CloudSpikes MultiCloud Solutions Inc.

𝐋𝐞𝐯𝐞𝐥 𝐮𝐩 𝐲𝐨𝐮𝐫 𝐬𝐨𝐟𝐭𝐰𝐚𝐫𝐞 𝐝𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭 𝐰𝐢𝐭𝐡 𝐃𝐞𝐯𝐒𝐞𝐜𝐎𝐩𝐬! DevSecOps is an approach that integrates security throughout the entire software development lifecycle (SDLC), from coding to deployment. It ensures you're building secure applications while maintaining speed and agility. Here are key DevSecOps practices to consider: 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐞𝐝 𝐒𝐞𝐜𝐮𝐫𝐢𝐭𝐲 𝐂𝐡𝐞𝐜𝐤𝐬: Continuously scan code for vulnerabilities throughout development. 𝐂𝐨𝐧𝐭𝐢𝐧𝐮𝐨𝐮𝐬 𝐌𝐨𝐧𝐢𝐭𝐨𝐫𝐢𝐧𝐠: Proactively identify and address security threats. 𝐂𝐈/𝐂𝐃 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧: Integrate security testing seamlessly into your CI/CD pipeline. 𝐈𝐧𝐟𝐫𝐚𝐬𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞 𝐚𝐬 𝐂𝐨𝐝𝐞 (𝐈𝐚𝐂): Manage and secure your infrastructure with code. 𝐂𝐨𝐧𝐭𝐚𝐢𝐧𝐞𝐫 𝐒𝐞𝐜𝐮𝐫𝐢𝐭𝐲: Secure containerized applications throughout their lifecycle. 𝐒𝐞𝐜𝐫𝐞𝐭 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭: Securely store and manage sensitive data. 𝐓𝐡𝐫𝐞𝐚𝐭 𝐌𝐨𝐝𝐞𝐥𝐢𝐧𝐠: Proactively identify and mitigate potential security risks. 𝐐𝐮𝐚𝐥𝐢𝐭𝐲 𝐀𝐬𝐬𝐮𝐫𝐚𝐧𝐜𝐞 (𝐐𝐀) 𝐈𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐢𝐨𝐧: Integrate security testing into your QA process. 𝐂𝐨𝐥𝐥𝐚𝐛𝐨𝐫𝐚𝐭𝐢𝐨𝐧 𝐚𝐧𝐝 𝐂𝐨𝐦𝐦𝐮𝐧𝐢𝐜𝐚𝐭𝐢𝐨𝐧: Foster a culture of shared responsibility for security across Dev, Sec, and Ops teams. 𝐕𝐮𝐥𝐧𝐞𝐫𝐚𝐛𝐢𝐥𝐢𝐭𝐲 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭: Identify, prioritize, and remediate vulnerabilities effectively. Credits to Satyender Sharma for this insightful creation. 𝐅𝐨𝐥𝐥𝐨𝐰 𝐮𝐬 𝐨𝐧 𝐋𝐢𝐧𝐤𝐞𝐝𝐈𝐧 👉🏻 https://lnkd.in/e2sq98PN https://lnkd.in/e-9dJf8i 𝐅𝐨𝐥𝐥𝐨𝐰 𝐮𝐬 𝐨𝐧 𝐅𝐚𝐜𝐞𝐛𝐨𝐨𝐤 👉🏻 https://lnkd.in/eWcXVwAt 𝐅𝐨𝐥𝐥𝐨𝐰 𝐮𝐬 𝐨𝐧 𝐈𝐧𝐬𝐭𝐚𝐠𝐫𝐚𝐦 👉🏻https://lnkd.in/ehA5ePqX

7 Critical Networking Protocols for Technology Professionals As a technology professional, understanding core networking protocols is essential for building and maintaining robust systems. Here's a concise guide to the most important protocols you should know: 1. TCP/IP - The fundamental protocol suite powering the internet - TCP ensures reliable data delivery with error checking and flow control - IP handles network addressing and routing - Critical for web services (HTTP:80, HTTPS:443) 2. DNS - Translates domain names to IP addresses - Consists of root servers, TLD servers, and authoritative name servers - Supports multiple record types (A, AAAA, MX, CNAME) - Essential for web infrastructure and email routing 3. HTTP/HTTPS - Powers modern web communications - Implements RESTful methods (GET, POST, PUT, DELETE) - Status codes indicate request outcomes - HTTPS adds encryption for secure data transfer 4. SMTP - Core email transmission protocol - Works alongside POP3 and IMAP - Implements security through SPF, DKIM, and DMARC - Operates on ports 25 (standard) and 587 (TLS) 5. FTP - Standard