Systèmes d'exploitation et cloud
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Cours, examens, TD, TP et exercices de systèmes d'exploitation et cloud. Thèmes couverts : Linux, Unix, Windows Server, Docker, Kubernetes, virtualisation.
Le livre blanc souligne les d fis des d ploiements Cloud mal con us, souvent acc l r s par la pand mie, et propose une solution : des plateformes int gr es et extensibles. Ces plateformes am liorent la satisfaction client, la collaboration et l'efficacit op rationnelle gr ce une meilleure interop rabilit et des API flexibles. L'accent est mis sur l'importance d' liminer les silos technologiques et d'adopter des solutions modernes bas es sur des micro-services, pour accro tre la productivit et permettre aux entreprises de s'adapter aux volutions rapides du march .
This document provides an in-depth discussion of scheduling problems in single-machine environments. It introduces the objective of optimizing specific criteria (e.g., makespan minimization) under given constraints. Mathematical models and theorems like FIFO, SPT, and EDD are utilized to achieve optimal scheduling. Additionally, the document explores computational solutions using tools like CPLEX and Lekin, as well as NP-hard scenario analysis supported by heuristic approaches.
The document introduces multi-machine scheduling problems aiming to optimize chosen criteria while respecting constraints. It elaborates on parallel machine scenarios and discusses flow shop and job shop setups, detailing rules and algorithms for optimal task sequencing and allocation, including LPT, SPT, Johnson's algorithm, and heuristics like CDS. Examples illustrate these methodologies, highlighting their application and outcomes, with software tools like Lekin and Cplex mentioned for resolution practices.
The document introduces scheduling problems for single-resource systems, aiming to optimize criteria like makespan and tardiness while respecting constraints. Methodologies include modeling and solving with tools like Lekin and CPLEX, focusing on NP-hard cases. Common scheduling problems analyzed range from minimizing processing times to handling precedence constraints. Optimization theories and heuristics, such as EDD and MDD, are discussed with examples.
This document comprehensively introduces scheduling problems in various contexts, including production systems, projects, and administration. It elaborates on classification schemas, key parameters, and methodologies to optimize resource allocation while balancing constraints such as precedence and resource availability. Practical examples in fields such as aeronautics, IT, and construction are covered alongside an exploration of decision-making processes across strategic, tactical, and operational levels. Core scheduling typologies like single-machine, flow shop, and job shop are explained...
This thesis investigates process improvement for EMS (Electronic Manufacturing Service), focusing on reducing non-conformity rates using the Lean Six Sigma methodology. The DMAIC framework (Define, Measure, Analyze, Improve, Control) is applied, starting with problem identification, including high non-conformity rates and excessive cost of poor quality (COPQ). Statistical analysis such as Process Capability and Value Stream Mapping (VSM) reveals inefficiencies, such as bottlenecks in manual assembly and operator variabilities. By integrating Lean for waste reduction and Six Sigma for qualit...
This document details the application of Lean Six Sigma methodologies to improve production processes within Electronic Manufacturing Services (EMS). Core methods include Value Stream Mapping, statistical analysis, and the DMAIC workflow (Define, Measure, Analyze, Improve, Control). Key findings include the identification of inefficiencies via non-conformity analysis and process redesign, resulting in enhanced productivity and quality metrics. Implemented improvements directly impacted the satisfactory achievement of defined project objectives.
This document appears to be an exercise or assessment related to tools development under the Linux operating system. It is structured with numbered tasks, likely designed to test proficiency in Linux-based programming or tool utilization. The methodology involves step-by-step problem-solving and applies practical knowledge of system tools. The findings are aimed at reinforcing the understanding of Linux fundamentals in a development environment.
The document introduces ARIMA models as an advanced methodology for analyzing and predicting time series data. It discusses stationarity, differentiation, and seasonal trends, elaborating on key statistical methods such as the KPSS test for stationarity testing. Practical implementation in R is explained, including the Hyndman-Khandakar algorithm and the auto.arima function for optimizing models. Finally, criteria such as AIC and residual diagnostics are utilized to select the best-performing model for forecasting.
This document explores the ARIMA model, a generalization of the ARMA model used for analyzing time series data. It discusses the importance of stationarity and the process of differencing to achieve it. Various methods of differentiation and model application are illustrated, alongside statistical tests for assessing stationarity.
Stochastic processes are employed to model variables whose behaviors are inherently random and cannot be fully explained by deterministic relationships. These processes consist of random variables indexed over time, and specific cases, such as stationary processes, require that the statistical properties remain constant over time. White noise is a notable example, featuring uncorrelated random variables with a constant spectral density. Key concepts include autocovariance and autocorrelation, which measure temporal dependencies, and are essential for analyzing and representing time series d...
This document introduces ARMA (AutoRegressive Moving Average) processes and describes their key characteristics, including stationarity and invertibility conditions. Examples illustrate how to simulate ARMA processes and test their stationarity for specific parameters. The methodology compares processes based on detailed conditions for ARMA(p,q) representations and describes the limitations and failures when stationarity conditions are not met. The findings underline the importance of parameter constraints for ensuring valid ARMA models.
