Somanath Mohapatra

#Connections !! AWS Cloud Engineer  #Dallas,TX (Hybrid)(#LocalOnly) Contractual - #w2 & #c2c Only - #USC and #GC Mandatory need :#AWS #Kubernetes #React or #Angular Reach me at Yash Chaudhary !! #followformore

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Troubleshooting Kubernetes ETCD server issues requires a systematic approach for effective problem resolution. Here are clear pathways to resolve common issues: 1. Check ETCD Cluster Health: - Utilize `kubectl` commands to verify the health of the ETCD cluster. Ensure all ETCD pods are running. 2. Review ETCD Logs: - Retrieve logs to pinpoint errors or warnings. Look for specific error messages related to ETCD cluster communication or data consistency. 3. Check ETCD Configuration: - Validate the correctness of configuration files. Ensure parameters like data directory, cluster endpoints, and TLS settings are accurate. 4. Network Issues: - Ensure network connectivity between ETCD nodes and Kubernetes nodes. Check firewall rules, network policies, and DNS resolution. 5. ETCD Data Consistency: - Address inconsistent data or data corruption issues by backing up and restoring ETCD data. Validate data consistency post-restoration. 6. Resource Utilization: - Monitor resource utilization of ETCD pods to ensure adequate allocation of CPU and memory resources. 7. Update and Patch Management: - Keep ETCD and Kubernetes components updated to the latest stable versions. Apply patches for known issues or security vulnerabilities. 8. Cluster Reconciliation: - Consider restarting ETCD pods or nodes cautiously if issues persist. Monitor cluster recovery and data integrity. 9. Community Support and Documentation: - Refer to Kubernetes documentation, ETCD troubleshooting guides, and community forums for specific issues not covered here. Effectively troubleshoot and resolve ETCD server issues in a Kubernetes cluster by following these pathways, ensuring reliability and stability of your container orchestration environment.

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Comparing AWS Lambda on ARM vs x86 architectures AWS Lambda introduced support for ARM-based Graviton2 instances alongside the traditional x86 instances. These ARM-based instances offer several benefits, including potentially lower costs and improved performance for certain workloads. Link : https://lnkd.in/gG5-zisN https://lnkd.in/gi69uSbK

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12 Microservices Best Practices : 1. Orchestration with Kubernetes Why it matters: - Automated container management - Efficient resource utilization - Self-healing capabilities - Rolling updates with zero downtime Best Tool: Kubernetes has become the de facto standard, with alternatives like Docker Swarm for simpler deployments. 2. API Gateway Implementation Critical aspects: - Request routing - Authentication & authorization - Rate limiting - Response caching - API versioning Popular choices: Kong, AWS API Gateway, or Netflix Zuul 3. Containerization with Docker Key benefits: - Consistent environments - Isolated dependencies - Rapid deployment - Version control for entire application stacks Pro tip: Use multi-stage builds to optimize container sizes 4. Security Best Practices Must-haves: - OAuth2/JWT implementation - Service-to-service authentication - Secrets management - Regular security audits - Network policies Remember: Security is a continuous process, not a one-time setup 5. CI/CD Pipeline Excellence Essential components: - Automated testing - Infrastructure as Code - Continuous monitoring - Automated rollbacks - Feature flags Tools to consider: Jenkins, GitLab CI, GitHub Actions 6. Single Responsibility Principle Guidelines: - One service = one business capability - Clear domain boundaries - Independent deployability - Autonomous teams Warning: Avoid the "nanoservice" trap! 7. Database Per Service Key considerations: - Data autonomy - Appropriate database selection - Clear ownership - Schema independence Challenge: Managing distributed transactions 8. Observability Triad Focus areas: - Metrics (what's happening) - Logging (why it happened) - Tracing (where it happened) Tools: ELK Stack, Prometheus, Jaeger 9. Event-Driven Architecture Benefits: - Loose coupling - Better scalability - Improved resilience - Asynchronous processing Technologies: Kafka, RabbitMQ, AWS SNS/SQS 10. Stateless Design Principles: - No session affinity - Cloud-native ready - Horizontal scalability - Resilience to failures 11. Scalability Patterns Strategies: - Horizontal scaling - Load balancing - Caching - Database sharding - Command Query Responsibility Segregation (CQRS) 12. Resilience & Fault Tolerance Implementation: - Circuit breakers - Retry policies - Fallback mechanisms - Bulkhead pattern Tool spotlight: Resilience4j, Hystrix Pro Tips for Success: 1. Start Small: - Begin with a monolith - Gradually break into services - Learn from each iteration 2. Monitor Everything: - Service health - Business metrics - Infrastructure metrics - User experience 3. Documentation is Key: - API specifications - Dependencies - Deployment procedures - Troubleshooting guides 4. Team Structure: - Conway's Law - Two-pizza teams - Clear ownership - Cross-functional capabilities Common Pitfalls to Avoid: - Premature decomposition - Shared databases - Synchronous communication dependencies - Inadequate monitoring - Insufficient automation