file transfer protocol - Supports active and passive modes - Secure variants include SFTP and FTPS - Ideal for large file transfers 6. UDP - Optimized for speed over reliability - Perfect for real-time applications (VoIP, streaming) - Provides minimal overhead - Commonly used with DNS and DHCP 7. DHCP - Automates IP address management - Uses DORA process for address assignment - Configures essential network parameters - Crucial for network scaling These protocols form the backbone of modern networking. Understanding them deeply enables better system design, troubleshooting, and performance optimization. Credit:- Brij kishore Pandey 𝐅𝐨𝐥𝐥𝐨𝐰 𝐮𝐬 𝐨𝐧 𝐋𝐢𝐧𝐤𝐞𝐝𝐈𝐧 👉🏻 https://lnkd.in/e2sq98PN https://lnkd.in/e-9dJf8i 𝐅𝐨𝐥𝐥𝐨𝐰 𝐮𝐬 𝐨𝐧 𝐅𝐚𝐜𝐞𝐛𝐨𝐨𝐤 👉🏻 https://lnkd.in/eWcXVwAt 𝐅𝐨𝐥𝐥𝐨𝐰 𝐮𝐬 𝐨𝐧 𝐈𝐧𝐬𝐭𝐚𝐠𝐫𝐚𝐦 👉🏻https://lnkd.in/ehA5ePqX

𝐓𝐡𝐞 𝐄𝐬𝐬𝐞𝐧𝐭𝐢𝐚𝐥 𝐒𝐭𝐞𝐩𝐬 𝐨𝐟 𝐚 𝐂𝐈/𝐂𝐃 𝐏𝐢𝐩𝐞𝐥𝐢𝐧𝐞 A CI/CD (Continuous Integration/Continuous Deployment) pipeline automates the process of software development, testing, and deployment. 1. 𝐂𝐨𝐝𝐞 𝐂𝐡𝐚𝐧𝐠𝐞𝐬: - What Happens? Developers make updates to the codebase. - Purpose: Initiates the pipeline. 2. 𝐂𝐨𝐝𝐞 𝐑𝐞𝐩𝐨𝐬𝐢𝐭𝐨𝐫𝐲: - What Happens? Code is pushed to Git or similar. - Purpose: Triggers the pipeline. 3. 𝐁𝐮𝐢𝐥𝐝: - What Happens? The CI server compiles the code. - Purpose: Produces executable artifacts. 4. 𝐏𝐫𝐞𝐝𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭 𝐓𝐞𝐬𝐭𝐢𝐧𝐠: - What Happens?: Automated tests are executed. - Purpose: These tests verify that the new code doesn't introduce errors. 5. 𝐒𝐭𝐚𝐠𝐢𝐧𝐠 𝐄𝐧𝐯𝐢𝐫𝐨𝐧𝐦𝐞𝐧𝐭: - What Happens?: If the code passes the tests, the built artifacts are deployed to a staging environment. - Purpose: The staging environment closely resembles the production environment . 6. 𝐒𝐭𝐚𝐠𝐢𝐧𝐠 𝐓𝐞𝐬𝐭𝐬: - What Happens?: Additional tests, such as performance tests or user acceptance tests, are conducted . - Purpose: These tests ensure that the application behaves as expected in a production-like environment, catching any issues that might not have been apparent in earlier testing phases. 7. 𝐀𝐩𝐩𝐫𝐨𝐯𝐚𝐥/𝐆𝐚𝐭𝐞: - What Happens?: In some cases, manual approval or automated checks are required before proceeding to production. - Purpose: This step acts as a safety net, allowing for human oversight . 8. 𝐃𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭 𝐭𝐨 𝐏𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧: - What Happens?: Once approved, the artifacts are deployed to the live production environment. - Purpose: This step makes the new code available to end-users, delivering the new features, fixes, or improvements. 9. 𝐏𝐨𝐬𝐭-𝐝𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭 𝐓𝐞𝐬𝐭𝐢𝐧𝐠: - What Happens?: After deployment, additional tests are run in the production environment. - Purpose: These tests ensure that the application is stable, performs well, and that the deployment did not introduce any new issues. 