The document provides a step-by-step tutorial for performing basic UNIX system administration tasks. It includes practical exercises on group and user management, modifying account properties, access rights manipulation, and user deletion commands. Additionally, it emphasizes the importance of cleanup post-lab session, demonstrating effective usage of UNIX commands such as groupadd, useradd, usermod, and chmod.
This document provides a detailed analysis of parallel and distributed computing architectures. It introduces Flynn's taxonomy, classifying architectures into SISD, SIMD, MISD, and MIMD, focusing on the MIMD class and its memory-based subclasses (shared, distributed, and hybrid). Advanced systems like clusters and computational grids are explored, addressing their components and use cases in academia and industry. It also delves into large-scale distributed systems and the concept of peer-to-peer systems for efficient computation and resource sharing.
The document explains task scheduling with focus on dependency types between tasks. It identifies producer-consumer, consumer-producer, and producer-producer dependencies, using examples of variables and their sequential operations. Dependency precedence is emphasized to conform to program execution order. The methodology involves clear categorization of dependencies to streamline sequencing in computational processes.
Ce document traite de l'ordonnancement de t ches ind pendantes en milieu h t rog ne, en mettant l'accent sur l' quilibrage de charge et la minimisation du makespan. Diff rentes m thodes et algorithmes d'ordonnancement sont pr sent s, y compris les principes de choix de processeurs et des heuristiques d'am lioration. Enfin, une comparaison entre ces algorithmes est effectu e pour en valuer l'efficacit .
This document delves into the architectural models for application hosting and SaaS maturity levels. It analyzes single-tier and N-tier architectures, their use cases, advantages, and limitations, emphasizing scalability and security. The SaaS maturity model is broken into four levels, ranging from ad-hoc/custom setups to scalable, multi-tenant-efficient solutions. Detailed examples and real-world applications are presented, enhancing understanding for cloud computing architects and developers.
This document provides a detailed overview of Kubernetes, a powerful open-source container orchestration platform. It covers the essential features such as resource scheduling, self-healing, service discovery, and scalability. Methodologies include the usage of API-driven declarative configurations, YAML manifests for object specifications, and diverse worker/control plane architectures. Extensions and integrations for storage, monitoring, and automation emphasize its flexibility and utility in modern cloud environments.
Docker networking allows containers and services to interconnect and communicate seamlessly across mixed OS environments in a platform-agnostic manner. It relies on a flexible and pluggable networking subsystem powered by various drivers including bridge, host, overlay, macvlan, and none, along with third-party plugins. User-defined bridge networks enhance container communication by providing improved isolation, DNS resolution, and customizable configurations compared to the default bridge network. The document highlights best practices for leveraging these networks, explains setup steps su...
This document outlines methods for managing persisting data in Docker containers, focusing on three primary mount types: volumes, bind mounts, and tmpfs mounts. Volumes, managed by Docker, are highlighted as the preferred approach due to their portability, safety, and performance benefits, offering use cases like sharing data across containers or cloud storage. Bind mounts are depicted as less flexible but ideal for accessing host system files or developing applications. Tmpfs mounts are recommended for temporary data needs, ensuring non-persistence and enhancing container performance. Key...
This document provides a comprehensive step-by-step guide for beginners on creating and utilizing Dockerfiles to build Docker images. It begins with an introductory explanation of Docker concepts and progresses into practical instructions on defining custom Docker images tailored for specific project needs. The guide includes examples, such as modifying Alpine Linux, explores the layering mechanism for image builds, and highlights caching for improved performance. Additionally, it emphasizes the importance of understanding base technologies when crafting Dockerfiles.
This document provides a detailed overview of best practices for Docker image creation and management, emphasizing the importance of keeping images small through efficient layering, base image selection, and multistage builds. It also highlights methods for managing application data using volumes and bind mounts during development and production. Furthermore, the document underscores the use of CI/CD pipelines for testing and deployment to ensure image security and quality assurance. Finally, practical differences between development and production environments are discussed alongside recom...
This document introduces Docker Compose as a tool for defining and running multi-container Docker applications using a YAML configuration file. The example Voting App is used for demonstration, which involves multiple microservices (Voting App, Redis, Worker, PostgreSQL database, and Result App). It highlights the simplicity of deploying complex stacks with a single command and discusses how Docker Compose facilitates container networking, volume preservation, and efficient container management. Key features like environment variables, efficient container recreation, and common commands for...
This document introduces Docker Compose, a tool to handle multiple containers with ease using a YAML-based configuration file. It discusses how services, volumes, and networks can be specified and managed, highlighting configuration options and dependencies. Scaling instances, environment variables, networking, and lifecycle management are detailed alongside deploy settings for Docker Swarm. The tutorial concludes with mentions of real-world applications like Spring Cloud Data Flow and practical usage commands.