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🚀 Understanding the Binpacking Problem in Kubernetes In Kubernetes, the binpacking problem refers to efficiently scheduling and allocating resources (like CPU and memory) to Pods, ensuring they are packed into nodes in a way that maximizes resource utilization while meeting constraints like resource limits, availability, and performance. Binpacking Problem in Kubernetes Context: The main objective is to place the pods on nodes such that resources (CPU, memory, etc.) are efficiently utilized, and the system remains stable. Here's how it works: 🔹 Pods as Items: Each pod requires a certain amount of resources. 🔹 Nodes as Bins: Nodes have a fixed amount of resources. 🔹 Objective: Maximize resource usage without overcommitting any node. Key Concepts in Binpacking within Kubernetes: 🔸 Scheduler: Kubernetes uses a scheduler to decide where a pod should run, taking into account resource availability, constraints (node selectors, taints, tolerations), and affinity rules. 🔸 Resource Requests & Limits: Pods define the minimum and maximum resources needed. The scheduler uses these to prevent over- or under-utilization of resources. 🔸 Node and Pod Resource Allocation: The scheduler ensures that pods are placed in nodes without exceeding the available resources on each node. Efficient Binpacking Algorithms: Best Fit: Place pods on the node with the least available resources while meeting the pod’s needs. Worst Fit: Place pods on the node with the most resources left to leave space for future pods. First Fit: Place pods on the first available node. Example: Resource Requests & Limits: Pod 1: Requests 1 CPU, 2GB memory. Pod 2: Requests 2 CPU, 1GB memory. Pod 3: Requests 1 CPU, 1GB memory. Nodes: Node A: 4 CPUs, 8GB memory. Node B: 2 CPUs, 4GB memory. Scheduling Decision: Pod 1 and Pod 2 could be placed on Node A. Pod 3 could be placed on Node B. This ensures efficient use of resources without overcommitting any node. Challenges in Binpacking: Overcommitment: Pods may consume more resources than requested, starving other pods. Resource Fragmentation: Small amounts of available capacity may hinder efficient pod placement. Scalability: As clusters grow, the complexity of the binpacking problem increases. Optimizing Binpacking in Kubernetes: To optimize binpacking: Set proper resource requests and limits for all pods. Use Vertical Pod Autoscaling (VPA) and Horizontal Pod Autoscaling (HPA) to scale based on resource usage. Implement taints and tolerations to avoid overpacking specific nodes. Efficient binpacking ensures that your Kubernetes cluster is performing optimally, maximizing resource utilization and minimizing waste. #Binpacking #KubernetesScheduling #ResourceOptimization #CloudComputing #ContainerOrchestration #Kubernetes #DevOps #CloudInfrastructure #DistributedSystems #Microservices

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DM me #DevSecOps folks !! ( #immediate ) Strong fundamentals with at least 2.5 -4 years implementation exp : Gradle, GIT, MS Azure (ARM templates, AKS, GitHub Adv Security( #ghas), Application gateway, #Azure AD)Frameworks: #Kubernetes, Gradle, #GitHubActions , CICD set up azure deployment, terraform script understanding .

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Pointers in Go 😑 , Dare you to point at me 📌 Pointer Basics: 🔹 A pointer in Go is a variable that stores the memory address of another variable. 🔹 Pointers are declared with an asterisk (*) in front of the type of variable they will point to. 📌 Pointer Operations: 🔹 To extract the address of a variable, use an ampersand (&) in front of the variable. 🔹 To dereference a pointer and get the value at that address, use an asterisk (*) on the address. 📌 Zero Value and Creating Pointers: 🔹 The zero value of a pointer is nil, indicating it does not point to anything. 🔹 You can create pointers using the new function in Go. 📌 Pointer Usage in Functions: 🔹 When passing a pointer to a function, you can change the value it points to. 🔹 Functions in Go can return pointers that point to variables allocated on the heap. 📌 Go vs. C & C++ Pointers: 🔹 Go does not support pointer arithmetic like C and C++. 🔹 Pointer arithmetic operations are not allowed in Go. I have written a detailed post here -> https://lnkd.in/g7gzhmvk 🚥 If you liked this post, consider: ♻ Repost to help others find it 🔔 Follow: Anuj Yadav 🧑‍🦰 Tag someone, who could get benefited. 💾 Save this post for future reference 🤔 Share your thoughts in the comments #golang #agiledcoders