10. 𝐌𝐨𝐧𝐢𝐭𝐨𝐫𝐢𝐧𝐠: - What Happens?: Continuous monitoring tools track the application's performance and user behavior in real-time. - Purpose: Monitoring helps detect potential issues early, gather insights into how the application is being used, and ensure that the system is running smoothly. 11. 𝐑𝐨𝐥𝐥𝐛𝐚𝐜𝐤 (𝐈𝐟 𝐍𝐞𝐜𝐞𝐬𝐬𝐚𝐫𝐲): - What Happens?: If issues are detected in production, the CI/CD pipeline can trigger a rollback to a previous stable version. - Purpose: This step provides a safety mechanism to quickly undo a deployment that causes problems, minimizing downtime and user impact. 12. 𝐍𝐨𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧: - What Happens?: The CI/CD pipeline sends notifications to stakeholders about the status of the deployment. - Purpose: Keeping everyone informed promotes transparency and accountability . Credit:- Satyender Sharma #devops #ci/cd #

Load Balancers, Reverse Proxies, Forward Proxies, and API Gateways Load Balancer What: Distributes incoming traffic across multiple servers to enhance availability, scalability, and reliability, operating at either the transport (Layer 4) or application layer (Layer 7). Use Cases: Ideal for balancing web or app traffic, preventing server overload, and ensuring fault tolerance in high-traffic environments. Question: How does your current setup handle traffic spikes, and do you think a load balancer could optimize it further? Reverse Proxy What: An intermediary that forwards client requests to the appropriate servers, often enhancing security and load balancing at the application layer (Layer 7). Use Cases: Shields internal servers, handles SSL/TLS encryption, and balances incoming requests to improve performance and security. Question: Is your application protected by a reverse proxy? What benefits have you observed, or would you like to see? Forward Proxy What: An intermediary for clients accessing external resources, masking client identity and offering caching and content filtering at the application layer. Use Cases: Provides client anonymity, controls internet access, and optimizes bandwidth by caching frequently accessed content. Question: Have you considered using a forward proxy for better client privacy or content control in your organization? API Gateway What: A central entry point for managing APIs, with features like authentication, rate limiting, and logging, operating at the application layer. Use Cases: Secures and manages APIs, enforces policies, limits abuse, and provides logging for analytics and compliance. Question: Are you leveraging an API gateway for your microservices? How has it impacted your API security and performance? In essence, Load Balancers focus on traffic distribution, Reverse Proxies boost server security and performance, Forward Proxies manage client access and anonymity, and API Gateways secure and streamline API management. Which of these components could bring the most benefit to your current system architecture? Credit:- Rocky Bhatia 𝐅𝐨𝐥𝐥𝐨𝐰 𝐮𝐬 𝐨𝐧 𝐋𝐢𝐧𝐤𝐞𝐝𝐈𝐧 👉🏻 https://lnkd.in/e2sq98PN https://lnkd.in/e-9dJf8i 𝐅𝐨𝐥𝐥𝐨𝐰 𝐮𝐬 𝐨𝐧 𝐅𝐚𝐜𝐞𝐛𝐨𝐨𝐤 👉🏻 https://lnkd.in/eWcXVwAt 𝐅𝐨𝐥𝐥𝐨𝐰 𝐮𝐬 𝐨𝐧 𝐈𝐧𝐬𝐭𝐚𝐠𝐫𝐚𝐦 👉🏻https://lnkd.in/ehA5ePqX

