Shea Waters’ Post

1. Do you manage a mission-critical application with 24/7 user demands?🕝 2. Are deployment stresses keeping you awake at night? 🌚 3. Using Kubernetes but plagued by daily customer tickets due to failed transactions? 🦠 4. Are you in #fintech, stressing over your deployments? https://lnkd.in/dkVuRecD Don't miss the links to the dotnet runtime and ASP NET Core source code at the bottom of the article. 🗨️ #k8s #aspnetcore #cloudnative #devops

As a Backend Engineer, I've had to learn a lot of concepts and tools to be effective. Here are some of the key ones that have helped me: 👉 API Design: REST, GraphQL, gRPC 👉 Dependency Injection 👉 Microservices Architecture: CQRS, Event Sourcing, Saga, Database per service 👉 Testing: unit tests, integration tests, end-to-end tests 👉 DevOps: Docker, Kubernetes, CDKTF, Helm 👉 Authentication and Authorization: OAuth2, JWT, RBAC 👉 Caching: Redis, Memcached 👉 Database Systems: MongoDB, Cassandra, PostgreSQL, Neo4J 👉 Monitoring: newrelic, Elastic Stack 👉 Message Brokers: RabbitMQ, Kafka These concepts and tools have been critical in my work, allowing me to design and build high-quality systems that meet the requirements of our projects. What would you add to this list? #backendengineering #softwaredevelopment

"Experienced Senior Java Developer/Tech Lead 🚀 Ready to modernize your legacy systems? I bring expertise in Java 11 & 17, Spring Boot, AWS (EC2, RDS, DynamoDB, SQS), Docker, CI/CD, TDD, BDD, DDD, and more. Let's transform your tech stack for success! 📞 Let's schedule a call. 📅 #JavaDeveloper #TechLead #LegacyModernization"

🚀 Excited to share my project! 🚀 I've successfully deployed a scalable, highly available, and secure Java application on Amazon Web Services (AWS) using a cutting-edge 3-tier architecture. Here are some key highlights of the project: 🌟 VPC Setup: Established a robust network structure with public and private subnets to ensure security and efficient communication. 🛡️ Bastion Host: Facilitates secure access to the private network for seamless administration. 🔨 Maven Build: Implemented a robust CI/CD pipeline using Maven, Bitbucket, Sonarcloud, and Jfrog for efficient code management and deployment. 🏗️ 3-Tier Architecture: Deployed MySQL RDS as the backend, Tomcat application server as the middleware, and Nginx as the frontend - all orchestrated in a highly available and auto-scalable setup. 🔄 Post-Deployment Actions: Configured cron jobs, CloudWatch alarms, and other tasks to ensure optimal system performance and monitoring. 🎯 Purpose: This project serves as a showcase of best practices in deploying and managing Java applications in the cloud. It demonstrates the use of various AWS services, automation tools, and CI/CD practices to achieve a secure, scalable, and highly available architecture. Developers and cloud enthusiasts can leverage this project to understand and implement similar setups for their applications. Check out the Git repository for more details and feel free to explore and learn! 🔗 http://bit.ly/42erBSO #AWS #Java #CloudComputing #DevOps #CI/CD #Scalability #Security #Innovation

