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Arvind

@aravind_mutthe

Cyber Security expert | โ˜๏ธ DevOps & Cloud Enthusiast | Protecting data in the cloud and securing the digital realm. ๐Ÿ›ก๏ธ #CyberSecurity #DevOps #Cloudsecurity
New York, USA
Joined November 2013
3.5K Following
187 Followers
96 Posts
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gxjo Verified account @gxjo_dev
Things You Should Know As a Backend Engineer (2026) APIs โ€“ REST, gRPC, WebSockets Auth โ€“ JWT, OAuth2, RBAC Databases โ€“ SQL + NoSQL, indexing Caching โ€“ Redis, invalidation Queues โ€“ Kafka, RabbitMQ Concurrency โ€“ async, workers System Design โ€“ scaling, replication Security โ€“ OWASP basics Observability โ€“ logs, metrics, tracing DevOps โ€“ Docker, CI/CD basics
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Uday๐Ÿ‘จโ€๐Ÿ’ป Verified account @uday_devops
Terraform Basics that Every DevOps Engineer Should Master Before jumping into complex infra, get your ๐—ง๐—ฒ๐—ฟ๐—ฟ๐—ฎ๐—ณ๐—ผ๐—ฟ๐—บ ๐—ณ๐˜‚๐—ป๐—ฑ๐—ฎ๐—บ๐—ฒ๐—ป๐˜๐—ฎ๐—น๐˜€ right - especially variables. ๐Ÿ”น ๐—ฆ๐˜๐—ฟ๐—ถ๐—ป๐—ด -> Resource names, tags ๐Ÿ”น ๐—ก๐˜‚๐—บ๐—ฏ๐—ฒ๐—ฟ -> Counts, ports ๐Ÿ”น ๐—•๐—ผ๐—ผ๐—น๐—ฒ๐—ฎ๐—ป -> Enable/Disable features ๐Ÿ”น ๐—Ÿ๐—ถ๐˜€๐˜ -> Multiple values (subnets, IPs) ๐Ÿ”น ๐— ๐—ฎ๐—ฝ -> Key-value configs (tags, env settings) ๐Ÿ’ก Why it matters: Clean variables = reusable code + scalable infrastructure Small basics, big impact.
uday_devops's tweet photo. Terraform Basics that Every DevOps Engineer Should Master Before jumping into complex infra, get your ๐—ง๐—ฒ๐—ฟ๐—ฟ๐—ฎ๐—ณ๐—ผ๐—ฟ๐—บ ๐—ณ๐˜‚๐—ป๐—ฑ๐—ฎ๐—บ๐—ฒ๐—ป๐˜๐—ฎ๐—น๐˜€ right - especially variables. ๐Ÿ”น ๐—ฆ๐˜๐—ฟ๐—ถ๐—ป๐—ด -> Resource names, tags ๐Ÿ”น ๐—ก๐˜‚๐—บ๐—ฏ๐—ฒ๐—ฟ -> Counts, ports ๐Ÿ”น ๐—•๐—ผ๐—ผ๐—น๐—ฒ๐—ฎ๐—ป -> Enable/Disable features ๐Ÿ”น ๐—Ÿ๐—ถ๐˜€๐˜ -> Multiple values (subnets, IPs) ๐Ÿ”น ๐— ๐—ฎ๐—ฝ -> Key-value configs (tags, env settings) ๐Ÿ’ก Why it matters: Clean variables = reusable code + scalable infrastructure Small basics, big impact.
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Dhanian ๐Ÿ—ฏ๏ธ Verified account @e_opore
PODS IN KUBERNETES EXPLAINED Think of a Pod like a small apartment unit inside a huge Kubernetes city. Inside the apartment, containers live together, share resources, and work as a team. WHAT IS A POD โ†’ a Pod is the smallest deployable unit in Kubernetes โ†’ it wraps one or more containers together โ†’ containers inside a pod share: โ†’ network โ†’ storage โ†’ localhost communication โ†’ Pods run applications inside the cluster WHY PODS EXIST โ†’ containers alone are isolated โ†’ Kubernetes needs a way to manage them as a group โ†’ Pod acts like a protective wrapper around containers โ†’ provides: โ†’ networking โ†’ storage โ†’ lifecycle management SINGLE CONTAINER POD โ†’ most pods contain only one container โ†’ example โ†’ nginx web server inside one pod โ†’ analogy โ†’ one person living in one apartment MULTI-CONTAINER POD โ†’ sometimes multiple containers run together in one pod โ†’ containers cooperate closely โ†’ example โ†’ main app container โ†’ logging sidecar container โ†’ analogy โ†’ roommates sharing the same apartment POD NETWORKING โ†’ every Pod gets its own IP address โ†’ containers inside the pod communicate using localhost โ†’ Pods communicate with other Pods through the cluster network โ†’ analogy โ†’ apartment has one shared address โ†’ roommates talk internally for free POD STORAGE โ†’ Pods can share storage volumes โ†’ all containers inside the pod access the same volume โ†’ useful for: โ†’ shared logs โ†’ shared files โ†’ temporary data HOW PODS WORK โ†’ developer creates deployment YAML โ†’ Kubernetes scheduler chooses a node โ†’ Pod is deployed onto that node โ†’ containers inside pod start running POD LIFECYCLE โ†’ Pending โ†’ pod is being created โ†’ Running โ†’ containers are active โ†’ Succeeded โ†’ task completed successfully โ†’ Failed โ†’ pod encountered an error โ†’ Unknown โ†’ Kubernetes cannot determine state POD RESTARTING โ†’ Pods are temporary and replaceable โ†’ if a pod crashes โ†’ Kubernetes creates a new one automatically โ†’ this ensures high availability PODS & NODES โ†’ Pods run on worker nodes โ†’ one node can host many pods โ†’ Kubernetes distributes pods across nodes for scalability SIDECAR CONTAINER PATTERN โ†’ helper container runs beside the main application โ†’ examples โ†’ logging agent โ†’ monitoring collector โ†’ proxy container โ†’ analogy โ†’ assistant living in the same apartment helping the main resident INIT CONTAINERS โ†’ special containers that run before the main app starts โ†’ used for setup tasks โ†’ examples โ†’ database migration โ†’ configuration setup POD COMMUNICATION FLOW โ†’ user sends request โ†’ service routes traffic โ†’ pod receives request โ†’ container processes request โ†’ response returned to user WHY PODS ARE IMPORTANT โ†’ foundation of Kubernetes workloads โ†’ simplify deployment and scaling โ†’ enable self-healing systems โ†’ provide resource isolation and sharing COMMON POD ISSUES โ†’ CrashLoopBackOff โ†’ app repeatedly crashes โ†’ ImagePullBackOff โ†’ container image cannot be downloaded โ†’ Pending state โ†’ insufficient cluster resources BEST PRACTICES โ†’ keep pods lightweight โ†’ use one main container per pod when possible โ†’ define resource limits โ†’ use health probes โ†’ avoid storing permanent data inside pods REAL WORLD ANALOGY โ†’ Kubernetes cluster = city โ†’ node = apartment building โ†’ pod = apartment unit โ†’ container = resident inside apartment โ†’ sidecar container = assistant roommate โ†’ service = delivery routing system END TO END FLOW โ†’ developer deploys pod โ†’ scheduler selects node โ†’ pod starts containers โ†’ pod receives traffic โ†’ Kubernetes monitors pod health โ†’ failed pod replaced automatically Grab the KUBERNETES EBOOK: https://t.co/1JQaCCc17i
e_opore's tweet photo. PODS IN KUBERNETES EXPLAINED Think of a Pod like a small apartment unit inside a huge Kubernetes city. Inside the apartment, containers live together, share resources, and work as a team. WHAT IS A POD โ†’ a Pod is the smallest deployable unit in Kubernetes โ†’ it wraps one or more containers together โ†’ containers inside a pod share: โ†’ network โ†’ storage โ†’ localhost communication โ†’ Pods run applications inside the cluster WHY PODS EXIST โ†’ containers alone are isolated โ†’ Kubernetes needs a way to manage them as a group โ†’ Pod acts like a protective wrapper around containers โ†’ provides: โ†’ networking โ†’ storage โ†’ lifecycle management SINGLE CONTAINER POD โ†’ most pods contain only one container โ†’ example โ†’ nginx web server inside one pod โ†’ analogy โ†’ one person living in one apartment MULTI-CONTAINER POD โ†’ sometimes multiple containers run together in one pod โ†’ containers cooperate closely โ†’ example โ†’ main app container โ†’ logging sidecar container โ†’ analogy โ†’ roommates sharing the same apartment POD NETWORKING โ†’ every Pod gets its own IP address โ†’ containers inside the pod communicate using