𝗨𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱𝗶𝗻𝗴 𝗛𝗧𝗧𝗣𝗦 𝗘𝗻𝗰𝗿𝘆𝗽𝘁𝗶𝗼𝗻: 𝗔 𝗦𝘁𝗲𝗽-𝗯𝘆-𝗦𝘁𝗲𝗽 𝗣𝗿𝗼𝗰𝗲𝘀𝘀 HTTPS encryption is crucial for securing online data exchanges. Here’s a breakdown of how it works, focusing on the key steps involved in establishing a secure, encrypted connection between a browser and a server. 𝗛𝗼𝘄 𝗛𝗧𝗧𝗣𝗦 𝗘𝗻𝗰𝗿𝘆𝗽𝘁𝗶𝗼𝗻 𝗪𝗼𝗿𝗸𝘀 1. 𝗖𝗼𝗻𝗻𝗲𝗰𝘁𝗶𝗼𝗻 𝗥𝗲𝗾𝘂𝗲𝘀𝘁: The browser initiates a secure HTTPS connection with the website. 2. 𝗦𝗲𝗿𝘃𝗲𝗿’𝘀 𝗣𝘂𝗯𝗹𝗶𝗰 𝗞𝗲𝘆: The server responds by sending its public key, included in its SSL/TLS certificate. This key is used to verify the server’s identity. 3. 𝗦𝗲𝘀𝘀𝗶𝗼𝗻 𝗞𝗲𝘆 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝗼𝗻: The browser generates a unique session key for this particular connection. 4. 𝗔𝘀𝘆𝗺𝗺𝗲𝘁𝗿𝗶𝗰 𝗘𝗻𝗰𝗿𝘆𝗽𝘁𝗶𝗼𝗻: The browser encrypts the session key with the server’s public key and sends it to the server. This is 𝗮𝘀𝘆𝗺𝗺𝗲𝘁𝗿𝗶𝗰 𝗲𝗻𝗰𝗿𝘆𝗽𝘁𝗶𝗼𝗻—a method where a pair of keys (a public key and a private key) is used. The public key encrypts data, while only the corresponding private key can decrypt it. This ensures that only the intended server can access the session key. 5. 𝗦𝘆𝗺𝗺𝗲𝘁𝗿𝗶𝗰 𝗘𝗻𝗰𝗿𝘆𝗽𝘁𝗶𝗼𝗻: Once the server receives the encrypted session key and decrypts it using its private key, both the browser and server use this session key for 𝘀𝘆𝗺𝗺𝗲𝘁𝗿𝗶𝗰 𝗲𝗻𝗰𝗿𝘆𝗽𝘁𝗶𝗼𝗻. In symmetric encryption, the same key is used for both encryption and decryption, making it faster and more efficient for continuous data exchange. 6. 𝗦𝗲𝗰𝘂𝗿𝗲 𝗗𝗮𝘁𝗮 𝗧𝗿𝗮𝗻𝘀𝗳𝗲𝗿: All data exchanged in this session is encrypted with the session key, ensuring confidentiality and integrity of the information. 𝗪𝗵𝘆 𝗛𝗧𝗧𝗣𝗦 𝗠𝗮𝘁𝘁𝗲𝗿𝘀 This process ensures that sensitive information—such as login credentials, payment data, and personal information—is encrypted and secure during transmission. HTTPS provides: - 𝗖𝗼𝗻𝗳𝗶𝗱𝗲𝗻𝘁𝗶𝗮𝗹𝗶𝘁𝘆: Data remains private and unreadable by third parties. - 𝗜𝗻𝘁𝗲𝗴𝗿𝗶𝘁𝘆: Data is protected from tampering during transmission. - 𝗔𝘂𝘁𝗵𝗲𝗻𝘁𝗶𝗰𝗮𝘁𝗶𝗼𝗻: Verifies the server’s legitimacy, safeguarding against malicious actors. In an era where data security is non-negotiable, HTTPS encryption is essential for protecting information and establishing trust in digital interactions. Credit: Brij kishore Pandey 𝐅𝐨𝐥𝐥𝐨𝐰 𝐮𝐬 𝐨𝐧 𝐋𝐢𝐧𝐤𝐞𝐝𝐈𝐧 👉🏻 https://lnkd.in/e2sq98PN https://lnkd.in/e-9dJf8i 𝐅𝐨𝐥𝐥𝐨𝐰 𝐮𝐬 𝐨𝐧 𝐅𝐚𝐜𝐞𝐛𝐨𝐨𝐤 👉🏻 https://lnkd.in/eWcXVwAt 𝐅𝐨𝐥𝐥𝐨𝐰 𝐮𝐬 𝐨𝐧 𝐈𝐧𝐬𝐭𝐚𝐠𝐫𝐚𝐦 👉🏻https://lnkd.in/ehA5ePqX