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𝐓𝐞𝐫𝐫𝐚𝐟𝐨𝐫𝐦 𝐂𝐨𝐦𝐦𝐚𝐧𝐝 𝐋𝐢𝐧𝐞𝐬 [ 𝐒𝐡𝐚𝐫𝐞 𝐭𝐡𝐢𝐬 𝐏𝐨𝐬𝐭 𝐚𝐧𝐝 𝐒𝐚𝐯𝐞 ] terraform fmt #format code per HCL canonical standard terraform validate #validate code for syntax terraform validate -backend=false #validate code skip backend validation terraform init #initialize directory, pull down providers terraform init -get-plugins=false #initialize directory, do not download plugins terraform init -verify-plugins=false #initialize directory, do not verify plugins for Hashicorp signature terraform apply --auto-approve #apply changes without being prompted to enter "yes" terraform destroy --auto-approve #destroy/cleanup deployment without being prompted for “yes” terraform plan -out plan.out #output the deployment plan to plan.out terraform apply plan.out #use the plan.out plan file to deploy infrastructure terraform plan -destroy #outputs a destroy plan terraform apply -target=aws_instance.my_ec2 #only apply/deploy changes to the targeted resource terraform apply -var my_region_variable=us-east-1 #pass a variable via command-line while applying a configuration terraform apply -lock=true #lock the state file so it can't be modified by any other Terraform apply or modification action(possible only where backend allows locking) terraform apply refresh=false # do not reconcile state file with real-world resources(helpful with large complex deployments for saving deployment time) terraform apply --parallelism=5 #number of simultaneous resource operations terraform refresh #reconcile the state in Terraform state file with real-world resources terraform providers #get information about providers used in current configuration terraform state show aws_instance.my_ec2 #show details stored in Terraform state for the resource terraform state pull > terraform.tfstate #download and output terraform state to a file terraform state mv aws_iam_role.my_ssm_role module.custom_module #move a resource tracked via state to different module terraform state replace-provider hashicorp/aws registry.custom.com/aws #replace an existing provider with another terraform state list #list out all the resources tracked via the current state file terraform state rm aws_instance.myinstace #unmanage a resource, delete it from Terraform state file If you are fresher/experienced then do checkout these links 𝐅𝐫𝐞𝐞 𝐜𝐨𝐮𝐫𝐬𝐞𝐬 𝐢𝐧 𝐃𝐞𝐯𝐎𝐩𝐬 - https://lnkd.in/gkB27ZDF 𝐅𝐑𝐄𝐄 𝐃𝐞𝐯𝐎𝐩𝐬/𝐒𝐑𝐄 𝐦𝐞𝐧𝐭𝐨𝐫𝐬𝐡𝐢𝐩 - https://t.me/freebootcamp7 [ Join this telegram group ] 𝐄𝐧𝐫𝐨𝐥𝐥 𝐏𝐑𝐈𝐌𝐄 𝐁𝐀𝐓𝐂𝐇 www.heydevops.in [ Recorded and Live sessions ]

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🚨 Terraform important commands and concepts 1. terraform init: Initializes a Terraform working directory. 2. terraform validate: Validates the Terraform configuration files. 3. terraform fmt: Formats the Terraform configuration files. ▶️ Section 2: Infrastructure Management 4. terraform apply: Applies the configuration to create or update infrastructure. 5. terraform destroy: Destroys the infrastructure managed by Terraform. 6. terraform refresh: Refreshes the Terraform state to match the actual infrastructure. 7. terraform show: Shows the Terraform state and configuration. ▶️ Section 3: State Management 8. terraform state list: Lists the resources in the Terraform state. 9. terraform state show: Shows the details of a specific resource in the Terraform state. 10. terraform state rm: Removes a resource from the Terraform state. 11. terraform state mv: Moves a resource from one state to another. ▶️ Section 4: Module Management 12. terraform get: Downloads and installs Terraform modules. 13. terraform module: Manages Terraform modules. 14. terraform module init: Initializes a Terraform module. ▶️ Section 5: Provider Management 15. terraform providers: Lists the available Terraform providers. 16. terraform provider: Manages Terraform providers. 17. terraform provider init: Initializes a Terraform provider. ▶️ Section 6: Workspace Management 18. terraform workspace: Manages Terraform workspaces. 19. terraform workspace new: Creates a new Terraform workspace. 20. terraform workspace select: Selects a Terraform workspace. ▶️ Section 7: Debugging and Troubleshooting 21. terraform debug: Enables debug logging for Terraform. 22. terraform logs: Shows the Terraform logs. 23. terraform console: Opens a Terraform console for interactive debugging. ▶️ Section 8: Import and Export 24. terraform import: Imports existing infrastructure into Terraform. 25. terraform export: Exports the Terraform state to a file. ▶️ Section 9: Miscellaneous 26. terraform version: Shows the Terraform version. 27. terraform help: Shows the Terraform help. 28. terraform upgrade: Upgrades Terraform to the latest version. ▶️ Section 10: Advanced Topics 29. terraform console: Opens a Terraform console for interactive debugging. 30. terraform graph: Generates a graph of the Terraform configuration. 31. terraform output: Shows the output of a Terraform configuration. More whole end to end course Bryan Krausen has the best one, here is the link https://lnkd.in/dinhv9GN Jasmine McFarlane-White #HUG_Gandhinagar #terraform #iac #infrastructure #hashicorp