localhost โ†’ Pods communicate with other Pods through the cluster network โ†’ analogy โ†’ apartment has one shared address โ†’ roommates talk internally for free POD STORAGE โ†’ Pods can share storage volumes โ†’ all containers inside the pod access the same volume โ†’ useful for: โ†’ shared logs โ†’ shared files โ†’ temporary data HOW PODS WORK โ†’ developer creates deployment YAML โ†’ Kubernetes scheduler chooses a node โ†’ Pod is deployed onto that node โ†’ containers inside pod start running POD LIFECYCLE โ†’ Pending โ†’ pod is being created โ†’ Running โ†’ containers are active โ†’ Succeeded โ†’ task completed successfully โ†’ Failed โ†’ pod encountered an error โ†’ Unknown โ†’ Kubernetes cannot determine state POD RESTARTING โ†’ Pods are temporary and replaceable โ†’ if a pod crashes โ†’ Kubernetes creates a new one automatically โ†’ this ensures high availability PODS & NODES โ†’ Pods run on worker nodes โ†’ one node can host many pods โ†’ Kubernetes distributes pods across nodes for scalability SIDECAR CONTAINER PATTERN โ†’ helper container runs beside the main application โ†’ examples โ†’ logging agent โ†’ monitoring collector โ†’ proxy container โ†’ analogy โ†’ assistant living in the same apartment helping the main resident INIT CONTAINERS โ†’ special containers that run before the main app starts โ†’ used for setup tasks โ†’ examples โ†’ database migration โ†’ configuration setup POD COMMUNICATION FLOW โ†’ user sends request โ†’ service routes traffic โ†’ pod receives request โ†’ container processes request โ†’ response returned to user WHY PODS ARE IMPORTANT โ†’ foundation of Kubernetes workloads โ†’ simplify deployment and scaling โ†’ enable self-healing systems โ†’ provide resource isolation and sharing COMMON POD ISSUES โ†’ CrashLoopBackOff โ†’ app repeatedly crashes โ†’ ImagePullBackOff โ†’ container image cannot be downloaded โ†’ Pending state โ†’ insufficient cluster resources BEST PRACTICES โ†’ keep pods lightweight โ†’ use one main container per pod when possible โ†’ define resource limits โ†’ use health probes โ†’ avoid storing permanent data inside pods REAL WORLD ANALOGY โ†’ Kubernetes cluster = city โ†’ node = apartment building โ†’ pod = apartment unit โ†’ container = resident inside apartment โ†’ sidecar container = assistant roommate โ†’ service = delivery routing system END TO END FLOW โ†’ developer deploys pod โ†’ scheduler selects node โ†’ pod starts containers โ†’ pod receives traffic โ†’ Kubernetes monitors pod health โ†’ failed pod replaced automatically Grab the KUBERNETES EBOOK: https://t.co/1JQaCCc17i
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yourclouddude Verified account @yourclouddude
Learn AWS to Master Cloud ๐Ÿš€
yourclouddude's tweet photo. Learn AWS to Master Cloud ๐Ÿš€ https://t.co/BootZI2mrg
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Abdelhadi
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ุนุงุดุช ุงู„ู…ู…ู„ูƒุฉ ุงู„ู…ุบุฑุจูŠุฉ ู…ู„ูƒุง ูˆุดุนุจุง ุŒูˆู„ุง ุนุฒุงุก ู„ู„ุฎูˆู†ุฉ ูˆุฃุนุฏุงุก ุงู„ูˆุทู†๐Ÿ‡ฒ๐Ÿ‡ฆ๐Ÿ‡ฒ๐Ÿ‡ฆ๐Ÿ‡ฒ๐Ÿ‡ฆ๐Ÿ‡ฒ๐Ÿ‡ฆ
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Carson Cunningham
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D@n
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Dhanian ๐Ÿ—ฏ๏ธ Verified account @e_opore
DATA STRUCTURES & ALGORITHMS (DSA) ROADMAP FOUNDATIONS What is DSA โ†’ Study of organizing data and solving problems efficiently Why DSA โ†’ Improves problem-solving and coding interview performance Time Complexity โ†’ Measure execution time using Big-O notation Space Complexity โ†’ Measure memory usage Big-O Notation โ†’ O(1), O(n), O(log n), O(nยฒ) Recursion Basics โ†’ Function calling itself PROGRAMMING BASICS Variables โ†’ Store data Data Types โ†’ int, float, string, boolean Control Structures โ†’ if/else, switch Loops โ†’ for, while, do-while Functions โ†’ Reusable blocks of code Input/Output โ†’ Handling user data ARRAYS Basics โ†’ Store elements in contiguous memory Traversal โ†’ Access elements sequentially Insertion โ†’ Add elements at index Deletion โ†’ Remove elements Searching โ†’ Linear Search, Binary Search Two Pointers โ†’ Optimize array problems Sliding Window โ†’ Efficient subarray problems STRINGS String Basics โ†’ Sequence of characters Manipulation โ†’ Concatenation, slicing Pattern Matching โ†’ KMP Algorithm Palindrome Problems โ†’ Reverse & compare Anagrams โ†’ Frequency counting String Hashing โ†’ Efficient comparisons LINKED LISTS Types โ†’ Singly, Doubly, Circular Traversal โ†’ Move through nodes Insertion โ†’ Beginning, middle, end Deletion โ†’ Remove nodes Reversal โ†’ Reverse linked list Cycle Detection โ†’ Floydโ€™s Cycle Algorithm STACKS LIFO Principle โ†’ Last In First Out Operations โ†’ push, pop, peek Applications โ†’ โ†’ Expression evaluation โ†’ Parentheses matching โ†’ Undo/Redo systems QUEUES FIFO Principle โ†’ First In First Out Types โ†’ Simple Queue, Circular Queue, Deque, Priority Queue Operations โ†’ enqueue, dequeue Applications โ†’ Scheduling, buffering HASHING Hash Tables โ†’ Key-value storage Hash Functions โ†’ Map keys to indices Collision Handling โ†’ Chaining, Open Addressing Applications โ†’ Fast lookup, caching TREES Binary Tree โ†’ Hierarchical structure Binary Search Tree (BST) โ†’ Ordered tree Traversals โ†’ โ†’ Inorder โ†’ Left, Root, Right โ†’ Preorder โ†’ Root, Left, Right โ†’ Postorder โ†’ Left, Right, Root Heap โ†’ Min Heap, Max Heap Trie โ†’ Efficient string storage GRAPHS Representation โ†’ Adjacency List, Matrix Traversal โ†’ โ†’ BFS (Breadth-First Search) โ†’ DFS (Depth-First Search) Shortest Path โ†’ Dijkstra, Bellman-Ford Minimum Spanning Tree โ†’ Primโ€™s, Kruskalโ€™s Topological Sorting โ†’ Directed graphs ALGORITHMIC TECHNIQUES Recursion โ†’ Divide problems into subproblems Backtracking โ†’ Try all possibilities (e.g., N-Queens) Greedy Algorithms โ†’ Local optimal choices Divide & Conquer โ†’ Break into smaller parts (Merge Sort) Dynamic Programming โ†’ Store results to avoid recomputation SORTING ALGORITHMS Bubble Sort โ†’ Simple but inefficient Selection Sort โ†’ Select minimum element Insertion Sort โ†’ Build sorted array Merge Sort โ†’ Divide & conquer Quick Sort โ†’ Partition-based sorting Heap Sort โ†’ Use heap structure SEARCHING ALGORITHMS Linear Search โ†’ Check each element Binary Search โ†’ Divide search space Advanced Searching โ†’ Ternary search ADVANCED TOPICS Segment Trees โ†’ Range queries Fenwick Tree (BIT) โ†’ Efficient updates Disjoint Set (Union-Find) โ†’ Connected components Bit Manipulation โ†’ Optimize computations Matrix Algorithms โ†’ Grid-based problems PROBLEM-SOLVING STRATEGY Understand Problem โ†’ Clarify requirements Brute Force โ†’ Start simple Optimize โ†’ Improve time/space complexity Dry Run โ†’ Test with examples Edge Cases โ†’ Handle all scenarios Practice โ†’ Consistency is key PLATFORMS TO PRACTICE LeetCode โ†’ Interview-focused problems Codeforces โ†’ Competitive programming HackerRank โ†’ Beginner to advanced GeeksforGeeks โ†’ Tutorials + problems QUICK LEARNING PATH Learn Basics โ†’ Programming + Big-O Master Core DS โ†’ Arrays, Strings, Linked Lists Learn Trees & Graphs โ†’ Advanced structures Practice Algorithms โ†’ Sorting, Searching, DP Solve Problems Daily โ†’ Build consistency Prepare for Interviews โ†’ Mock tests & challenges Grab the DSA EBOOK: https://t.co/Y2uMlOqQZl
