, and the management of pilot infrastructures
needed for software integration and acceptance testing.
%\begin{figure}
% \centering
% \includegraphics[width=\textwidth]{Figure5.pdf}
% \caption{Software development lifecycle implementation}
% \label{fig:1}
%\end{figure}
Preview releases are made available for evaluation by user communities and
resource providers through the pilot infrastructures. Release
candidates are subjected to integration testing, which may include the
%\subsection{Software development lifecycle management}
Software lifecycle management is performed mostly via automated actions orchestrated.
In Figure we depict the project's software lifecycle management services and
activities and their interdependencies:
\begin{itemize}
\item Version Control System (VCS) - Source Code is made available through public VCS
repositories, hosted externally in GitHub repositories, guaranteeing in this
way the software openness and visibility, simplifying the exploitation beyond the
project lifetime. The INDIGO-DataCloud software is released under the Apache 2.0
software license and can be deployed on both public and private Cloud infrastructures.
\item Software quality assurence criteria and control activities and services to enable them:
\begin{itemize}
\item Continuous Integration service using {\bf Jenkins}: Service to automate the building,
packaging (where applicable) and execution of unit and functional tests of software components.
\item Code review service using GitHub: Code review of software source code is one integral part of the SQA\@. This service facilitates the code review proces. It records the
comments and allows the reviewer to verify the software modification.
\item Code metrics services using {\bf Grimoire}: To collect and visualize several metrics about the software components.
\end{itemize}
\item Software release and maintenance activities, services and supporting infrastructures
\begin{itemize}
\item A project management service using {\bf openproject.org} is made available by the
project: It provides tools such as an issue tracker, wiki, a placeholder for documents and a project management timeline.
\item Artifacts repositories for RPM and Debian packages, and Docker Hub for containers:
In INDIGO-DataCloud there are two types of artifacts, packaged software and virtual images.
The software can be downloaded from our public repository\footnote{http://repo.indigo-datacloud.eu}.
\item Release notes, installation and configuration guides, user and development manuals are made
available on {\bf GitBook}\footnote{https://indigo-dc.gitbooks.io/indigo-datacloud-releases}.
\item Bug trackers using GitHub issues tracker: Services to track issues and bugs of INDIGO-DataCloud software components.
\item Integration infrastructure: this infrastructure is composed of computing resources to support directly
the Continuous Integration service. It's the place where building and packaging of software
occurs as well as the execution of unit and functional tests. These resources are provided by INDIGO partners.
\item Testing infrastructure: this infrastructure aims to provide several types of environment. A stable environment
for users where they can preview the software and services developed by INDIGO-DataCloud, prior to its public release.
\item Preview infrastructure: where the released artifacts are deployed and made available for testing and validation by the use-cases.
\end{itemize}
\end{itemize}
The first INDIGO-DataCloud major release (codename {\tt MidnightBlue}) was released 1st of August 2016 (see table~\ref{tab:1} for the fact sheet). The
second INDIGO-DataCloud major release (codename {\tt ElectricIndigo}) was made publicly available on April 14th 2017 (see table~\ref{tab:2} for the fact sheet).
\section{DevOps approach in INDIGO}
Progressive levels of automation were adopted throughout the different phases of
the INDIGO-DataCloud project software development and delivery processes.
\subsection{Services for continuous integration and SQA}
The INDIGO-DataCloud CI process is schematically shown
in Figure~\ref{fig:3}. The process, in its different steps, reflects some of
the main and important achievements of the software integration team, such as:
\begin{itemize}
\item New features are developed independently from the
production version in \textit{feature branches}. The creation of
a pull request for a specific feature branch marks the start of
the automated validation process through the execution of the
SQA jobs.
\item The SQA jobs perform the code style verification and calculate unit
and functional test coverage.
\begin{itemize}
\item The tools necessary for tackling these tests are packaged in
Docker images, available in DockerHub.
\item Each test then initiates a new container that provides a
clean environment for its execution.
\item This is an innovative approach that provides the flexibility
needed to cope with the INDIGO-DataCloud software diversity.
\end{itemize}
\item The results of the several SQA jobs are made available in the Jenkins
service which notifies back to GitHub their exit status.
\begin{itemize}
\item Only if the tests have succeeded, the source code is
validated and is ready to be merged into the production branch.
\end{itemize}
\item The last step in the workflow is the code review, where a human
review of the change is performed. After code review the source code
can be merged and becomes ready for integration and later release.
\end{itemize}
As a general rule, the described CI process must be followed by all the PTs
contributing code to INDIGO-DataCloud. However there are exceptions to this rule that fall into two main categories:
\subsection{Continuous delivery}
Continuous delivery adds, on top of the software development chain, a seamless
manufacturing of software packages ready to be deployed into production
services. Therefore, fast, frequent and small releases can be taken over thus
promoting the reliability of the software.
\subsection{DevOps adoption from user communities}
The experience gathered throughout the project with regards to the adoption of different DevOps
practices is not only useful and suitable for the software related to the core services in the
INDIGO-DataCloud solution, but also applicable to the development and distribution of the applications coming from the user communities.
\section{Conclusions}
Thanks to the new common solutions developed by the INDIGO project, teams of first-line
researchers in Europe are using public and private Cloud resources to get new results in Physics, Biology, Astronomy, Medicine, Humanities and other disciplines.
%\section*{Acknowledgments}
%eXtreme-DataCloud has been funded by the European Commision H2020 research and innovation program under grant agreement RIA XXXXXXX.
\end{document}