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𝗞𝘂𝗯𝗲𝗿𝗻𝗲𝘁𝗲𝘀 𝗢𝗽𝗲𝗻 𝗦𝘁𝗮𝗻𝗱𝗮𝗿𝗱𝘀 (𝗢𝗖𝗜, 𝗖𝗥𝗜, 𝗖𝗡𝗜, 𝗖𝗦𝗜, 𝗦𝗠𝗜, 𝗖𝗜𝗟) Kubernetes, the de facto standard for container orchestration, relies on a robust ecosystem of open standards. These standards are developed and maintained by the community and define how different components interact within the system 𝗞𝗲𝘆 𝗯𝗲𝗻𝗲𝗳𝗶𝘁𝘀 🔶 𝙄𝙣𝙩𝙚𝙧𝙤𝙥𝙚𝙧𝙖𝙗𝙞𝙡𝙞𝙩𝙮: Different vendors can create products adhering to the same standard, ensuring seamless integration. 🔶 𝙁𝙡𝙚𝙭𝙞𝙗𝙞𝙡𝙞𝙩𝙮: You can choose components and plugins from various vendors based on your specific needs. 𝗦𝘁𝗮𝗻𝗱𝗮𝗿𝗱𝘀 : 🔶 𝙊𝙥𝙚𝙣 𝘾𝙤𝙣𝙩𝙖𝙞𝙣𝙚𝙧 𝙄𝙣𝙞𝙩𝙞𝙖𝙩𝙞𝙫𝙚 (𝙊𝘾𝙄): Defines a standard for container image formats and runtimes. Popular examples include 𝘋𝘰𝘤𝘬𝘦𝘳, 𝘊𝘙𝘐-𝘖, 𝘢𝘯𝘥 𝘙𝘒𝘛 images. 🔶 𝘾𝙤𝙣𝙩𝙖𝙞𝙣𝙚𝙧 𝙍𝙪𝙣𝙩𝙞𝙢𝙚 𝙄𝙣𝙩𝙚𝙧𝙛𝙖𝙘𝙚 (𝘾𝙍𝙄): Establishes a consistent way for Kubernetes to interact with different container runtimes. CRI utilizes a plugin architecture, allowing support for various Runtime options like 𝘊𝘙𝘐-𝘖, c𝘰𝘯𝘵𝘢𝘪𝘯𝘦𝘳𝘥 etc 🔶 𝘾𝙤𝙣𝙩𝙖𝙞𝙣𝙚𝙧 𝙉𝙚𝙩𝙬𝙤𝙧𝙠 𝙄𝙣𝙩𝙚𝙧𝙛𝙖𝙘𝙚 (𝘾𝙉𝙄): Provides a specification and toolset for configuring network interfaces within containers. This plugin architecture enables Kubernetes to integrate with various network plugins like 𝘍𝘭𝘢𝘯𝘯𝘦𝘭, 𝘊𝘢𝘭𝘪𝘤𝘰, 𝘢𝘯𝘥 𝘞𝘦𝘢𝘷𝘦 𝘕𝘦𝘵. 🔶 𝘾𝙤𝙣𝙩𝙖𝙞𝙣𝙚𝙧 𝙎𝙩𝙤𝙧𝙖𝙜𝙚 𝙄𝙣𝙩𝙚𝙧𝙛𝙖𝙘𝙚 (𝘾𝙎𝙄): Facilitates communication between Kubernetes and diverse storage providers. Storage providers can develop CSI plugins that are compatible with various container orchestration systems. Examples 𝘈𝘞𝘚 𝘌𝘭𝘢𝘴𝘵𝘪𝘤 𝘉𝘭𝘰𝘤𝘬 𝘚𝘵𝘰𝘳𝘢𝘨𝘦, 𝘕𝘦𝘵𝘈𝘱𝘱 etc. 🔶 𝙎𝙚𝙧𝙫𝙞𝙘𝙚 𝙈𝙚𝙨𝙝 𝙄𝙣𝙩𝙚𝙧𝙛𝙖𝙘𝙚 (𝙎𝙈𝙄): Defines a standard for service meshes on Kubernetes, allowing consistent interaction with different service mesh implementations like 𝘐𝘴𝘵𝘪𝘰, 𝘓𝘪𝘯𝘬𝘦𝘳𝘥 etc 🔶 𝘾𝙤𝙣𝙩𝙖𝙞𝙣𝙚𝙧 𝙄𝙢𝙖𝙜𝙚 𝙇𝙞𝙗𝙧𝙖𝙧𝙮 (𝘾𝙄𝙇): This set of specifications defines how container images are stored, indexed, and distributed. Major container registries like 𝘋𝘰𝘤𝘬𝘦𝘳 𝘏𝘶𝘣, 𝘘𝘶𝘢𝘺.𝘪𝘰, 𝘢𝘯𝘥 𝘏𝘢𝘳𝘣𝘰𝘳 leverage CIL for sharing and reusing container images across various platforms and environments. #kubernetes #Containerization #Cloud