𝐋𝐞𝐚𝐫𝐧 𝐭𝐨 𝐁𝐮𝐢𝐥𝐝 𝐚𝐧𝐝 𝐃𝐞𝐩𝐥𝐨𝐲 𝐚 𝐃𝐨𝐜𝐤𝐞𝐫 𝐈𝐦𝐚𝐠𝐞 𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗮 𝗗𝗼𝗰𝗸𝗲𝗿 𝗜𝗺𝗮𝗴𝗲: 1. Dockerfile: Create a text file with instructions to build the image. 2. Base Image: Start with a base image like Ubuntu or Alpine Linux. 3. Dependencies: Install necessary dependencies using commands like `RUN`. 4. Application Code: Copy your application code into the image. 5. Ports: Expose any necessary ports with `EXPOSE`. 6. Build: Run `docker build` command to build the image. 𝗗𝗲𝗽𝗹𝗼𝘆𝗶𝗻𝗴 𝗮 𝗗𝗼𝗰𝗸𝗲𝗿 𝗜𝗺𝗮𝗴𝗲: 1. Docker Registry: Store your built images in a Docker registry like Docker Hub. 2. Docker Compose: Define services, networks, and volumes in a `docker•compose.yml` file. 3. Deploy: Run `docker•compose up` to deploy your application. 𝗕𝗲𝘀𝘁 𝗣𝗿𝗮𝗰𝘁𝗶𝗰𝗲𝘀: • Keep images small by minimizing layers and dependencies. • Use `.dockerignore` to exclude unnecessary files. • Regularly update base images and dependencies for security patches. Credit:- TheAlpha.Dev #docker #devops #engineering #kubernetes

𝐃𝐞𝐯𝐎𝐩𝐬 𝐑𝐨𝐚𝐝𝐦𝐚𝐩 Programming Language Choose a language that aligns with your project needs and team expertise. Master at least one scripting language (e.g., Python, Ruby) for automation. Version Control Learn Git for efficient and collaborative code management. Understand branching strategies and best practices. Automation Tools Explore configuration management tools (e.g., Ansible, Puppet) for infrastructure as code. Familiarize yourself with tools like Jenkins for continuous integration. Management Tool & Deployment Utilize tools like Docker for containerization. Learn about deployment strategies and orchestration tools (e.g., Kubernetes). CI/CD Tools Implement continuous integration with Jenkins or GitLab CI. Build automated deployment pipelines for continuous delivery. Test Automation Tools Master testing frameworks like JUnit or NUnit. Use tools like Selenium for end-to-end testing. Monitoring Tools Understand monitoring concepts and tools (e.g., Prometheus, Grafana). Set up alerts and create dashboards for effective monitoring. DBMS Gain expertise in one or more database systems (e.g., MySQL, PostgreSQL). Understand database scaling and optimization. Containerization Tools Dive into containerization tools like Docker. Learn about container networking and storage. Container Orchestration Explore container orchestration tools such as Kubernetes. Understand service discovery and load balancing. Cloud Computing Familiarize yourself with cloud platforms (e.g., AWS, Azure, GCP). Learn how to deploy and manage applications in the cloud. Credits to TheAlpha.Dev for this insightful creation. 𝐅𝐨𝐥𝐥𝐨𝐰 𝐮𝐬 𝐨𝐧 𝐋𝐢𝐧𝐤𝐞𝐝𝐈𝐧 👉🏻 https://lnkd.in/e2sq98PN https://lnkd.in/e-9dJf8i 𝐅𝐨𝐥𝐥𝐨𝐰 𝐮𝐬 𝐨𝐧 𝐅𝐚𝐜𝐞𝐛𝐨𝐨𝐤 👉🏻 https://lnkd.in/eWcXVwAt 𝐅𝐨𝐥𝐥𝐨𝐰 𝐮𝐬 𝐨𝐧 𝐈𝐧𝐬𝐭𝐚𝐠𝐫𝐚𝐦 👉🏻https://lnkd.in/ehA5ePqX #DevOps #Programming #Automation #CI/CD #CloudComputing #TechSkills #DevOpsRoadmap