🚀 Unlock Deeper Insights for Your GCP Java App in Cloud Run: Beyond the Golden Signals! 🚀 . . . . Monitoring your Java application on Cloud Run goes beyond the basics! While the "Golden Signals" (latency, traffic, errors, and saturation) are essential, here are additional metrics to supercharge your understanding and optimize performance: Application-Specific Metrics: 🗑️ Java Garbage Collection: Identify memory leaks or inefficiencies. 🔄 Thread Pool Utilization: Ensure efficient resource allocation. 📊 Database Interactions: Spot potential bottlenecks or inefficient queries. 🚀 HTTP API Performance: Monitor endpoints for latency, errors, and response sizes. 📜 Application Logs: Proactively diagnose issues with log analysis tools. Cloud Run and Terraform Metrics: 🔄 Container Restarts and Crashes: Identify container instability or deployment issues. ⚙️ Cloud Run Revisions and Scaling: Ensure efficient resource utilization. 🛠️ Terraform Deployment Times and Success Rates: Optimize your CI/CD pipeline. 🏭 Cloud Registry Repository Access: Identify bottlenecks in your build and deployment process. Additional Metrics: 💻 Resource Utilization: Monitor CPU, memory, and network usage. 💸 Cost Optimization: Track Cloud Run costs and resource usage. 📈 User Experience Metrics: Utilize synthetic monitoring tools for optimal user experience. Visualization and Alerting: 📊 Dashboarding Tools: Use Grafana or Kibana for comprehensive visualizations. 🚨 Alerting Rules: Proactively identify and remediate issues with key metrics. Benefits of Going Beyond the Golden Signals: 🎯 Deeper Insights: Identify specific bottlenecks, memory leaks, or inefficient code. 🛡️ Improved Stability: Proactively address issues before impacting users. 💰 Cost Savings: Scale efficiently and avoid over-provisioning. 🚀 Faster Debugging: Quickly pinpoint root causes and resolve efficiently. By incorporating these metrics into your SRE dashboard, you gain a holistic view of your GCP Java application in Cloud Run—empowering you to optimize performance, enhance reliability, and deliver a seamless user experience. 🌱 Thank you for reading! 🙌 Stay tuned for more posts! 🙌 🌐Follow me hashtag #ramprakash on LinkedIn for the latest in cloud computing, Devops / DevSecOps / SRE and tech trends! 👩💻👩💻🚀 #DevSecOps #SecureSoftware #ContinuousImprovement #TechInnovation #SoftwareDevelopment #GCP #Java #CloudRun #DevOps #Monitoring #PerformanceOptimization

How to Integrate Dynatrace with a Java-based Application – A Guide One final step: To monitor your processes, it is necessary to restart them. You can always check which processes are not being monitored and require restarting. Simply select Deployment status from the navigation menu, click on either the All Hosts or Recently connected hosts tab, and expand the desired host to view the relevant information. Read More: https://lnkd.in/drtQE-mg #javaskills #javadevelopment #java

Microservices Best Practices: 1) Keep Independent and loosely coupled Microservices. 2) Try to Reach the Glory of REST. 3) Use Distributed Configuration. 4) Using Spring HATEOAS. This helps you use navigable, restful APIs. 5) Monitor everything and Logging. 6) Application performance management(APM). This collects extra details to help you troubleshoot issues.  7) Continuous Delivery. 8) API gateways to aggregate data to specific clients. 9) Event Sourcing and CQRS (Command and Query Responsibility Segregation). #microservices #java

Five years in the Java microservices trenches, and I'm still dreaming of: ✒ Observability superpowers: X-ray our systems with AI-powered tracing and anomaly detection. No more poking blind in the dark! ✒ Fort Knox security: Built-in microservice security, zero-trust architectures, and bulletproof identity management. Sleep tight, hackers. ✒ Tamed testing beast: Contract testing, chaos testing, and smart test case generation. Free us from the testing treadmill! ✒ Developer experience bliss: Hot reloading, streamlined CI/CD, and marshmallow-soft deployments. Coding should be a joyride, not a drag. ✒ Open source rocket fuel: More collaboration, innovation, and democratization of microservices magic. Let's code the future together! What's on your 2024 Java microservices wishlist? Share in the comments! #microservices #javadeveloper #devlife #wishfulthinking

Notes from JAVAPRO serverless sessions. If you are a Java SRE or dev, checkout Adam Bien's sessions. Serverless makes a lot of sense going into 2024. Examples are AWS specific. MONEY (free lunches are over) - Pay for what you use - Scale to zero ENVIRONMENT - Reduction in CO2 (why are you running a server at night when nobody is using it?) LESSER OVERHEAD/ HEADACHE - Lesser responsibilities (no docker; no jvm; no OS; no VPCs; no IPs) FASTER - faster provisioning - connectionless (RDS proxy) - Built-in authentication - Dev is identical to production (Major advantage for QA) - Easy updates (1 second downtime for RDS patches/ upgrades) + Blue/ Green (RDS/ Aurora) for schema changes