e_opore's tweet photo. DATA STRUCTURES & ALGORITHMS (DSA) ROADMAP FOUNDATIONS What is DSA โ†’ Study of organizing data and solving problems efficiently Why DSA โ†’ Improves problem-solving and coding interview performance Time Complexity โ†’ Measure execution time using Big-O notation Space Complexity โ†’ Measure memory usage Big-O Notation โ†’ O(1), O(n), O(log n), O(nยฒ) Recursion Basics โ†’ Function calling itself PROGRAMMING BASICS Variables โ†’ Store data Data Types โ†’ int, float, string, boolean Control Structures โ†’ if/else, switch Loops โ†’ for, while, do-while Functions โ†’ Reusable blocks of code Input/Output โ†’ Handling user data ARRAYS Basics โ†’ Store elements in contiguous memory Traversal โ†’ Access elements sequentially Insertion โ†’ Add elements at index Deletion โ†’ Remove elements Searching โ†’ Linear Search, Binary Search Two Pointers โ†’ Optimize array problems Sliding Window โ†’ Efficient subarray problems STRINGS String Basics โ†’ Sequence of characters Manipulation โ†’ Concatenation, slicing Pattern Matching โ†’ KMP Algorithm Palindrome Problems โ†’ Reverse & compare Anagrams โ†’ Frequency counting String Hashing โ†’ Efficient comparisons LINKED LISTS Types โ†’ Singly, Doubly, Circular Traversal โ†’ Move through nodes Insertion โ†’ Beginning, middle, end Deletion โ†’ Remove nodes Reversal โ†’ Reverse linked list Cycle Detection โ†’ Floydโ€™s Cycle Algorithm STACKS LIFO Principle โ†’ Last In First Out Operations โ†’ push, pop, peek Applications โ†’ โ†’ Expression evaluation โ†’ Parentheses matching โ†’ Undo/Redo systems QUEUES FIFO Principle โ†’ First In First Out Types โ†’ Simple Queue, Circular Queue, Deque, Priority Queue Operations โ†’ enqueue, dequeue Applications โ†’ Scheduling, buffering HASHING Hash Tables โ†’ Key-value storage Hash Functions โ†’ Map keys to indices Collision Handling โ†’ Chaining, Open Addressing Applications โ†’ Fast lookup, caching TREES Binary Tree โ†’ Hierarchical structure Binary Search Tree (BST) โ†’ Ordered tree Traversals โ†’ โ†’ Inorder โ†’ Left, Root, Right โ†’ Preorder โ†’ Root, Left, Right โ†’ Postorder โ†’ Left, Right, Root Heap โ†’ Min Heap, Max Heap Trie โ†’ Efficient string storage GRAPHS Representation โ†’ Adjacency List, Matrix Traversal โ†’ โ†’ BFS (Breadth-First Search) โ†’ DFS (Depth-First Search) Shortest Path โ†’ Dijkstra, Bellman-Ford Minimum Spanning Tree โ†’ Primโ€™s, Kruskalโ€™s Topological Sorting โ†’ Directed graphs ALGORITHMIC TECHNIQUES Recursion โ†’ Divide problems into subproblems Backtracking โ†’ Try all possibilities (e.g., N-Queens) Greedy Algorithms โ†’ Local optimal choices Divide & Conquer โ†’ Break into smaller parts (Merge Sort) Dynamic Programming โ†’ Store results to avoid recomputation SORTING ALGORITHMS Bubble Sort โ†’ Simple but inefficient Selection Sort โ†’ Select minimum element Insertion Sort โ†’ Build sorted array Merge Sort โ†’ Divide & conquer Quick Sort โ†’ Partition-based sorting Heap Sort โ†’ Use heap structure SEARCHING ALGORITHMS Linear Search โ†’ Check each element Binary Search โ†’ Divide search space Advanced Searching โ†’ Ternary search ADVANCED TOPICS Segment Trees โ†’ Range queries Fenwick Tree (BIT) โ†’ Efficient updates Disjoint Set (Union-Find) โ†’ Connected components Bit Manipulation โ†’ Optimize computations Matrix Algorithms โ†’ Grid-based problems PROBLEM-SOLVING STRATEGY Understand Problem โ†’ Clarify requirements Brute Force โ†’ Start simple Optimize โ†’ Improve time/space complexity Dry Run โ†’ Test with examples Edge Cases โ†’ Handle all scenarios Practice โ†’ Consistency is key PLATFORMS TO PRACTICE LeetCode โ†’ Interview-focused problems Codeforces โ†’ Competitive programming HackerRank โ†’ Beginner to advanced GeeksforGeeks โ†’ Tutorials + problems QUICK LEARNING PATH Learn Basics โ†’ Programming + Big-O Master Core DS โ†’ Arrays, Strings, Linked Lists Learn Trees & Graphs โ†’ Advanced structures Practice Algorithms โ†’ Sorting, Searching, DP Solve Problems Daily โ†’ Build consistency Prepare for Interviews โ†’ Mock tests & challenges Grab the DSA EBOOK: https://t.co/Y2uMlOqQZl
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aravind_mutthe ย retweeted
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Dhanian ๐Ÿ—ฏ๏ธ Verified account @e_opore
If I had to start with Java, Iโ€™d learn these concepts: 1. Java Basics 2. JVM, JRE, JDK 3. Data Types 4. Variables 5. Operators 6. Control Flow (if, switch) 7. Loops (for, while, do-while) 8. Methods 9. Arrays 10. Strings 11. Object-Oriented Programming (OOP) 12. Classes & Objects 13. Constructors 14. Encapsulation 15. Inheritance 16. Polymorphism 17. Abstraction 18. Interfaces 19. Abstract Classes 20. Packages 21. Access Modifiers 22. Static Keyword 23. Final Keyword 24. This & Super 25. Method Overloading 26. Method Overriding 27. Exception Handling 28. Try-Catch-Finally 29. Custom Exceptions 30. Collections Framework 31. List, Set, Map 32. ArrayList 33. HashSet 34. HashMap 35. Iterators 36. Comparable & Comparator 37. Generics 38. Enums 39. Annotations 40. Lambda Expressions 41. Functional Interfaces 42. Streams API 43. Optional 44. Date & Time API 45. File Handling 46. NIO 47. Serialization 48. Deserialization 49. Multithreading 50. Thread Lifecycle 51. Synchronization 52. Concurrency Utilities 53. Executors & Thread Pools 54. Locks & Atomic Variables 55. Parallel Streams 56. Reflection API 57. JDBC 58. Database Connectivity 59. Connection Pooling 60. SQL Integration 61. Build Tools (Maven, Gradle) 62. Dependency Management 63. Logging (Log4j, SLF4J) 64. Testing (JUnit, Mockito) 65. Debugging 66. Performance Tuning 67. Garbage Collection 68. Memory Management 69. JVM Internals 70. Spring Framework 71. Spring Boot 72. REST APIs with Spring 73. Dependency Injection 74. Aspect-Oriented Programming (AOP) 75. Spring Data JPA 76. Hibernate ORM 77. Microservices with Spring 78. API Security (Spring Security) 79. OAuth & JWT 80. Docker with Java 81. Kubernetes Deployment 82. CI/CD for Java Apps 83. Cloud Deployment (AWS, Azure) 84. Reactive Programming (WebFlux) 85. Event-Driven Systems 86. Message Brokers (Kafka, RabbitMQ) 87. Distributed Systems Basics 88. Caching (Redis, Ehcache) 89. Search (Elasticsearch) 90. Monitoring (Prometheus, Grafana) 91. Observability 92. Logging & Tracing 93. API Gateway 94. Service Discovery 95. Circuit Breaker (Resilience4j) 96. Scalability 97. High Availability 98. System Design with Java (...and more concepts) === ๐Ÿ‘‹ PS - Want a complete Java roadmap from beginner to advanced? Read right now: โ†’ Java Ebook: https://t.co/STSI0ZDYpa === ๐Ÿ’พ Save this for later & RT to help others learn Java. ๐Ÿ‘ค Follow @e_opore + turn on notifications.