𝐖𝐡𝐲 𝐑𝐞𝐝𝐢𝐬 𝐢𝐬 𝐬𝐨 𝐟𝐚𝐬𝐭 ? Redis stands out for its lightning-fast speed and performance, especially in in-memory data storage. Here’s why: 1. In-Memory Storage: Data is stored in memory, avoiding slow disk I/O operations for super-fast reads/writes. 2. Optimised Data Structures: Specialised structures (strings, hashes, sets) minimise memory usage while maximising speed. 3. Single-Threaded Architecture: Simple event-loop handling ensures efficiency without complex locking mechanisms. 4. Asynchronous I/O: Redis handles multiple connections concurrently without separate threads, boosting responsiveness. 5. Efficient Persistence: Offers flexible persistence options with minimal impact on performance. 6. Streamlined Protocol: A simple protocol minimises overhead for faster command processing. 7. No SQL Overhead: Lacks a query language like SQL, eliminating query parsing and execution delays. 8. Memory Optimisation: Custom allocators and compression reduce memory usage and maximise efficiency. In short, Redis’s architecture makes it the go-to choice for fast, efficient data storage and retrieval. Credits to Rocky Bhatia for this insightful creation. 𝐅𝐨𝐥𝐥𝐨𝐰 𝐮𝐬 𝐨𝐧 𝐋𝐢𝐧𝐤𝐞𝐝𝐈𝐧 👉🏻 https://lnkd.in/e2sq98PN https://lnkd.in/e-9dJf8i 𝐅𝐨𝐥𝐥𝐨𝐰 𝐮𝐬 𝐨𝐧 𝐅𝐚𝐜𝐞𝐛𝐨𝐨𝐤 👉🏻 https://lnkd.in/eWcXVwAt 𝐅𝐨𝐥𝐥𝐨𝐰 𝐮𝐬 𝐨𝐧 𝐈𝐧𝐬𝐭𝐚𝐠𝐫𝐚𝐦 👉🏻https://lnkd.in/ehA5ePqX

How to build a machine learning model ? Building a machine learning model typically involves several key steps, Please note that this is a general overview, and the specific implementation may vary depending on your dataset and the machine learning library you are using. 1. Define the Problem: Determine whether it's a classification task (e.g., spam or not spam) or a regression task (e.g., predicting house prices). 2. Gather and Prep Data: Collect relevant data from various sources. Clean the data by handling missing values, outliers, and inconsistencies Split the data into input features (X) and the target variable (y) 3. Explore the Data (EDA): Perform EDA to understand the data's distribution, statistics, and relationships between variables. 4. Split the Dataset: Divide the dataset into training and testing sets. The training set is used to train the model, while the testing set is used to evaluate its performance. 5. Choose an Algorithm: Select an appropriate machine learning algorithm based on the nature of your problem (e.g., linear regression, decision tree, neural networks). 6. Train the Model: Train the chosen machine learning algorithm on the training data. 7. Optimize Hyperparameters: Fine-tune the model by optimizing hyperparameters. 8. Feature Selection: Consider feature selection techniques to reduce dimensionality and improve model efficiency and performance. 9. Cross-Validation: Assess the model's performance more robustly using techniques like k-fold cross-validation. 