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******Kubernetes Interview Question****** 1. What is Kubernetes, and why is it used? 2. Explain the components of the Kubernetes master and worker nodes. 3. What are Pods in Kubernetes? 4. What is the difference between a Pod and a Node? 5. What is a Namespace, and why is it used? 6. How does Kubernetes handle Pod failures? 7. What are the different types of workloads in Kubernetes? 8. How does a Deployment work? 9. What is a StatefulSet, and when would you use it? 10. Explain DaemonSets and provide a use case for them. 11. What is the difference between ReplicationController, ReplicaSet, and Deployment? 12. What is a Service in Kubernetes, and what are the different types? 13. How does Kubernetes manage internal and external networking? 14. What is a ClusterIP, NodePort, and LoadBalancer Service? 15. Explain Ingress in Kubernetes and its use case. 16. How does DNS work within a Kubernetes cluster? 17. What are Persistent Volumes (PVs) and Persistent Volume Claims (PVCs)? 18. Explain the process of binding a PV to a PVC. 19. What is a StorageClass, and how does it relate to dynamic provisioning? 20. How are ConfigMaps used in Kubernetes? 21. What is the difference between ConfigMaps and Secrets? 22. How can you securely manage secrets in Kubernetes? 23. How do you scale Pods in Kubernetes? 24. What is the Horizontal Pod Autoscaler (HPA), and how does it work? 25. How does Cluster Autoscaler differ from HPA? 26. What is Role-Based Access Control (RBAC) in Kubernetes? 27. Explain the difference between Role and ClusterRole. 28. What is a ServiceAccount, and why would you use it? 29. How can you implement network policies for Pod communication? 30. How do you monitor Kubernetes clusters? 31. What tools would you use to monitor and log Kubernetes applications? 32. What is node affinity? 33. What is StaticPods? 34. What is Taint and Toleration? 35. What is Sidecar Containers and their purpose? 36. How to debug specific container logs?Consider there are 2 containers running inside a single pod? 37. What are the different deployment strategies in Kubernetes? 38. Describe the process of rolling update in Kubernetes? #Linux #AWS #DevOps

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Interview Tip (System Design) 📖💼 System design round is very common these days, not only FAANG/MAANG but other organisations also take system design round very seriously. Follow Arun Kumar Singh for more system design and interview tips The system design is complex and one design doesnt fits all. Below we share useful rules to get you unstuck in an interview - 1. For a Read-Heavy System - Consider using a Cache. 2. For a Write-Heavy System - Use Message Queues for async processing 3. For a Low Latency Requirement - Consider using a Cache and CDN. 4. Need 𝐀tomicity, 𝐂onsistency, 𝐈solation, 𝐃urability Compliant DB - Go for RDBMS/SQL Database. 5. Have unstructured data - Go for NoSQL Database. 6. Have Complex Data (Videos, Images, Files) - Go for Blob/Object storage. 7. Complex Pre-computation - Use Message Queue & Cache. 8. High-Volume Data Search - Consider search index, tries or search engine. 9. Scaling SQL Database - Implement Database Sharding. 10. High Availability, Performance, & Throughput - Use a Load Balancer. 11. Global Data Delivery - Consider using a CDN. 12. Graph Data (data with nodes, edges, and relationships) - Utilize Graph Database. 13. Scaling Various Components - Implement Horizontal Scaling. 14. High-Performing Database Queries - Use Database Indexes. 15. Bulk Job Processing - Consider Batch Processing & Message Queues. 16. Server Load Management & Preventing DOS Attacks- Use a Rate Limiter. 17. Microservices Architecture - Use an API Gateway. 18. For Single Point of Failure - Implement Redundancy. 19. For Fault-Tolerance and Durability - Implement Data Replication. 20. For User-to-User fast communication - Use Websockets. 21. Failure Detection in Distributed Systems - Implement a Heartbeat. 22. Data Integrity - Use Checksum Algorithm. 23. Efficient Server Scaling - Implement Consistent Hashing. 24. Decentralized Data Transfer - Consider Gossip Protocol. 25. Location-Based Functionality - Use Quadtree, Geohash, etc. 26. Avoid Specific Technology Names - Use generic terms. 27. High Availability and Consistency Trade-Off - Eventual Consistency. 28. For IP resolution & Domain Name Query - Mention DNS. 29. Handling Large Data in Network Requests - Implement Pagination. 30. Cache Eviction Policy - Preferred is LRU (Least Recently Used) Cache. 31. To handle traffic spikes: Implement Autoscaling to manage resources dynamically by 32. Need analytics and audit trails - Consider using data lakes or append-only databases 33. Handling Large-Scale Simultaneous Connections - Use Connection Pooling and consider using Protobuf to minimize data payload .. many more Credit Dinesh Varyani #sre #devops #apple #google #netflix #amazon #interviewtips #interviewquestions #interviewpreparation #systemdesign #interview #jobhunting #softwareengineering #softwaredevelopment

