𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗲𝗱 𝗧𝗲𝘀𝘁𝗶𝗻𝗴:
- Selenium: Great for testing web applications.
- Appium: Focuses on testing mobile applications for iOS and Android.
- Katalon: User-friendly tool for testing web, mobile, and API applications.
- JMeter: Used for performance and load testing of applications.
𝗖𝗼𝗻𝘁𝗮𝗶𝗻𝗲𝗿 𝗢𝗿𝗰𝗵𝗲𝘀𝘁𝗿𝗮𝘁𝗶𝗼𝗻:
- Kubernetes: Manages containerized applications efficiently.
- Docker Swarm: Simple tool for smaller teams using Docker containers.
- Openshift: Red Hat's solution for container orchestration.
- Apache Mesos: Efficiently orchestrates and manages containers.
𝗠𝗼𝗻𝗶𝘁𝗼𝗿𝗶𝗻𝗴:
- Kibana: Visualizes and analyzes logs in real-time.
- Nagios: Open-source system for monitoring IT infrastructure.
- Prometheus: Monitors metrics and alerts for dynamic environments.
- Splunk: Analyzes and monitors machine-generated data.
𝗣𝗹𝗮𝗻𝗻𝗶𝗻𝗴:
- Jira: Popular for project management and agile development.
- Slack: Real-time messaging platform for team collaboration.
- Confluence: Atlassian's tool for creating, sharing, and collaborating on documents.
𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗶𝗻𝗴:
- Python: Versatile language for automation, scripting, and web development.
- Go: Efficient compiled language for scalable systems.
- Groovy: Dynamic language for scripting in Jenkins pipelines.
- Bash: Shell scripting language for automating tasks in Unix environments.
𝗖𝗼𝗻𝘁𝗮𝗶𝗻𝗲𝗿𝘀:
- Docker: Revolutionized application packaging and deployment.
- buildAH: Builds container images without a Docker daemon.
- Podman: Daemonless alternative to Docker for managing containers.
- Kaniko: Builds container images inside containers securely.
𝗜𝗔𝗖 & 𝗜𝗣 (𝗜𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 𝗮𝘀 𝗖𝗼𝗱𝗲 𝗮𝗻𝗱 𝗜𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 𝗣𝗿𝗼𝘃𝗶𝘀𝗶𝗼𝗻𝗶𝗻𝗴):
- Ansible: Automates configuration management and task automation.
- Puppet: Manages infrastructure configuration for consistency and compliance.
- Terraform: IAC tool supporting various cloud providers and on-premises environments.
𝗦𝗼𝘂𝗿𝗰𝗲 𝗖𝗼𝗻𝘁𝗿𝗼𝗹 & 𝗖𝗼𝗹𝗹𝗮𝗯𝗼𝗿𝗮𝘁𝗶𝘃𝗲 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁:
- Gitlab: Integrated platform for source code management and collaboration.
- Git: Distributed version control system for tracking changes and collaboration.
- BitBucket: Atlassian's Git repository management solution.
𝗖𝗹𝗼𝘂𝗱 𝗣𝗹𝗮𝘁𝗳𝗼𝗿𝗺𝘀:
- Google Cloud: Provides scalable infrastructure and various cloud services.
- AWS (Amazon Web Services): Leading cloud service provider with a wide range of services.
- Azure: Microsoft's cloud platform offering comprehensive services.
- Oracle Cloud: Complete suite of cloud services for enterprises adopting DevOps.
𝗕𝗮𝘀𝗶𝗰𝘀:
𝟭. 𝗦𝘆𝗻𝘁𝗮𝘅 𝗮𝗻𝗱 𝗩𝗮𝗿𝗶𝗮𝗯𝗹𝗲𝘀:
- Master Python's basic syntax and variable handling.
𝟮. 𝗗𝗮𝘁𝗮 𝗧𝘆𝗽𝗲𝘀 𝗮𝗻𝗱 𝗖𝗼𝗻𝗱𝗶𝘁𝗶𝗼𝗻𝘀:
- Explore data types, type conversion, and conditional statements.
𝟯. 𝗟𝗼𝗼𝗽𝘀 𝗮𝗻𝗱 𝗘𝘅𝗰𝗲𝗽𝘁𝗶𝗼𝗻𝘀:
- Efficiently use 'for' and 'while' loops, and handle exceptions.
𝟰. 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝘀:
- Grasp the concept of functions for modular coding.
𝗗𝗮𝘁𝗮 𝗦𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲𝘀:
𝟱. 𝗟𝗶𝘀𝘁𝘀, 𝗧𝘂𝗽𝗹𝗲𝘀, 𝗦𝗲𝘁𝘀, 𝗗𝗶𝗰𝘁𝗶𝗼𝗻𝗮𝗿𝗶𝗲𝘀:
- Understand Python's versatile data structures.
