[{"data":1,"prerenderedAt":64},["ShallowReactive",2],{"site-content-public":3},{"freelance":4,"blogPosts":7},{"fiverr":5,"upwork":6},"https://www.fiverr.com/s/99vwy5e","https://www.upwork.com/freelancers/~01d4eba92d3e89fc39?mp_source=share",[8,23,35,45,54],{"id":9,"title":10,"excerpt":11,"content":12,"url":13,"publishedAt":14,"tags":15},"post-1740000000000","Launching My Fiverr Backend Engineering Service: A New Milestone","I launched a new Fiverr backend engineering service to support startups and teams building scalable systems with Go, Laravel, and production-ready architecture.","\u003Cp>After 3+ years of hands-on software engineering work across production systems, I recently launched a Fiverr service focused on backend development and system design.\u003C/p>\u003Cp>This move is not just about freelancing. It is about helping startups and product teams build reliable backend foundations with practical engineering support.\u003C/p>\u003Ch3>What I have been working on\u003C/h3>\u003Cp>Through my work at \u003Cstrong>Mada Software\u003C/strong> and other remote teams, I have contributed to real production environments and high-traffic applications.\u003C/p>\u003Cul>\u003Cli>Built and improved backend services using \u003Cstrong>Laravel\u003C/strong> and \u003Cstrong>Go\u003C/strong>\u003C/li>\u003Cli>Optimized API performance and database query paths\u003C/li>\u003Cli>Supported scalable e-commerce and marketplace workflows\u003C/li>\u003Cli>Worked with \u003Cstrong>Redis\u003C/strong>, \u003Cstrong>RabbitMQ\u003C/strong>, and REST APIs in production\u003C/li>\u003Cli>Implemented CI/CD pipelines that reduced deployment issues and improved release reliability\u003C/li>\u003Cli>Contributed to microservices and distributed system architecture decisions\u003C/li>\u003C/ul>\u003Ch3>What I offer through this service\u003C/h3>\u003Cul>\u003Cli>API development and architecture support\u003C/li>\u003Cli>Performance optimization and bottleneck analysis\u003C/li>\u003Cli>System design guidance for scalability and reliability\u003C/li>\u003Cli>Codebase stabilization and refactoring for safer releases\u003C/li>\u003C/ul>\u003Cp>Fiverr service: \u003Ca href=\"https://lnkd.in/e2wbGyFG\" rel=\"noopener noreferrer\" target=\"_blank\">https://lnkd.in/e2wbGyFG\u003C/a>\u003C/p>\u003Cp>Portfolio: \u003Ca href=\"https://kareemhamed.io\" rel=\"noopener noreferrer\" target=\"_blank\">https://kareemhamed.io\u003C/a>\u003C/p>\u003Ch3>Original LinkedIn post\u003C/h3>\u003Cp>\u003Ca href=\"https://www.linkedin.com/posts/kareemhamed001_backenddevelopment-softwareengineering-golang-activity-7428169821915209728-bSkN?utm_source=share&utm_medium=member_desktop&rcm=ACoAAC96xNoBJAg09G_5CceKPY48ruNk22xIdX4\" rel=\"noopener noreferrer\" target=\"_blank\">View the original LinkedIn post\u003C/a>\u003C/p>\u003Cp>If you are building a product and need backend support, feel free to connect.\u003C/p>","https://www.linkedin.com/posts/kareemhamed001_backenddevelopment-softwareengineering-golang-activity-7428169821915209728-bSkN?utm_source=share&utm_medium=member_desktop&rcm=ACoAAC96xNoBJAg09G_5CceKPY48ruNk22xIdX4","2026-02-15",[16,17,18,19,20,21,22],"backend-development","software-engineering","golang","laravel","microservices","ci-cd","freelance",{"id":24,"title":25,"excerpt":26,"content":27,"url":28,"publishedAt":14,"tags":29},"post-1740000000001","Why Goroutines Are Go’s Secret Weapon for High-Performance Systems","Go handles extreme backend load effectively because of lightweight goroutines, fast runtime scheduling, and an efficient M:N concurrency model.","\u003Cp>Using \u003Ccode>go func()\u003C/code> often feels fast immediately. But when your system must process millions of records in seconds, performance depends on how Go works under the hood.\u003C/p>\u003Cp>Go’s concurrency model is not only a feature—it is a runtime-level engineering advantage.\u003C/p>\u003Ch3>1) Memory efficiency\u003C/h3>\u003Cp>Traditional OS threads can consume significant memory (often around 1MB by default), which limits how many concurrent units of work you can run safely. Goroutines start with a very small stack (around 2KB), making high concurrency practical even on constrained infrastructure.