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How Does Node.js Handle Different Client Requests in a Single Event Loop, and What Changes with NGINX as an Ingress Proxy? Node.js is built around a single-threaded event loop, ideal for handling I/O-bound tasks asynchronously. Let’s explore how it handles requests directly versus how it operates with NGINX as an ingress proxy. Node.js Without NGINX (Direct Handling) 1️⃣ Event Loop & Non-Blocking I/O:     Node.js processes each client request asynchronously, offloading I/O operations, allowing it to handle many connections efficiently. 2️⃣ Static Content:     Serving static files from Node.js can be inefficient and consumes resources that could be used for dynamic requests. 3️⃣ SSL/TLS Overhead:     Node.js can handle SSL/TLS natively, but this adds CPU load, reducing performance in high-traffic environments. 4️⃣ Connection Management:     Node.js is good at handling fast-moving connections but may struggle with long-running or slow connections, impacting its performance under heavy load. Benefits: - Simplicity and real-time communication. - Ideal for I/O-bound, fast-response applications. Cons: - Poor static file handling. - SSL adds load. - Limited scalability with direct connections. --- Node.js with NGINX as Ingress Proxy 1️⃣ Load Balancing:     NGINX distributes traffic across multiple Node.js instances, allowing for horizontal scaling and improved resource utilization. 2️⃣ Static File Handling:     NGINX handles static content, offloading it from Node.js and improving overall performance. 3️⃣ SSL Termination:     NGINX takes care of SSL/TLS encryption, reducing the CPU load on Node.js, especially under high traffic. 4️⃣ Connection Handling:     NGINX manages slow or idle connections, letting Node.js focus on active requests, improving concurrency. 5️⃣ Caching & Compression:     NGINX handles caching and compression, speeding up responses without adding extra work to Node.js. 6️⃣ Security Enhancements:    NGINX offers rate limiting, IP filtering, and protection against DDoS attacks, adding a critical layer of security. Benefits: - Scalability with load balancing. - Efficient static content serving and SSL offloading. - Advanced connection management and security. Cons: - Increased complexity with an additional layer to manage. - Resource overhead from adding a proxy. Conclusion: Without NGINX, Node.js is simple but can struggle with static content, SSL, and scalability. With NGINX, the system becomes highly scalable, efficient, and secure, making it ideal for production environments handling high traffic. #NodeJS #NGINX #LoadBalancing #WebPerformance #Scalability #Security

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🛠️ **How to Attach Multiple EBS Volumes to an EC2 Instance in AWS** 🛠️ Attaching multiple Elastic Block Store (EBS) volumes to an EC2 instance can enhance performance and storage capabilities. Here’s a step-by-step guide to do it: **1. Launch Your EC2 Instance:**   - Start by launching your EC2 instance from the AWS Management Console.   - Select the desired instance type and configure other settings as needed. **2. Create EBS Volumes:**   - Navigate to the **EC2 Dashboard**.   - Click on **Volumes** under the **Elastic Block Store** section.   - Choose **Create Volume** and specify the size, type (e.g., gp2, io1), and availability zone (must match the instance's AZ).   - Repeat this step for each EBS volume you want to create. **3. Attach EBS Volumes to Your Instance:**   - In the **Volumes** section, select the volume you want to attach.   - Click on **Actions** and then **Attach Volume**.   - Select your EC2 instance from the list.   - Specify the device name (e.g., `/dev/sdf`, `/dev/sdg`, etc.).   - Click **Attach**. Repeat for additional volumes. **4. Format and Mount the Volumes (Linux Instances):**   - SSH into your EC2 instance.   - Use the `lsblk` command to list the attached volumes.   - Format the new volumes using a command like `sudo mkfs -t ext4 /dev/xvdf` (replace `/dev/xvdf` with your volume name).   - Create a mount point: `sudo mkdir /mnt/myvolume`.   - Mount the volume: `sudo mount /dev/xvdf /mnt/myvolume`.   - To make the mount persistent, add an entry in `/etc/fstab`. **5. Verify and Use the Volumes:**   - Check the mounted volumes with `df -h` to ensure everything is set up correctly.   - Now you can use the volumes for data storage, backups, or any other purpose! #AWS #EC2 #EBS #CloudComputing #DevOps #TechTips