e_opore's tweet photo. If I had to start with Java, Iโ€™d learn these concepts: 1. Java Basics 2. JVM, JRE, JDK 3. Data Types 4. Variables 5. Operators 6. Control Flow (if, switch) 7. Loops (for, while, do-while) 8. Methods 9. Arrays 10. Strings 11. Object-Oriented Programming (OOP) 12. Classes & Objects 13. Constructors 14. Encapsulation 15. Inheritance 16. Polymorphism 17. Abstraction 18. Interfaces 19. Abstract Classes 20. Packages 21. Access Modifiers 22. Static Keyword 23. Final Keyword 24. This & Super 25. Method Overloading 26. Method Overriding 27. Exception Handling 28. Try-Catch-Finally 29. Custom Exceptions 30. Collections Framework 31. List, Set, Map 32. ArrayList 33. HashSet 34. HashMap 35. Iterators 36. Comparable & Comparator 37. Generics 38. Enums 39. Annotations 40. Lambda Expressions 41. Functional Interfaces 42. Streams API 43. Optional 44. Date & Time API 45. File Handling 46. NIO 47. Serialization 48. Deserialization 49. Multithreading 50. Thread Lifecycle 51. Synchronization 52. Concurrency Utilities 53. Executors & Thread Pools 54. Locks & Atomic Variables 55. Parallel Streams 56. Reflection API 57. JDBC 58. Database Connectivity 59. Connection Pooling 60. SQL Integration 61. Build Tools (Maven, Gradle) 62. Dependency Management 63. Logging (Log4j, SLF4J) 64. Testing (JUnit, Mockito) 65. Debugging 66. Performance Tuning 67. Garbage Collection 68. Memory Management 69. JVM Internals 70. Spring Framework 71. Spring Boot 72. REST APIs with Spring 73. Dependency Injection 74. Aspect-Oriented Programming (AOP) 75. Spring Data JPA 76. Hibernate ORM 77. Microservices with Spring 78. API Security (Spring Security) 79. OAuth & JWT 80. Docker with Java 81. Kubernetes Deployment 82. CI/CD for Java Apps 83. Cloud Deployment (AWS, Azure) 84. Reactive Programming (WebFlux) 85. Event-Driven Systems 86. Message Brokers (Kafka, RabbitMQ) 87. Distributed Systems Basics 88. Caching (Redis, Ehcache) 89. Search (Elasticsearch) 90. Monitoring (Prometheus, Grafana) 91. Observability 92. Logging & Tracing 93. API Gateway 94. Service Discovery 95. Circuit Breaker (Resilience4j) 96. Scalability 97. High Availability 98. System Design with Java (...and more concepts) === ๐Ÿ‘‹ PS - Want a complete Java roadmap from beginner to advanced? Read right now: โ†’ Java Ebook: https://t.co/STSI0ZDYpa === ๐Ÿ’พ Save this for later & RT to help others learn Java. ๐Ÿ‘ค Follow @e_opore + turn on notifications.
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aravind_mutthe ย retweeted
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AsyncTrix Verified account @asynctrix
๐ŸŒ Networking Concepts - Difficulty Breakdown ๐Ÿ”ฅ โ€ข ๐ŸŒ IP Addressing -> ๐ŸŸข Easy โ€ข ๐Ÿ”Œ Ports -> ๐ŸŸข Easy โ€ข ๐Ÿ“ก DNS -> ๐ŸŸข Easy โ€ข ๐Ÿ”„ HTTP / HTTPS -> ๐ŸŸข Easy โ€ข ๐ŸŒ TCP vs UDP -> ๐ŸŸก Easyโ€“Medium โ€ข ๐Ÿ”€ Load Balancing -> ๐ŸŸก Easyโ€“Medium โ€ข ๐Ÿงฑ Subnets -> ๐ŸŸก Easyโ€“Medium โ€ข ๐Ÿ”’ SSL/TLS -> ๐ŸŸก Easyโ€“Medium โ€ข ๐Ÿ“ฆ NAT -> ๐ŸŸ  Medium โ€ข ๐Ÿ” Routing -> ๐ŸŸ  Medium โ€ข ๐Ÿง  CIDR -> ๐ŸŸ  Medium โ€ข ๐ŸŒ‰ VPN -> ๐ŸŸ  Medium โ€ข ๐Ÿ”ฅ Firewalls (stateful/stateless) -> ๐Ÿ”ด Hard โ€ข ๐Ÿ“ก BGP -> ๐Ÿ”ด Hard โ€ข โš™๏ธ Network protocols deep dive -> ๐Ÿ”ด Hard โ€ข ๐Ÿงฌ Distributed networking -> ๐ŸŸฃ Very Hard โ€ข โš™๏ธ Designing global networks -> โ˜ ๏ธ Extreme Feel Free to Add ๐Ÿ‘‡
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aravind_mutthe ย retweeted
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Nandkishor Verified account @devops_nk
Linux (OS, shell, processes) โ†“ Networking (DNS, TCP/IP, HTTP, NAT) โ†“ Git & GitHub (version control, PRs) โ†“ AWS (EC2, IAM, VPC, S3) โ†“ Docker (containers, images) โ†“ Kubernetes (pods, services, scaling) โ†“ CI/CD (Jenkins, GitHub Actions) โ†“ IAC (Terraform, CFN) โ†“ Automation (Ansible, Bash) โ†“ Monitoring & Observability (Prometheus / Grafana) โ†“ Security Basics (IAM, secrets) โ†“ SRE (SLI, SLO, SLA) โ†“ Python (scripting, automation) Congrats ๐ŸŽ‰ Youโ€™re DevOps-Engineer now. ๐Ÿ’ฌ Add missing tools in comments.