𝗔𝗱𝘃𝗮𝗻𝗰𝗲𝗱 𝗖𝗼𝗻𝗰𝗲𝗽𝘁𝘀:
𝟲. 𝗢𝗢𝗣, 𝗢𝗦 𝗖𝗼𝗺𝗽𝗮𝘁𝗶𝗯𝗶𝗹𝗶𝘁𝘆, 𝗮𝗻𝗱 𝗘𝗱𝗶𝘁𝗼𝗿𝘀:
- Delve into OOP, Python's compatibility with various OS, and popular code editors.
𝟳. 𝗦𝗰𝗿𝗶𝗽𝘁𝗶𝗻𝗴 𝗮𝗻𝗱 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻:
- Learn Python scripting for task automation.
𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗮𝗻𝗱 𝗔𝗻𝗮𝗹𝘆𝘀𝗶𝘀:
𝟴. 𝗗𝗮𝘁𝗮 𝗪𝗿𝗮𝗻𝗴𝗹𝗶𝗻𝗴, 𝗗𝗦𝗔, 𝗮𝗻𝗱 𝗩𝗲𝗿𝘀𝗶𝗼𝗻 𝗖𝗼𝗻𝘁𝗿𝗼𝗹:
- Prepare and analyze data, delve into DSA, and use Git for version control.
𝟵. 𝗪𝗲𝗯 𝗙𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸𝘀 𝗮𝗻𝗱 𝗜𝗗𝗘𝘀:
- Familiarize yourself with web frameworks, and explore IDEs like PyCharm and Jupyter.
𝟭𝟬. 𝗧𝗲𝘀𝘁𝗶𝗻𝗴 𝗮𝗻𝗱 𝗣𝗮𝗰𝗸𝗮𝗴𝗲 𝗠𝗮𝗻𝗮𝗴𝗲𝗿𝘀:
- Discover testing frameworks (Beautiful Soup, Scrapy, URLLIB) and package managers (pip, conda).
- REST
- SOAP
- GraphQL
- gRPC
- WebSockets
- Webhooks
- MQTT
- AMQP
An architectural pattern is a general, reusable solution to a common architectural problem in software design. It provides a conceptual framework for structuring and organising software systems to address specific concerns, such as scalability, maintainability, flexibility, and efficiency.
1. Microservices Architecture:
- Approach: Divides app into small, independent services with APIs.
- Example: Netflix - user management, content streaming, and recommendations as separate services.
2. Layered Architecture:
- Approach: Divides app into layers (presentation, logic, data) for specific functions.
- Example: JavaEE apps - UI, business logic, and data access in distinct layers.
3. Event-Driven Architecture:
- Approach: Components communicate through events for loose coupling.
- Example: Airbnb uses Apache Kafka for real-time event processing, like booking requests.
4. Model-View-Controller (MVC) Architecture:
- Approach: Splits app into Model (data), View (UI), Controller (logic).
- Example: Ruby on Rails apps - data, interface, and user input handling separated.
5. Master-Slave Architecture:
- Approach: One master coordinates multiple slaves' tasks.
- Example: Database replication - master for writes, slaves for reads, as seen in many systems.
6. Monolithic Architecture:
- Approach: Entire app bundled together as a single unit.
- Example: Traditional enterprise software - all features in a single executable.
7. Service-Oriented Architecture (SOA):
- Approach: App composed of reusable, loosely coupled services.
- Example: Salesforce - sales, support, and marketing services integrated or standalone.
Apart from above we have other Architectural pattern like :
Hexagonal Architecture
CQRS (Command Query Responsibility Segregation)
Lambda Architecture
Peer-to-Peer (P2P) Architecture
Pipe and Filter Architecture
Data-Centric Architecture
Each pattern offers unique advantages and trade-offs, depending on the project's requirements and complexities.
𝐈 𝐩𝐥𝐚𝐧 𝐭𝐨 𝐜𝐨𝐯𝐞𝐫 𝐞𝐯𝐞𝐫𝐲𝐭𝐡𝐢𝐧𝐠 𝐫𝐞𝐥𝐚𝐭𝐞𝐝 𝐭𝐨 𝐛𝐞𝐜𝐨𝐦𝐢𝐧𝐠 𝐚𝐧 𝐚𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭 𝐨𝐧 𝐦𝐲 𝐲𝐨𝐮𝐭𝐮𝐛𝐞 𝐜𝐡𝐚𝐧𝐧𝐞𝐥, 𝐩𝐥𝐞𝐚𝐬𝐞 𝐬𝐭𝐚𝐲 𝐭𝐮𝐧𝐞𝐝 𝐢𝐟 𝐲𝐨𝐮 𝐡𝐚𝐯𝐞 𝐧𝐨𝐭 𝐬𝐮𝐛𝐬𝐜𝐫𝐢𝐛𝐞𝐝 𝐭𝐨 𝐦𝐲 𝐜𝐡𝐚𝐧𝐧𝐞𝐥 .