\u003C/p>\u003Ch3>2) Faster context switching\u003C/h3>\u003Cp>In many systems, thread switching is managed by the OS and can be expensive under heavy load. Go’s runtime schedules goroutines in user space, reducing switching overhead and improving responsiveness.\u003C/p>\u003Ch3>3) M:N scheduler intelligence\u003C/h3>\u003Cp>Go maps many goroutines onto fewer OS threads and dynamically balances work. If one thread is blocked, runnable goroutines can move to another thread (work stealing), keeping throughput steady.\u003C/p>\u003Ch3>Bottom line\u003C/h3>\u003Cp>Go’s strength is not only clean syntax. Its runtime helps engineers focus on business logic while still getting reliable, scalable performance in production backend workloads.\u003C/p>\u003Ch3>Original LinkedIn post\u003C/h3>\u003Cp>\u003Ca href=\"https://www.linkedin.com/posts/kareemhamed001_golang-backend-concurrency-activity-7426896202601869312-xyEB?utm_source=share&utm_medium=member_desktop&rcm=ACoAAC96xNoBJAg09G_5CceKPY48ruNk22xIdX4\" rel=\"noopener noreferrer\" target=\"_blank\">View the original LinkedIn post\u003C/a>\u003C/p>","https://www.linkedin.com/posts/kareemhamed001_golang-backend-concurrency-activity-7426896202601869312-xyEB?utm_source=share&utm_medium=member_desktop&rcm=ACoAAC96xNoBJAg09G_5CceKPY48ruNk22xIdX4",[18,30,31,32,33,34],"backend","concurrency","performance","go-runtime","systems-design",{"id":36,"title":37,"excerpt":38,"content":39,"url":40,"publishedAt":14,"tags":41},"post-1740000000002","Why 100 Goroutines Beat One Massive Loop: Worker Pool Pattern in Go","A fixed worker pool delivers high throughput without resource chaos by balancing parallelism, memory usage, and database pressure.","\u003Cp>When processing very large datasets, the wrong concurrency model can hurt more than help. For one analytics workload, I had three options:\u003C/p>\u003Cul>\u003Cli>Single sequential process (too slow)\u003C/li>\u003Cli>One goroutine per record (resource chaos)\u003C/li>\u003Cli>Fixed worker pool (best balance)\u003C/li>\u003C/ul>\u003Cp>The worker pool pattern was the most stable and scalable option.\u003C/p>\u003Ch3>Why a fixed worker pool works\u003C/h3>\u003Cp>Spawning thousands of goroutines at once can overwhelm DB connections and spike CPU usage. A controlled number of workers keeps throughput high while protecting shared resources.\u003C/p>\u003Ch3>Core building blocks\u003C/h3>\u003Cul>\u003Cli>\u003Cstrong>Job channel\u003C/strong>: queues record batches for processing\u003C/li>\u003Cli>\u003Cstrong>Fixed workers\u003C/strong>: a stable number of goroutines pulling jobs continuously\u003C/li>\u003Cli>\u003Cstrong>WaitGroup\u003C/strong>: ensures all workers finish before returning results\u003C/li>\u003C/ul>\u003Ch3>Result\u003C/h3>\u003Cp>Using this design, I got stable memory behavior, consistent CPU utilization, and significantly faster dashboard response times.\u003C/p>\u003Cp>In Go, concurrency is not just about doing more things at once—it is about doing them efficiently and predictably.\u003C/p>\u003Ch3>Original LinkedIn post\u003C/h3>\u003Cp>\u003Ca href=\"https://www.linkedin.com/posts/kareemhamed001_golang-concurrency-backend-activity-7426539115791306752-3Cqp?utm_source=share&utm_medium=member_desktop&rcm=ACoAAC96xNoBJAg09G_5CceKPY48ruNk22xIdX4\" rel=\"noopener noreferrer\" target=\"_blank\">View the original LinkedIn post\u003C/a>\u003C/p>","https://www.linkedin.com/posts/kareemhamed001_golang-concurrency-backend-activity-7426539115791306752-3Cqp?utm_source=share&utm_medium=member_desktop&rcm=ACoAAC96xNoBJAg09G_5CceKPY48ruNk22xIdX4",[18,42,31,43,32,44],"worker-pool","backend-engineering","system-design",{"id":46,"title":47,"excerpt":48,"content":49,"url":50,"publishedAt":14,"tags":51},"post-1740000000003","From 25 Seconds to 500ms: Reducing Analytics Latency with Go and Redis","A sidecar Go service, cache-aside strategy, and proactive cache warming reduced analytics response time from 25 seconds to about 500ms.","\u003Cp>In backend systems, 25 seconds of latency is a serious user experience problem. I faced this with a legacy analytics dashboard querying a 10M-row table.\u003C/p>\u003Cp>The bottleneck was not only the database. ORM overhead and sequential processing in the application layer were major contributors.