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aravind_mutthe ย retweeted
e_opore's profile image
Dhanian ๐Ÿ—ฏ๏ธ Verified account @e_opore
๐Ÿ“‚ Kubernetes Roadmap โ”ƒ โ”ฃ ๐Ÿ“‚ Foundations โ”ƒ โ”ฃ ๐Ÿ“‚ Linux Basics (Processes, Networking, File System) โ”ƒ โ”ฃ ๐Ÿ“‚ Networking Fundamentals (TCP/IP, DNS, HTTP/HTTPS) โ”ƒ โ”ฃ ๐Ÿ“‚ Containers vs Virtual Machines โ”ƒ โ”ฃ ๐Ÿ“‚ Docker Fundamentals (Images, Containers, Volumes) โ”ƒ โ”— ๐Ÿ“‚ YAML & Configuration Files โ”ƒ โ”ฃ ๐Ÿ“‚ Core Kubernetes Concepts โ”ƒ โ”ฃ ๐Ÿ“‚ Kubernetes Architecture (Master & Worker Nodes) โ”ƒ โ”ฃ ๐Ÿ“‚ Pods (Smallest Deployable Units) โ”ƒ โ”ฃ ๐Ÿ“‚ Labels, Selectors & Annotations โ”ƒ โ”ฃ ๐Ÿ“‚ Namespaces โ”ƒ โ”— ๐Ÿ“‚ kubectl CLI Basics โ”ƒ โ”ฃ ๐Ÿ“‚ Workloads & Controllers โ”ƒ โ”ฃ ๐Ÿ“‚ Deployments โ”ƒ โ”ฃ ๐Ÿ“‚ ReplicaSets โ”ƒ โ”ฃ ๐Ÿ“‚ StatefulSets โ”ƒ โ”ฃ ๐Ÿ“‚ DaemonSets โ”ƒ โ”— ๐Ÿ“‚ Jobs & CronJobs โ”ƒ โ”ฃ ๐Ÿ“‚ Networking in Kubernetes โ”ƒ โ”ฃ ๐Ÿ“‚ Services (ClusterIP, NodePort, LoadBalancer) โ”ƒ โ”ฃ ๐Ÿ“‚ Ingress Controllers โ”ƒ โ”ฃ ๐Ÿ“‚ DNS in Kubernetes โ”ƒ โ”ฃ ๐Ÿ“‚ Network Policies โ”ƒ โ”— ๐Ÿ“‚ Service Discovery โ”ƒ โ”ฃ ๐Ÿ“‚ Storage & Persistence โ”ƒ โ”ฃ ๐Ÿ“‚ Volumes โ”ƒ โ”ฃ ๐Ÿ“‚ Persistent Volumes (PV) โ”ƒ โ”ฃ ๐Ÿ“‚ Persistent Volume Claims (PVC) โ”ƒ โ”ฃ ๐Ÿ“‚ Storage Classes โ”ƒ โ”— ๐Ÿ“‚ Stateful Application Storage โ”ƒ โ”ฃ ๐Ÿ“‚ Configuration & Secrets โ”ƒ โ”ฃ ๐Ÿ“‚ ConfigMaps โ”ƒ โ”ฃ ๐Ÿ“‚ Secrets Management โ”ƒ โ”ฃ ๐Ÿ“‚ Environment Variables โ”ƒ โ”— ๐Ÿ“‚ Secure Configuration Practices โ”ƒ โ”ฃ ๐Ÿ“‚ Security โ”ƒ โ”ฃ ๐Ÿ“‚ RBAC (Role-Based Access Control) โ”ƒ โ”ฃ ๐Ÿ“‚ Authentication & Authorization โ”ƒ โ”ฃ ๐Ÿ“‚ Pod Security Standards โ”ƒ โ”ฃ ๐Ÿ“‚ Network Security โ”ƒ โ”— ๐Ÿ“‚ Secrets Encryption โ”ƒ โ”ฃ ๐Ÿ“‚ Observability & Monitoring โ”ƒ โ”ฃ ๐Ÿ“‚ Logging (ELK Stack) โ”ƒ โ”ฃ ๐Ÿ“‚ Metrics (Prometheus) โ”ƒ โ”ฃ ๐Ÿ“‚ Visualization (Grafana) โ”ƒ โ”ฃ ๐Ÿ“‚ Alerts & Health Checks โ”ƒ โ”— ๐Ÿ“‚ Debugging Pods โ”ƒ โ”ฃ ๐Ÿ“‚ Scaling & Performance โ”ƒ โ”ฃ ๐Ÿ“‚ Horizontal Pod Autoscaler (HPA) โ”ƒ โ”ฃ ๐Ÿ“‚ Vertical Pod Autoscaler (VPA) โ”ƒ โ”ฃ ๐Ÿ“‚ Cluster Autoscaling โ”ƒ โ”ฃ ๐Ÿ“‚ Resource Requests & Limits โ”ƒ โ”— ๐Ÿ“‚ Performance Optimization โ”ƒ โ”ฃ ๐Ÿ“‚ Advanced Concepts โ”ƒ โ”ฃ ๐Ÿ“‚ Helm (Package Manager) โ”ƒ โ”ฃ ๐Ÿ“‚ Operators & CRDs โ”ƒ โ”ฃ ๐Ÿ“‚ Service Mesh (Istio, Linkerd) โ”ƒ โ”ฃ ๐Ÿ“‚ Multi-Cluster Management โ”ƒ โ”— ๐Ÿ“‚ GitOps (ArgoCD, Flux) โ”ƒ โ”ฃ ๐Ÿ“‚ Cloud & Managed Kubernetes โ”ƒ โ”ฃ ๐Ÿ“‚ AWS EKS โ”ƒ โ”ฃ ๐Ÿ“‚ Google GKE โ”ƒ โ”ฃ ๐Ÿ“‚ Azure AKS โ”ƒ โ”ฃ ๐Ÿ“‚ Vercel / Edge Deployments โ”ƒ โ”— ๐Ÿ“‚ Hybrid & On-Prem Clusters โ”ƒ โ”ฃ ๐Ÿ“‚ Real-World Projects โ”ƒ โ”ฃ ๐Ÿ“‚ Deploy a Microservices App โ”ƒ โ”ฃ ๐Ÿ“‚ CI/CD Pipeline with Kubernetes โ”ƒ โ”ฃ ๐Ÿ“‚ Scalable Web Application โ”ƒ โ”ฃ ๐Ÿ“‚ Monitoring Stack Setup โ”ƒ โ”— ๐Ÿ“‚ Multi-Service SaaS Deployment โ”ƒ โ”ฃ ๐Ÿ“‚ Practice & Growth โ”ƒ โ”ฃ ๐Ÿ“‚ Hands-on Labs (Minikube, Kind) โ”ƒ โ”ฃ ๐Ÿ“‚ Contribute to Open Source โ”ƒ โ”ฃ ๐Ÿ“‚ Kubernetes Certifications (CKA, CKAD) โ”ƒ โ”ฃ ๐Ÿ“‚ Build Production-Ready Projects โ”ƒ โ”— ๐Ÿ“‚ Troubleshooting Scenarios โ”ƒ โ”— ๐Ÿ“‚ Career & Monetization โ”ฃ ๐Ÿ“‚ DevOps Engineer Roles โ”ฃ ๐Ÿ“‚ Cloud Engineer Roles โ”ฃ ๐Ÿ“‚ Freelancing & Consulting โ”ฃ ๐Ÿ“‚ SaaS Infrastructure โ”— ๐Ÿ“‚ Continuous Learning Follow this consistently for 3โ€“5 months and youโ€™ll master Kubernetes and cloud-native engineering Grab the KUBERNETES HANDBOOK: https://t.co/1JQaCCc17i
e_opore's tweet photo. ๐Ÿ“‚ Kubernetes Roadmap โ”ƒ โ”ฃ ๐Ÿ“‚ Foundations โ”ƒ โ”ฃ ๐Ÿ“‚ Linux Basics (Processes, Networking, File System) โ”ƒ โ”ฃ ๐Ÿ“‚ Networking Fundamentals (TCP/IP, DNS, HTTP/HTTPS) โ”ƒ โ”ฃ ๐Ÿ“‚ Containers vs Virtual Machines โ”ƒ โ”ฃ ๐Ÿ“‚ Docker Fundamentals (Images, Containers, Volumes) โ”ƒ โ”— ๐Ÿ“‚ YAML & Configuration Files โ”ƒ โ”ฃ ๐Ÿ“‚ Core Kubernetes Concepts โ”ƒ โ”ฃ ๐Ÿ“‚ Kubernetes Architecture (Master & Worker Nodes) โ”ƒ โ”ฃ ๐Ÿ“‚ Pods (Smallest Deployable Units) โ”ƒ โ”ฃ ๐Ÿ“‚ Labels, Selectors & Annotations โ”ƒ โ”ฃ ๐Ÿ“‚ Namespaces โ”ƒ โ”— ๐Ÿ“‚ kubectl CLI Basics โ”ƒ โ”ฃ ๐Ÿ“‚ Workloads & Controllers โ”ƒ โ”ฃ ๐Ÿ“‚ Deployments โ”ƒ โ”ฃ ๐Ÿ“‚ ReplicaSets โ”ƒ โ”ฃ ๐Ÿ“‚ StatefulSets โ”ƒ โ”ฃ ๐Ÿ“‚ DaemonSets โ”ƒ โ”— ๐Ÿ“‚ Jobs & CronJobs โ”ƒ โ”ฃ ๐Ÿ“‚ Networking in Kubernetes โ”ƒ โ”ฃ ๐Ÿ“‚ Services (ClusterIP, NodePort, LoadBalancer) โ”ƒ โ”ฃ ๐Ÿ“‚ Ingress Controllers โ”ƒ โ”ฃ ๐Ÿ“‚ DNS in Kubernetes โ”ƒ โ”ฃ ๐Ÿ“‚ Network Policies โ”ƒ โ”— ๐Ÿ“‚ Service Discovery โ”ƒ โ”ฃ ๐Ÿ“‚ Storage & Persistence โ”ƒ โ”ฃ ๐Ÿ“‚ Volumes โ”ƒ โ”ฃ ๐Ÿ“‚ Persistent Volumes (PV) โ”ƒ โ”ฃ ๐Ÿ“‚ Persistent Volume Claims (PVC) โ”ƒ โ”ฃ ๐Ÿ“‚ Storage Classes โ”ƒ โ”— ๐Ÿ“‚ Stateful Application Storage โ”ƒ โ”ฃ ๐Ÿ“‚ Configuration & Secrets โ”ƒ โ”ฃ ๐Ÿ“‚ ConfigMaps โ”ƒ โ”ฃ ๐Ÿ“‚ Secrets Management โ”ƒ โ”ฃ ๐Ÿ“‚ Environment Variables โ”ƒ โ”— ๐Ÿ“‚ Secure Configuration Practices โ”ƒ โ”ฃ ๐Ÿ“‚ Security โ”ƒ โ”ฃ ๐Ÿ“‚ RBAC (Role-Based Access Control) โ”ƒ โ”ฃ ๐Ÿ“‚ Authentication & Authorization โ”ƒ โ”ฃ ๐Ÿ“‚ Pod Security Standards โ”ƒ โ”ฃ ๐Ÿ“‚ Network Security โ”ƒ โ”— ๐Ÿ“‚ Secrets Encryption โ”ƒ โ”ฃ ๐Ÿ“‚ Observability & Monitoring โ”ƒ โ”ฃ ๐Ÿ“‚ Logging (ELK Stack) โ”ƒ โ”ฃ ๐Ÿ“‚ Metrics (Prometheus) โ”ƒ โ”ฃ ๐Ÿ“‚ Visualization (Grafana) โ”ƒ โ”ฃ ๐Ÿ“‚ Alerts & Health Checks โ”ƒ โ”— ๐Ÿ“‚ Debugging Pods โ”ƒ โ”ฃ ๐Ÿ“‚ Scaling & Performance โ”ƒ โ”ฃ ๐Ÿ“‚ Horizontal Pod Autoscaler (HPA) โ”ƒ โ”ฃ ๐Ÿ“‚ Vertical Pod Autoscaler (VPA) โ”ƒ โ”ฃ ๐Ÿ“‚ Cluster Autoscaling โ”ƒ โ”ฃ ๐Ÿ“‚ Resource Requests & Limits โ”ƒ โ”— ๐Ÿ“‚ Performance Optimization โ”ƒ โ”ฃ ๐Ÿ“‚ Advanced Concepts โ”ƒ โ”ฃ ๐Ÿ“‚ Helm (Package Manager) โ”ƒ โ”ฃ ๐Ÿ“‚ Operators & CRDs โ”ƒ โ”ฃ ๐Ÿ“‚ Service Mesh (Istio, Linkerd) โ”ƒ โ”ฃ ๐Ÿ“‚ Multi-Cluster Management โ”ƒ โ”— ๐Ÿ“‚ GitOps (ArgoCD, Flux) โ”ƒ โ”ฃ ๐Ÿ“‚ Cloud & Managed Kubernetes โ”ƒ โ”ฃ ๐Ÿ“‚ AWS EKS โ”ƒ โ”ฃ ๐Ÿ“‚ Google GKE โ”ƒ โ”ฃ ๐Ÿ“‚ Azure AKS โ”ƒ โ”ฃ ๐Ÿ“‚ Vercel / Edge Deployments โ”ƒ โ”— ๐Ÿ“‚ Hybrid & On-Prem Clusters โ”ƒ โ”ฃ ๐Ÿ“‚ Real-World Projects โ”ƒ โ”ฃ ๐Ÿ“‚ Deploy a Microservices App โ”ƒ โ”ฃ ๐Ÿ“‚ CI/CD Pipeline with Kubernetes โ”ƒ โ”ฃ ๐Ÿ“‚ Scalable Web Application โ”ƒ โ”ฃ ๐Ÿ“‚ Monitoring Stack Setup โ”ƒ โ”— ๐Ÿ“‚ Multi-Service SaaS Deployment โ”ƒ โ”ฃ ๐Ÿ“‚ Practice & Growth โ”ƒ โ”ฃ ๐Ÿ“‚ Hands-on Labs (Minikube, Kind) โ”ƒ โ”ฃ ๐Ÿ“‚ Contribute to Open Source โ”ƒ โ”ฃ ๐Ÿ“‚ Kubernetes Certifications (CKA, CKAD) โ”ƒ โ”ฃ ๐Ÿ“‚ Build Production-Ready Projects โ”ƒ โ”— ๐Ÿ“‚ Troubleshooting Scenarios โ”ƒ โ”— ๐Ÿ“‚ Career & Monetization โ”ฃ ๐Ÿ“‚ DevOps Engineer Roles โ”ฃ ๐Ÿ“‚ Cloud Engineer Roles โ”ฃ ๐Ÿ“‚ Freelancing & Consulting โ”ฃ ๐Ÿ“‚ SaaS Infrastructure โ”— ๐Ÿ“‚ Continuous Learning Follow this consistently for 3โ€“5 months and youโ€™ll master Kubernetes and cloud-native engineering Grab the KUBERNETES HANDBOOK: https://t.co/1JQaCCc17i
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aravind_mutthe ย retweeted
techyoutbe's profile image
Tech Fusionist Verified account @techyoutbe
20 Protocols Every Cloud, DevOps & AI Engineer Should Know โšก If you understand these protocols, you understand how systems actually talk. 1.HTTP โ€” web communication 2.HTTPS โ€” encrypted web traffic 3.TCP โ€” reliable packet delivery 4.UDP โ€” fast, lightweight transport 5.IP โ€” device addressing and routing 6.DNS โ€” translates names to IPs 7.SSH โ€” secure remote access 8.FTP/SFTP โ€” file transfers 9.SMTP โ€” sending emails 10.IMAP โ€” retrieving emails Now the cloud/devops stack ๐Ÿ‘‡ 11.TLS โ€” encryption and certificate trust 12.BGP โ€” internet and cloud route exchange 13.ARP โ€” maps IP to MAC addresses 14.ICMP โ€” ping, diagnostics, reachability 15.DHCP โ€” automatic IP assignment 16.NFS โ€” shared network storage 17.SMB โ€” network file sharing 18.LDAP โ€” identity and directory auth 19.gRPC โ€” high-performance service-to-service communication 20.MQTT โ€” lightweight messaging for IoT/AI edge systems Bonus if you work with Kubernetes: 21.VXLAN โ€” overlay networking 22.BGP (yes again) โ€” used by MetalLB and CNI designs 23.eBPF โ€” modern packet processing magic 24.Raft โ€” powers distributed consensus (think etcd)
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aravind_mutthe ย retweeted
techyoutbe's profile image
Tech Fusionist Verified account @techyoutbe
Kubernetes - Visual Explanation ๐Ÿ”ฅ๐Ÿ”ฅ
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aravind_mutthe ย retweeted
devXritesh's profile image
Ritesh Roushan Verified account @devXritesh
As a backend engineer, Please learn: System design fundamentals (scalability, availability, trade-offs) Databases deep dive (indexing, transactions, sharding, replication) API design & contracts (REST, gRPC, versioning, idempotency) Async systems (queues, event-driven architecture, backpressure) Caching strategies (Redis, CDN, cache invalidation) Concurrency & consistency (race conditions, locking, isolation levels) Reliability patterns (retries, circuit breakers, rate limiting) Observability (logging, metrics, distributed tracing) Performance tuning (latency, throughput, bottleneck analysis) All very important topics.
