▎Common Backend Development Terms
1. Server: A computer or system that provides data, resources, or services to other computers (clients) over a network.
2. Database: An organized collection of data that can be easily accessed, managed, and updated. Common databases include MySQL, PostgreSQL, MongoDB, and SQLite.
3. API (Application Programming Interface): A set of protocols and tools that allows different software applications to communicate with each other, often exposing endpoints for data interaction.
4. REST (Representational State Transfer): An architectural style for designing networked applications that use HTTP requests to access and manipulate data, typically in JSON or XML format.
5. GraphQL: A query language for APIs that allows clients to request only the data they need, providing a more efficient and flexible alternative to REST.
6. Middleware: Software that acts as a bridge between different applications or services, often handling requests and responses in web applications.
7. Authentication: The process of verifying the identity of a user or system, often using methods like passwords, tokens, or OAuth.
8. Authorization: The process of determining whether a user or system has permission to perform a specific action or access certain resources.
9. Session Management: The technique used to manage user sessions in web applications, allowing users to stay logged in and maintain state across multiple requests.
10. Microservices: An architectural style that structures an application as a collection of small, loosely coupled services, each responsible for a specific business function.
11. Monolithic Architecture: A traditional software architecture where all components of an application are combined into a single, unified codebase.
12. CRUD (Create, Read, Update, Delete): The four basic operations of persistent storage, representing the fundamental functions of a database.
13. ORM (Object-Relational Mapping): A programming technique used to convert data between incompatible type systems in object-oriented programming languages, allowing developers to interact with databases using objects instead of SQL queries.
14. Web Server: A server that handles HTTP requests from clients, serving web pages and resources. Examples include Apache, Nginx, and Microsoft IIS.
15. Load Balancer: A device or software that distributes network or application traffic across multiple servers to ensure reliability and performance.
16. Caching: The process of storing copies of files or data in temporary storage locations to reduce latency and improve performance in data retrieval.
17. Continuous Integration/Continuous Deployment (CI/CD): A set of practices that enable developers to automatically test and deploy code changes to production environments quickly and reliably.
18. Version Control: A system that tracks changes to code over time, allowing developers to collaborate effectively and manage different versions of their applications, commonly using tools like Git.
19. Containerization: A method of packaging an application and its dependencies into a container that can run consistently across different computing environments, often using tools like Docker.
20. Serverless Computing: A cloud computing model where the cloud provider automatically manages the infrastructure required to run applications, allowing developers to focus on writing code without worrying about server management.
1. Server: A computer or system that provides data, resources, or services to other computers (clients) over a network.
2. Database: An organized collection of data that can be easily accessed, managed, and updated. Common databases include MySQL, PostgreSQL, MongoDB, and SQLite.
3. API (Application Programming Interface): A set of protocols and tools that allows different software applications to communicate with each other, often exposing endpoints for data interaction.
4. REST (Representational State Transfer): An architectural style for designing networked applications that use HTTP requests to access and manipulate data, typically in JSON or XML format.
5. GraphQL: A query language for APIs that allows clients to request only the data they need, providing a more efficient and flexible alternative to REST.
6. Middleware: Software that acts as a bridge between different applications or services, often handling requests and responses in web applications.
7. Authentication: The process of verifying the identity of a user or system, often using methods like passwords, tokens, or OAuth.
8. Authorization: The process of determining whether a user or system has permission to perform a specific action or access certain resources.
9. Session Management: The technique used to manage user sessions in web applications, allowing users to stay logged in and maintain state across multiple requests.
10. Microservices: An architectural style that structures an application as a collection of small, loosely coupled services, each responsible for a specific business function.
11. Monolithic Architecture: A traditional software architecture where all components of an application are combined into a single, unified codebase.
12. CRUD (Create, Read, Update, Delete): The four basic operations of persistent storage, representing the fundamental functions of a database.
13. ORM (Object-Relational Mapping): A programming technique used to convert data between incompatible type systems in object-oriented programming languages, allowing developers to interact with databases using objects instead of SQL queries.
14. Web Server: A server that handles HTTP requests from clients, serving web pages and resources. Examples include Apache, Nginx, and Microsoft IIS.
15. Load Balancer: A device or software that distributes network or application traffic across multiple servers to ensure reliability and performance.
16. Caching: The process of storing copies of files or data in temporary storage locations to reduce latency and improve performance in data retrieval.
17. Continuous Integration/Continuous Deployment (CI/CD): A set of practices that enable developers to automatically test and deploy code changes to production environments quickly and reliably.
18. Version Control: A system that tracks changes to code over time, allowing developers to collaborate effectively and manage different versions of their applications, commonly using tools like Git.
19. Containerization: A method of packaging an application and its dependencies into a container that can run consistently across different computing environments, often using tools like Docker.
20. Serverless Computing: A cloud computing model where the cloud provider automatically manages the infrastructure required to run applications, allowing developers to focus on writing code without worrying about server management.
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▎Common DevOps Terms
1. CI/CD Pipeline: A set of automated processes that builds, tests, and deploys code changes from a repository to production.
2. Infrastructure as Code (IaC): Managing and provisioning infrastructure (servers, networks, databases) through machine-readable definition files (code) rather than physical hardware configuration.
3. Configuration Management: The process of maintaining consistency and control over software application configurations and their environments. Tools include Ansible, Chef, Puppet.
4. Containerization: Packaging an application and its dependencies into a self-contained unit (container) that can run reliably across different environments. Docker is the most common tool.
5. Container Orchestration: Automating the deployment, scaling, and management of containerized applications. Kubernetes is the industry standard.
6. Cloud Computing: On-demand delivery of IT resources over the internet with pay-as-you-go pricing. Major providers: AWS, Azure, GCP.
7. Virtual Machine (VM): An emulation of a computer system, allowing you to run an operating system and applications on top of another operating system.
8. API Gateway: A server that acts as a single entry point for all client requests to backend microservices, simplifying client interactions and providing security, monitoring, and traffic management.
9. Service Mesh: A dedicated infrastructure layer for making service-to-service communication safe, fast, and reliable, often used in microservices architectures. Examples: Istio, Linkerd.
10. Monitoring: The process of collecting, analyzing, and acting on data about system performance and health. Tools include Prometheus, Grafana, ELK Stack.
11. Logging: The process of recording events that occur within an application or system, crucial for debugging and auditing.
12. Alerting: The system that notifies the operations team when a critical event or threshold breach is detected in the monitoring system.
13. Scalability: The ability of a system to handle an increasing amount of work by adding resources. Horizontal (adding more servers) vs. Vertical (adding more power to existing servers).
14. Availability: The percentage of time a system is operational and accessible. Often measured in "nines" (e.g., 99.99% uptime).
15. Fault Tolerance: The ability of a system to continue operating, perhaps at a reduced level, rather than failing completely when some part of the system fails.
16. Disaster Recovery (DR): A plan and set of procedures to recover and protect a business IT infrastructure in the event of a disaster.
17. GitOps: An operational framework that codifies infrastructure and application configuration management in Git repositories, using Git as the single source of truth.
18. Testing (Unit, Integration, End-to-End): Different levels of automated testing to ensure code quality and functionality before deployment.
19. Release Engineering: The practice of managing and automating the software release process to ensure it is efficient, reliable, and repeatable.
20. Observability: The ability to understand the internal state of a system by examining its outputs (logs, metrics, traces). More comprehensive than just monitoring.
1. CI/CD Pipeline: A set of automated processes that builds, tests, and deploys code changes from a repository to production.
2. Infrastructure as Code (IaC): Managing and provisioning infrastructure (servers, networks, databases) through machine-readable definition files (code) rather than physical hardware configuration.
3. Configuration Management: The process of maintaining consistency and control over software application configurations and their environments. Tools include Ansible, Chef, Puppet.
4. Containerization: Packaging an application and its dependencies into a self-contained unit (container) that can run reliably across different environments. Docker is the most common tool.
5. Container Orchestration: Automating the deployment, scaling, and management of containerized applications. Kubernetes is the industry standard.
6. Cloud Computing: On-demand delivery of IT resources over the internet with pay-as-you-go pricing. Major providers: AWS, Azure, GCP.
7. Virtual Machine (VM): An emulation of a computer system, allowing you to run an operating system and applications on top of another operating system.
8. API Gateway: A server that acts as a single entry point for all client requests to backend microservices, simplifying client interactions and providing security, monitoring, and traffic management.
9. Service Mesh: A dedicated infrastructure layer for making service-to-service communication safe, fast, and reliable, often used in microservices architectures. Examples: Istio, Linkerd.
10. Monitoring: The process of collecting, analyzing, and acting on data about system performance and health. Tools include Prometheus, Grafana, ELK Stack.
11. Logging: The process of recording events that occur within an application or system, crucial for debugging and auditing.
12. Alerting: The system that notifies the operations team when a critical event or threshold breach is detected in the monitoring system.
13. Scalability: The ability of a system to handle an increasing amount of work by adding resources. Horizontal (adding more servers) vs. Vertical (adding more power to existing servers).
14. Availability: The percentage of time a system is operational and accessible. Often measured in "nines" (e.g., 99.99% uptime).
15. Fault Tolerance: The ability of a system to continue operating, perhaps at a reduced level, rather than failing completely when some part of the system fails.
16. Disaster Recovery (DR): A plan and set of procedures to recover and protect a business IT infrastructure in the event of a disaster.
17. GitOps: An operational framework that codifies infrastructure and application configuration management in Git repositories, using Git as the single source of truth.
18. Testing (Unit, Integration, End-to-End): Different levels of automated testing to ensure code quality and functionality before deployment.
19. Release Engineering: The practice of managing and automating the software release process to ensure it is efficient, reliable, and repeatable.
20. Observability: The ability to understand the internal state of a system by examining its outputs (logs, metrics, traces). More comprehensive than just monitoring.
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Forwarded from Free Programming Books
📘Laravel Handbook
✍️ Author: Flavio Copes
Read Online
#Laravel
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✍️ Author: Flavio Copes
Read Online
#Laravel
────────────────────
👉 @free_programming_books_bds 👈
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Forwarded from Programming Quiz Channel
Which situation most strongly suggests a need for refactoring?
Anonymous Quiz
4%
The code has documentation
15%
The project uses Git
67%
The code is difficult to modify safely
15%
The application has multiple users