Operating Systems and Virtualization Concepts

Operating Systems

• Definition: Software that manages hardware resources and services for computer programs.
• Functions: Memory management, process scheduling, and input/output handling.
• Types: Single-user, multi-user, real-time, and distributed.

Containerization

• Containers: Lightweight, portable units packaging applications and dependencies for consistent environments.
• Container Runtime: Software for executing and managing containers (e.g., Docker).
• Images: Read-only templates containing application code and dependencies.

Virtualization

• Hypervisor: A layer enabling multiple virtual machines (VMs) on a single physical machine, managing VMs and allocating resources.
• Virtual Machines: Emulated computers running operating systems and applications as if they were physical machines.

Distributed Systems

• Definition: Components on networked computers communicating and coordinating through messages.
• Key Concepts: Scalability, reliability, and resource management are critical for performance.
• Microservices: An architectural style structuring applications as loosely coupled services.

Infrastructure

• Definition: Underlying physical and virtual resources supporting applications (servers, storage, networking).
• Management: Overseeing deployment, scaling, and maintenance of infrastructure components.

Automation and Scripting

• Importance: Automation tools and scripting languages optimize processes, manage configurations, and deploy applications effectively.

Networking

• Protocols: Rules governing data communication essential for distributed systems and cloud computing.
• Explanation of Difficult Terms:
  • Containerization: Allows applications to run in isolated but share same OS kernel
  • Hypervisor: Software creating and running virtual machines
  • Orchestration: Automated arrangement, coordination and management of complex systems.
  • Scalability: System's capacity for growth, crucial for distributed systems
  • Microservices: Architectural component structured into small, autonomous services.
  • CLI: Text-based command line interface for instructions
  • Docker: Platform to automate deployment of applications within containers
  • Asciinema: Record terminal sessions as text-based videos

TCP/IP Model

• Framework for network communication; consisting of five layers: Application, Transport, Network, Data Link, and Physical. Each layer has specific functions and protocols.

Protocols (detailed)

• Application Layer: Protocols like HTTP, FTP & DNS facilitate user interactions with the network
• Transport Layer: Protocols like TCP (Transmission Control Protocol) and UDP (User Datagram Protocol) for data flow control and error correction are utilized.
• Network Layer: Manages IP addressing and routing packets across networks. It is responsible for determining the best path for data to travel.
• Data Link Layer: Responsible for node-to-node data transfer, error correction, and managing MAC addresses.
• Physical Layer: Deals with transmission of raw data over various media including cables and signals, involving hardware technologies.

Networking Models

• OSI Model: Seven layers.
• TCP/IP Model: Four layers (Application, Transport, Internet, and Network Access). Models crucial for understanding data flow.

Routers

• Networking devices connecting networks and managing traffic between them.
• Routing table helps in determining best paths for data packets.

Low-Layer Protocols

• Protocols like Ethernet and Wi-Fi, operating at physical and data-link layers. Responsible for data transmission, framing, and error detection.

Address Resolution Protocol (ARP)

• Maps IP addresses to MAC addresses, enabling communication between devices on local networks.

Domain Name System (DNS)

• Translates human-readable domain names (like sdu.dk) into IP addresses.

HyperText Transfer Protocol (HTTP)

• Client-server protocol used for transferring web pages.

Multicast

• Data transmission from one sender to multiple specific receivers.

Routing Protocols

• Protocols like RIP (Routing Information Protocol) and OSPF (Open Shortest Path First) for determining optimal paths for data.

Autonomous Systems (AS)

• Large networks or groups of networks under single administrative control. Essential for controlling routing policies and IP address space.
• Examples: ISPs, technology companies.

Interoperability and Communication

• Importance of interoperability between diverse systems and protocols for seamless communication.

Distributed Systems (detailed)

• Core concepts like fault tolerance, data consistency and scalability are essential for distributed system operation.

Apache Kafka

• Distributed event streaming platform for high-throughput, fault-tolerant data processing.
• Widely used for building real-time data pipelines and streaming applications.

Kubernetes

• Container orchestration platform for automating deployment, scaling, and management of containerized applications.
• Provides a robust framework for microservices and distributed systems.

12 Factor Application

• Codebase: Application should use version control for code changes to ensure consistent builds and deployments.
• Dependencies: Declared explicitly for deployments so builds and runs are the same in every environment.
• Configuration: Stored separately from application code. Configuration variables are set externally to adapt across different environments.
• Backing Services: Each service functions as an external resource to the application. For example, a database is treated as a service and not part of the application itself.
• Build, Release, Run: The application is built, tested, and released using automated builds, releases, and deployments.
• Processes: Run as one or more completely independent processes in order to scale easily and robustly.
• Port Binding: Services are exposed via ports; allowing the application to respond to outside requests and be managed.
• Concurrency: Application code should be written to scale and support concurrent operation.

File Systems

• Types: NTFS, FAT32, EXT4, APFS. Distinction between physical, virtual and logical file systems.
• Data Management: Inodes, metadata, fragmentation.

Cache and Storage

• Cache: Smaller, faster volatile memory storing frequently accessed data. Key in improving memory access speeds.
• Storage: primary and secondary storage (RAM, hard drives, SSDs).

Security

• Key Concepts: Confidentiality, Integrity, and Availability (CIA).
• Tactics: Detect attacks and intrusion.

Performance

• Key Concepts: Efficiency, response time, and resource utilization.
• Tactics: Limit resource demand, limit event response and manage resources.

Energy Efficiency

• Key Concepts: Reducing energy consumption and operational costs.
• Tactics: Monitor resources, implement metering, and optimize resource allocation

Modifiability

• Key Concepts: Changing a system to implement new features efficiently.
• Tactics: increase cohesion, reduce coupling, and enhance modularity.

Test your understanding of critical concepts related to operating systems, virtualization, and distributed systems. This quiz covers the primary functions of operating systems, the characteristics of containers, the role of hypervisors, and the significance of automation tools. Challenge yourself and see how well you know these foundational topics in computer science!