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aravind_mutthe ย retweeted
yourclouddude's profile image
yourclouddude Verified account @yourclouddude
If I had to start AWS from scratch in 2026, Iโ€™d follow this exact 12-week plan: Week 1โ€“2 โ†’ Foundations Linux โ€ข Networking โ€ข Git โ€ข Python basics Week 2โ€“3 โ†’ Cloud Fundamentals Regions โ€ข AZs โ€ข Pricing IaaS vs PaaS vs SaaS Week 3โ€“6 โ†’ Core AWS EC2 โ€ข S3 โ€ข IAM โ€ข RDS Lambda โ€ข VPC โ€ข CloudWatch (learn what they do + when to use) Week 6โ€“8 โ†’ How AWS actually works EC2 โ†” RDS S3 โ†” CloudFront Lambda โ†” API Gateway VPC โ†” everything (this is where you level up) Week 8โ€“10 โ†’ Build Projects โ€ข Static website (S3 + CloudFront) โ€ข App deployment (EC2 + RDS) โ€ข Serverless API โ€ข Monitoring setup Week 10โ€“11 โ†’ Security Basics IAM โ€ข least privilege โ€ข encryption Week 11โ€“12 โ†’ Deployment SSH โ€ข environment setup CI/CD (GitHub Actions) Week 12 โ†’ Portfolio GitHub + simple case studies (Optional) Cert Path CLF โ†’ SAA Final Step โ†’ Apply Cloud โ€ข DevOps โ€ข AWS support roles This isnโ€™t about learning AWS. Itโ€™s about getting hired. โ˜๏ธ
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aravind_mutthe ย retweeted
yourclouddude's profile image
yourclouddude Verified account @yourclouddude
If you want to become a Cloud Engineer, master these 10 skills โ˜๏ธ โ‘  Linux โ†’ live in the terminal โ‘ก Networking โ†’ VPC, subnets, routing โ‘ข Compute โ†’ EC2, scaling, load balancing โ‘ฃ Storage โ†’ S3, EBS, EFS โ‘ค IAM โ†’ roles, policies, security โ‘ฅ Databases โ†’ RDS, DynamoDB basics โ‘ฆ Serverless โ†’ Lambda + APIs โ‘ง Monitoring โ†’ CloudWatch, logs, alerts โ‘จ Automation โ†’ CLI, Terraform, scripting โ‘ฉ Projects โ†’ real cloud architectures Thatโ€™s it. Not 200 services. Not everything. ๐Ÿ“Œ Cloud Engineers donโ€™t memorize. They build and connect systems.
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aravind_mutthe ย retweeted
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Edison Verified account @CodeEdison
Databases vs Servers most beginners mix these up. Here is a thread to fix that. 1) A server and a database are NOT the same thing. They solve different problems but work together in every real app. 2) If you understand this difference, backend concepts like APIs, auth, and scaling start making sense. 3) What is a server? A server is a computer (or software on a computer) that receives requests and sends responses. 4) When your frontend sends a request like: โ€œGet user profileโ€ That request hits a server first not the database. 5) The serverโ€™s job: Handle requests Run business logic Validate data Decide what should happen next Think of it as the brain of the application. 6) What is a database? A database is a system designed to store, organize, and retrieve data efficiently. 7) Databases do NOT: Talk directly to the frontend Apply business rules Decide who is allowed to access data They just store and return data when asked. 8) Simple flow in a real app: User clicks button โ†’ Frontend sends request โ†’ Server processes logic โ†’ Server queries database โ†’ Database returns data โ†’ Server sends response โ†’ Frontend updates UI 9) Important rule: Frontend should NEVER talk directly to the database. Thatโ€™s a security and architecture disaster. 10) Why the server sits in the middle: Security (auth, permissions) Validation (clean data) Control (what data is exposed) 11) Analogy time: Server = waiter Database = kitchen storage Customers donโ€™t enter the kitchen. They talk to the waiter. 12) Common beginner mistake: โ€œI sent a request, so my database is my backend.โ€ No. Your server code is the backend. The database is just one part of it. 13) Examples: Server: Node.js, Spring Boot, Django Database: MySQL, PostgreSQL, MongoDB Different roles. Different responsibilities. 14) Mental model to remember: Servers decide. Databases store. 15) Once this clicks, APIs, authentication, and full-stack architecture become much easier. Follow for more beginner-friendly full-stack breakdowns.
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aravind_mutthe ย retweeted
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Ahmedkhan Verified account @Ahmed___khaan
Cybersecurity Engineer Roadmap in 2026 Stage 1 โ€“ Networking Basics Stage 2 โ€“ Linux & Security Tools Stage 3 โ€“ Firewalls & IDS/IPS Stage 4 โ€“ Ethical Hacking Basics Stage 5 โ€“ Web Security (OWASP Top 10) Stage 6 โ€“ Cryptography Stage 7 โ€“ Cloud Security (AWS, Azure) Stage 8 โ€“ Penetration Testing Tools (Metasploit, Burp) Stage 9 โ€“ Certifications (CEH, CISSP) ๐Ÿ† Cybersecurity Engineer
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aravind_mutthe ย retweeted
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Ahmedkhan Verified account @Ahmed___khaan