\u003C/p>\u003Ch3>Architecture decision\u003C/h3>\u003Cp>Instead of only tweaking queries, I introduced a focused Go sidecar service for heavy aggregation workloads.\u003C/p>\u003Ch3>What changed\u003C/h3>\u003Cul>\u003Cli>\u003Cstrong>Concurrency\u003C/strong>: replaced sequential loops with goroutine-based parallel extraction\u003C/li>\u003Cli>\u003Cstrong>Cache-aside\u003C/strong>: stored expensive aggregate results in Redis\u003C/li>\u003Cli>\u003Cstrong>Proactive cache warming\u003C/strong>: background worker refreshed cache every 5 minutes\u003C/li>\u003C/ul>\u003Ch3>Outcome\u003C/h3>\u003Cp>Response time dropped from 25s to approximately 500ms, with much more consistent dashboard behavior under load.\u003C/p>\u003Ch3>Engineering lesson\u003C/h3>\u003Cp>Laravel remains excellent for productivity, but at high scale or CPU-heavy paths, Go can be the right companion technology. The best architecture is pragmatic, not stack-loyal.\u003C/p>\u003Ch3>Original LinkedIn post\u003C/h3>\u003Cp>\u003Ca href=\"https://www.linkedin.com/posts/kareemhamed001_golang-backend-performance-activity-7425814339208712192-krr4?utm_source=share&utm_medium=member_desktop&rcm=ACoAAC96xNoBJAg09G_5CceKPY48ruNk22xIdX4\" rel=\"noopener noreferrer\" target=\"_blank\">View the original LinkedIn post\u003C/a>\u003C/p>","https://www.linkedin.com/posts/kareemhamed001_golang-backend-performance-activity-7425814339208712192-krr4?utm_source=share&utm_medium=member_desktop&rcm=ACoAAC96xNoBJAg09G_5CceKPY48ruNk22xIdX4",[18,30,52,53,20,19],"performance-optimization","redis",{"id":55,"title":56,"excerpt":57,"content":58,"url":59,"publishedAt":14,"tags":60},"post-1740000000004","Designing a Go Microservices E-Commerce Learning Project","A practical Go microservices project focused on architecture decisions, service boundaries, reliability patterns, and observability—not just feature count.","\u003Cp>I built a Go-based e-commerce learning project to practice microservices architecture with a strong focus on engineering decisions over feature quantity.\u003C/p>\u003Ch3>Service landscape\u003C/h3>\u003Cp>The system is split into five independent services:\u003C/p>\u003Cul>\u003Cli>API Gateway\u003C/li>\u003Cli>User Service\u003C/li>\u003Cli>Product Service\u003C/li>\u003Cli>Cart Service\u003C/li>\u003Cli>Order Service\u003C/li>\u003C/ul>\u003Ch3>API Gateway responsibilities\u003C/h3>\u003Cul>\u003Cli>JWT-based authentication\u003C/li>\u003Cli>Authorization and RBAC\u003C/li>\u003Cli>Request routing\u003C/li>\u003Cli>Rate limiting\u003C/li>\u003Cli>Unified handling of cross-cutting concerns\u003C/li>\u003C/ul>\u003Ch3>Architecture style\u003C/h3>\u003Cp>Each service follows Clean Architecture layers (Domain / Use Case / Repository / Delivery) to keep business logic isolated from infrastructure details and improve maintainability over time.\u003C/p>\u003Ch3>Data and communication\u003C/h3>\u003Cul>\u003Cli>Database-per-service pattern\u003C/li>\u003Cli>PostgreSQL for User, Product, and Order services\u003C/li>\u003Cli>Redis for Cart service performance\u003C/li>\u003Cli>gRPC + Protocol Buffers for inter-service communication\u003C/li>\u003C/ul>\u003Ch3>Reliability and observability\u003C/h3>\u003Cul>\u003Cli>Circuit breaker for service-to-service calls\u003C/li>\u003Cli>Graceful shutdown to protect in-flight requests\u003C/li>\u003Cli>Distributed tracing with OpenTelemetry\u003C/li>\u003Cli>Structured logging for data-driven debugging\u003C/li>\u003C/ul>\u003Cp>The full system runs with Docker. The biggest takeaway was understanding how early architecture decisions shape scalability and operability as systems grow.\u003C/p>\u003Ch3>Original LinkedIn post\u003C/h3>\u003Cp>\u003Ca href=\"https://www.linkedin.com/posts/kareemhamed001_microservices-systemdesign-distributedsystems-activity-7424108593215365120-CRx-?utm_source=share&utm_medium=member_desktop&rcm=ACoAAC96xNoBJAg09G_5CceKPY48ruNk22xIdX4\" rel=\"noopener noreferrer\" target=\"_blank\">View the original LinkedIn post\u003C/a>\u003C/p>","https://www.linkedin.com/posts/kareemhamed001_microservices-systemdesign-distributedsystems-activity-7424108593215365120-CRx-?utm_source=share&utm_medium=member_desktop&rcm=ACoAAC96xNoBJAg09G_5CceKPY48ruNk22xIdX4",[20,44,61,43,18,62,63],"distributed-systems","grpc","clean-architecture",1774866600916]