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kubernetes few important concepts and important interview questions: 1. Architecture? 2. pod ? 3. Namespace? 4. Replica controller vs replica set? 5. Deployment? 6. Replicaset vs Deployment? 7 . Labels and selectors ? working on services will shortly update

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Sharing some Best Practices for Microservices Deployment: 1. Database Connectivity: Ensure support for both 1-way and 2-way SSL configurations for secure MongoDB connections. 2. Kafka Connectivity: Configure SSL support for both the Kafka broker and Avro Schema Registry based on the setup requirements. 3. Container Endpoints Exposure: Expose all container service endpoints through a single SSL port to streamline secure access. 4. Container Health Check Endpoints: Implement health check APIs that validate external connections to resources like MongoDB, Kafka, and Redis to ascertain container health. 5. IPv4 and IPv6 Localhost Support: Configure containers to support both IPv4 and IPv6 localhost configurations natively. 6. Application Configuration Management: Consolidate all application configurations that vary across SDLC environments into a single file, such as `app.properties`. 7. Secrets Management: Use a cloud-native secrets management service to securely store sensitive data like passwords, private keys, and other credentials, rather than relying on encrypted files. 8. Standardized Path Configuration: Standardize paths used by application containers for read/write operations, such as for log files, configuration files, and machine learning model paths. 9. Startup Logs:   - Include essential details in startup logs, such as:     - Environment and AWS region (if using Secret Manager)     - URLs of all data sources     - Confirmation of successful connections and session establishment     - Exposed endpoints and health check status     - Ensure passwords, PII, and other sensitive data are removed or redacted   - Debug logs should capture external I/O checkpoints (e.g., DB retrievals/insertions, Kafka message processing, Redis operations). 10. Log File Naming: Include `{HOSTNAME}` in log file names for easier identification and management. 11. Pod Health Check: Ensure pod health check endpoints perform KPI checks on external connections (e.g., databases, caches, messaging). Pause pod restarts if health checks fail consecutively, and trigger alerts. 12. Vulnerability Scanning in CI/CD: Integrate SonaType vulnerability checks in CI automation and ensure the latest library versions are used. 13. API Handshake Mechanism: If needed, implement a JWT-based handshake mechanism with 2048-bit encryption to secure API interactions between microservices.