๐Ÿ—ƒ 40 Commonly Targeted Ports by Hackers:๐Ÿ‘จ๐Ÿฟโ€๐Ÿ’ป ย ย ย  ๐Ÿ”’ Port 21 (FTP) ย ย ย  ๐Ÿšช Port 22 (SSH) ย ย ย  ๐Ÿ’ป Port 23 (Telnet) ย ย ย  ๐Ÿ“ง Port 25 (SMTP) ย ย ย  ๐ŸŒ Port 53 (DNS) ย ย ย  ๐ŸŒ Port 80 (HTTP) ย ย ย  ๐Ÿ”’ Port 443 (HTTPS) ย ย ย  ๐ŸŽฎ Port 3074 (Xbox Live) ย ย ย  ๐Ÿ“ฒ Port 5060 (SIP) ๐ŸŽฒ Port 8080 (Proxy) ย ย ย  ๐Ÿ“ Port 135 (RPC) ย ย ย  ๐Ÿ–ฅ๏ธ Port 139 (NetBIOS) ย ย ย  ๐Ÿ”“ Port 1433 (MSSQL) ย ย ย  ๐ŸŽฒ Port 1521 (Oracle) ย ย ย  ๐Ÿ”“ Port 1723 (PPTP) ย ย ย  ๐Ÿ“ค Port 1900 (UPnP) ย ย ย  ๐ŸŽฎ Port 2302 (DayZ) ย ย ย  ๐Ÿ–จ๏ธ Port 3389 (RDP) ย ย ย  ๐Ÿ”’ Port 3306 (MySQL) ย ย ย  ๐Ÿ•ธ๏ธ Port 4000 (Elasticsearch) ๐Ÿ“‚ Port 4444 (Metasploit) ย ย ย  ๐Ÿ“ค Port 5000 (Python Flask) ย ย ย  ๐ŸŽฎ Port 5555 (Android Debug Bridge) ย ย ย  ๐Ÿ“ค Port 5900 (VNC) ย ย ย  ๐Ÿ–ฅ๏ธ Port 6667 (IRC) ย ย ย  ๐Ÿ“ง Port 6697 (IRC SSL) ย ย ย  ๐Ÿ“‚ Port 8000 (HTTP Alt) ย ย ย  ๐Ÿ–ฅ๏ธ Port 8081 (HTTP Proxy) ย ย ย  ๐Ÿ”“ Port 9100 (Printer) ๐Ÿ“‚ Port 27017 (MongoDB) ย ย ย  ๐ŸŒ Port 28017 (MongoDB HTTP Interface) ๐Ÿ“‚ Port 9090 (Web Debugging) ย ย ย  ๐Ÿ“ Port 445 (SMB) ย ย ย  ๐Ÿ’ป Ports 5985/5986 (WinRM) ย ย ย  ๐Ÿ”„ Port 6379 (Redis) ย ย ย  ๐Ÿ“‚ Port 6666 (IRC) ย ย ย  ๐Ÿ“ง Port 993 (IMAP SSL) ย ย ย  ๐Ÿ”’ Port 995 (POP3 SSL) ย ย ย  ๐ŸŽฒ Port 1434 (Microsoft SQL Monitor)
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aravind_mutthe ย retweeted
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๐—ฟ๐—ฎ๐—บ๐—ฎ๐—ธ๐—ฟ๐˜‚๐˜€๐—ต๐—ป๐—ฎโ€” ๐—ฒ/๐—ฎ๐—ฐ๐—ฐ Verified account @techwith_ram
This is the only article youโ€™ll need to build your own MCP server. It covers: > need of MCP > how MCP works > core concepts along with visualization > build your own mcp server > theory + coding
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aravind_mutthe ย retweeted
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Ayaan ๐Ÿง Verified account @twtayaan
๐Ÿ“‚ DevOps Engineer Roadmap โ”œโ”€ ๐Ÿ“‚ Foundations (START HERE) โ”‚ โ”œโ”€ ๐Ÿ“‚ Linux โญ FIRST โ”‚ โ”‚ โ”œโ”€ File system & permissions โ”‚ โ”‚ โ”œโ”€ Processes & signals โ”‚ โ”‚ โ”œโ”€ Systemd & services โ”‚ โ”‚ โ”œโ”€ Package managers โ”‚ โ”‚ โ””โ”€ Bash scripting โ”‚ โ”‚ โ”‚ โ”œโ”€ ๐Ÿ“‚ Networking โ”‚ โ”‚ โ”œโ”€ TCP/IP basics โ”‚ โ”‚ โ”œโ”€ DNS โ”‚ โ”‚ โ”œโ”€ HTTP / HTTPS โ”‚ โ”‚ โ”œโ”€ Load balancers โ”‚ โ”‚ โ”œโ”€ Reverse proxies โ”‚ โ”‚ โ””โ”€ Firewalls & ports โ”‚ โ”‚ โ”‚ โ”œโ”€ ๐Ÿ“‚ Git โ”‚ โ”‚ โ”œโ”€ Branching โ”‚ โ”‚ โ”œโ”€ Merge vs Rebase โ”‚ โ”‚ โ”œโ”€ Pull requests โ”‚ โ”‚ โ””โ”€ Git workflows โ”‚ โ”‚ โ”‚ โ””โ”€ ๐Ÿ“‚ Programming โ”‚ โ”œโ”€ Python / Go / Bash โ”‚ โ”œโ”€ APIs โ”‚ โ”œโ”€ JSON & YAML โ”‚ โ””โ”€ Automation scripts โ”‚ โ”œโ”€ ๐Ÿ“‚ Containers โ”‚ โ”œโ”€ ๐Ÿ“‚ Docker โ”‚ โ”‚ โ”œโ”€ Images & containers โ”‚ โ”‚ โ”œโ”€ Dockerfile โ”‚ โ”‚ โ”œโ”€ Volumes โ”‚ โ”‚ โ”œโ”€ Networking โ”‚ โ”‚ โ””โ”€ Docker Compose โ”‚ โ”‚ โ”‚ โ””โ”€ ๐Ÿ“‚ Container Internals โ”‚ โ”œโ”€ Namespaces โ”‚ โ”œโ”€ cgroups โ”‚ โ”œโ”€ OCI runtime โ”‚ โ””โ”€ Container registries โ”‚ โ”œโ”€ ๐Ÿ“‚ Cloud (COMES EARLY) โ”‚ โ”œโ”€ AWS / GCP / Azure basics โ”‚ โ”œโ”€ Compute (VMs) โ”‚ โ”œโ”€ Storage โ”‚ โ”œโ”€ Networking (VPC, Subnets) โ”‚ โ”œโ”€ IAM & permissions โ”‚ โ””โ”€ Load balancers โ”‚ โ”œโ”€ ๐Ÿ“‚ Kubernetes โ”‚ โ”œโ”€ Architecture โ”‚ โ”œโ”€ Pods, Deployments, Services โ”‚ โ”œโ”€ Networking & Ingress โ”‚ โ”œโ”€ Storage (PV, PVC) โ”‚ โ”œโ”€ Helm โ”‚ โ””โ”€ Troubleshooting โ”‚ โ”œโ”€ ๐Ÿ“‚ CI/CD โ”‚ โ”œโ”€ Pipelines โ”‚ โ”œโ”€ Jenkins / GitHub Actions / GitLab CI โ”‚ โ”œโ”€ Build & Test automation โ”‚ โ”œโ”€ Artifact management โ”‚ โ””โ”€ Deployment strategies โ”‚ โ”œโ”€ ๐Ÿ“‚ Infrastructure as Code โ”‚ โ”œโ”€ Terraform / OpenTofu โ”‚ โ”œโ”€ Pulumi โ”‚ โ”œโ”€ Provisioning cloud resources โ”‚ โ””โ”€ Remote state โ”‚ โ”œโ”€ ๐Ÿ“‚ Observability โ”‚ โ”œโ”€ Monitoring (Prometheus) โ”‚ โ”œโ”€ Logging (ELK / Loki) โ”‚ โ”œโ”€ Tracing (Jaeger / Tempo) โ”‚ โ”œโ”€ Alerting โ”‚ โ””โ”€ Debugging production systems โ”‚ โ”œโ”€ ๐Ÿ“‚ Security โ”‚ โ”œโ”€ IAM โ”‚ โ”œโ”€ Secrets management โ”‚ โ”œโ”€ Container security โ”‚ โ”œโ”€ Network policies โ”‚ โ””โ”€ Vulnerability scanning โ”‚ โ””โ”€ ๐Ÿ“‚ Production & Real World โ”œโ”€ CI/CD pipelines โ”œโ”€ GitOps โ”œโ”€ Scaling systems โ”œโ”€ Incident debugging โ”œโ”€ Cost optimization โ””โ”€ Reliability engineering
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aravind_mutthe ย retweeted
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Uday๐Ÿ‘จโ€๐Ÿ’ป Verified account @uday_devops
What is Terraform? -> Terraform is an infrastructure-as-code tool that lets you build, change, and version cloud and on-prem resources safely and effectively. Use of Terraform: -> Terraform is an infrastructure as code tool that lets you define infrastructure resources in human-readable configuration files that you can version, reuse, and share. -> You can then use a consistent workflow to safely and efficiently provision and manage your infrastructure throughout its lifecycle.
uday_devops's tweet photo. What is Terraform? -> Terraform is an infrastructure-as-code tool that lets you build, change, and version cloud and on-prem resources safely and effectively. Use of Terraform: -> Terraform is an infrastructure as code tool that lets you define infrastructure resources in human-readable configuration files that you can version, reuse, and share. -> You can then use a consistent workflow to safely and efficiently provision and manage your infrastructure throughout its lifecycle.
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