10. Evaluate the Model: Use appropriate evaluation metrics to assess the model's performance on the testing set. 11. Deploy: Once satisfied with the model's performance, deploy it in real-world applications. Remember that the specific steps and tools used may vary depending on the problem, data, and machine learning library you're using. Building machine learning models is an iterative process that often involves experimenting with different approaches to achieve the best results. Credits to Rocky Bhatia for this insightful creation. 𝐅𝐨𝐥𝐥𝐨𝐰 𝐮𝐬 𝐨𝐧 𝐋𝐢𝐧𝐤𝐞𝐝𝐈𝐧 👉🏻 https://lnkd.in/e2sq98PN https://lnkd.in/e-9dJf8i 𝐅𝐨𝐥𝐥𝐨𝐰 𝐮𝐬 𝐨𝐧 𝐅𝐚𝐜𝐞𝐛𝐨𝐨𝐤 👉🏻 https://lnkd.in/eWcXVwAt 𝐅𝐨𝐥𝐥𝐨𝐰 𝐮𝐬 𝐨𝐧 𝐈𝐧𝐬𝐭𝐚𝐠𝐫𝐚𝐦 👉🏻https://lnkd.in/ehA5ePqX

𝐁𝐞𝐬𝐭 𝐖𝐚𝐲 𝐭𝐨 𝐔𝐧𝐝𝐞𝐫𝐬𝐭𝐚𝐧𝐝 𝐊𝐮𝐛𝐞𝐫𝐧𝐞𝐭𝐞𝐬 𝐀𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐮𝐫𝐞 Kubernetes is an open-source container orchestration platform that automates the deployment, scaling, and management of containerized applications, allowing for seamless and efficient container orchestration in a cluster of machines. Let's break it down using a familiar scenario: a restaurant! Kubernetes Cluster: The Restaurant - Think of the cluster as the restaurant itself – where everything happens. It's the place with tables, chairs, and a bustling kitchen. Nodes: The Kitchen and Waitstaff - Nodes are like the kitchen and the waitstaff combined. They run the show, with worker nodes as chefs and master nodes as the head chef ensuring everything runs smoothly. Containers: Plates of Food - Containers are like plates of food. They hold all the ingredients (code, libraries, dependencies) needed to run an application. Pods: Plates and Cutlery - Pods are like plates with cutlery. They can contain multiple containers (just like a plate can have different foods) and share the same network space. Deployments: The Menu - Deployments are your menu – they specify what dishes (containers) are available, how many, and how they should be served. Services: The Waitstaff Taking Orders - Services act like the waitstaff. They route requests to the right pods based on labels and selectors, ensuring seamless communication. 📖 ConfigMaps and Secrets: The Recipe Book - ConfigMaps and Secrets are your recipe book, storing configuration data and sensitive info separately from the application code. 🚪 Ingress Controllers: The Menu Display - Ingress controllers are like the menu display outside the restaurant, directing external requests to the right services. ❄️ Persistent Storage: The Fridge and Pantry - Persistent storage is your fridge and pantry, where important data is stored, persisting even if a container is replaced. So, Kubernetes orchestrates your application just like a restaurant serves meals - efficiently and seamlessly. Credits to Rocky Bhatia for this insightful creation. 𝐅𝐨𝐥𝐥𝐨𝐰 𝐮𝐬 𝐨𝐧 𝐋𝐢𝐧𝐤𝐞𝐝𝐈𝐧 👉🏻 https://lnkd.in/e2sq98PN https://lnkd.in/e-9dJf8i 𝐅𝐨𝐥𝐥𝐨𝐰 𝐮𝐬 𝐨𝐧 𝐅𝐚𝐜𝐞𝐛𝐨𝐨𝐤 👉🏻 https://lnkd.in/eWcXVwAt 𝐅𝐨𝐥𝐥𝐨𝐰 𝐮𝐬 𝐨𝐧 𝐈𝐧𝐬𝐭𝐚𝐠𝐫𝐚𝐦 👉🏻https://lnkd.in/ehA5ePqX