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15 straight-cut points to save AWS bills: 1) 𝐑𝐢𝐠𝐡𝐭-𝐬𝐢𝐳𝐞 𝐢𝐧𝐬𝐭𝐚𝐧𝐜𝐞𝐬: Match instance types to your workload needs to avoid over-provisioning and reduce compute costs. 2) 𝐔𝐬𝐞 𝐒𝐩𝐨𝐭 𝐈𝐧𝐬𝐭𝐚𝐧𝐜𝐞𝐬: Leverage AWS Spot Instances for non-critical workloads to save up to 90% on compute costs. 3) 𝐒𝐜𝐡𝐞𝐝𝐮𝐥𝐞 𝐢𝐧𝐬𝐭𝐚𝐧𝐜𝐞 𝐬𝐡𝐮𝐭𝐝𝐨𝐰𝐧𝐬: Use automation tools to turn off dev/test environments outside business hours. (if it's a non-critical 24*7 Resource) 4) 𝐔𝐬𝐞 𝐬𝐞𝐫𝐯𝐞𝐫𝐥𝐞𝐬𝐬 𝐬𝐞𝐫𝐯𝐢𝐜𝐞𝐬: Opt for AWS Lambda or Fargate to run code without provisioning servers, paying only for actual compute time used. 5) 𝐋𝐞𝐯𝐞𝐫𝐚𝐠𝐞 𝐒𝐚𝐯𝐢𝐧𝐠𝐬 𝐏𝐥𝐚𝐧𝐬 𝐨𝐫 𝐑𝐞𝐬𝐞𝐫𝐯𝐞𝐝 𝐈𝐧𝐬𝐭𝐚𝐧𝐜𝐞𝐬: Commit to 1- or 3-year usage plans for predictable workloads to reduce costs. 6) 𝐔𝐬𝐞 𝐒3 𝐥𝐢𝐟𝐞𝐜𝐲𝐜𝐥𝐞 𝐩𝐨𝐥𝐢𝐜𝐢𝐞𝐬: Move infrequently accessed data to cheaper storage classes like S3 Glacier. 7) 𝐔𝐬𝐞 𝐏𝐫𝐢𝐯𝐚𝐭𝐞 𝐈𝐏𝐬 𝐟𝐨𝐫 𝐢𝐧𝐭𝐞𝐫-𝐬𝐞𝐫𝐯𝐢𝐜𝐞 𝐜𝐨𝐦𝐦𝐮𝐧𝐢𝐜𝐚𝐭𝐢𝐨𝐧: Ensure services communicate over private IPs within the same VPC to avoid public data transfer costs. 8) 𝐎𝐩𝐭𝐢𝐦𝐢𝐳𝐞 𝐝𝐚𝐭𝐚 𝐭𝐫𝐚𝐧𝐬𝐟𝐞𝐫: Use AWS PrivateLink or Direct Connect for internal data transfers to avoid public data transfer charges. 9) 𝐔𝐬𝐞 𝐜𝐚𝐜𝐡𝐢𝐧𝐠: Implement caching with CloudFront or ElastiCache to reduce backend compute and data transfer costs. 10) 𝐌𝐨𝐧𝐢𝐭𝐨𝐫 𝐮𝐧𝐮𝐬𝐞𝐝 𝐫𝐞𝐬𝐨𝐮𝐫𝐜𝐞𝐬: Use cost management tools to find and terminate idle resources like unused EBS volumes or Elastic IPs. 11) 𝐈𝐦𝐩𝐥𝐞𝐦𝐞𝐧𝐭 𝐚𝐮𝐭𝐨-𝐬𝐜𝐚𝐥𝐢𝐧𝐠: Automatically scale your instances to handle traffic spikes and downscale during off-peak times. 12) 𝐂𝐨𝐧𝐬𝐨𝐥𝐢𝐝𝐚𝐭𝐞 𝐂𝐥𝐨𝐮𝐝𝐖𝐚𝐭𝐜𝐡 𝐥𝐨𝐠𝐬: Use CloudWatch log groups efficiently to avoid unnecessary data retention costs. 13) 𝐋𝐞𝐯𝐞𝐫𝐚𝐠𝐞 𝐀𝐑𝐌-𝐛𝐚𝐬𝐞𝐝 𝐢𝐧𝐬𝐭𝐚𝐧𝐜𝐞𝐬: Use AWS Graviton-based instances for workloads that support ARM architecture for better cost-performance. 14) 𝐌𝐢𝐧𝐢𝐦𝐢𝐳𝐞 𝐜𝐫𝐨𝐬𝐬-𝐫𝐞𝐠𝐢𝐨𝐧 𝐝𝐚𝐭𝐚 𝐭𝐫𝐚𝐧𝐬𝐟𝐞𝐫𝐬: Keep services in the same AWS region to avoid inter-region data transfer fees. (to achieve high availability, you can keep minimum resources running in other AZs or run in standby mode) 15) 𝐂𝐨𝐦𝐩𝐫𝐞𝐬𝐬 𝐚𝐧𝐝 𝐨𝐩𝐭𝐢𝐦𝐢𝐳𝐞 𝐝𝐚𝐭𝐚: Reduce data transfer sizes by compressing files before sending between services. Did I miss any important points? please add in the comment section below! Cheers, Sandip Das

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Mini Project 2 : Efficient and Secure Azure Infrastructure Provisioning with Terraform Automation In this project, I successfully automated the deployment of a robust and scalable Azure infrastructure using Terraform, a popular Infrastructure as Code (IaC) tool. The deployment includes creating a resource group, virtual network, subnets, public IPs, network interfaces, and a network security group with defined security rules. The infrastructure is designed with security in mind. The password for the virtual machine is securely stored and retrieved from Azure Key Vault, ensuring sensitive data is not exposed. The network security group is configured with specific rules to control inbound and outbound traffic, enhancing the security of the resources within the network. The infrastructure also demonstrates scalability and flexibility. It includes the creation of a managed disk and its attachment to a Windows virtual machine. The virtual machine is connected to the network via two network interfaces, each associated with a different subnet, demonstrating a multi-subnet setup. This project showcases my skills in automating cloud infrastructure deployment, managing Azure resources, and implementing secure and scalable cloud solutions. It also highlights my proficiency in using Terraform for Infrastructure as Code (IaC), which allows for consistent and repeatable deployments, reducing the possibility of human error and increasing efficiency in managing and scaling the infrastructure. GitHub Link: https://lnkd.in/g7mN7s5C #terraform #devops #freshers #hiring #SRE #devopsengineer #project #terraforminazure

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