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Showing posts from December, 2025

End-to-End Grafana Setup

Monitor Server Performance + Application Performance (Metrics, Logs, Traces) If you want a   single monitoring pane of glass   for: server health (CPU, RAM, disk, network) application performance (latency, error rates) centralized logs distributed traces Grafana works best when paired with the following stack: Prometheus   → metrics Node Exporter   → Linux server metrics cAdvisor   → container metrics (optional but very useful) Loki   → logs (optional) Tempo   → distributed traces (optional) OpenTelemetry   → application instrumentation (recommended) This post walks through a   practical, production-style setup on Ubuntu using Docker Compose , then shows how to instrument applications for full APM. What You’ll Get (Architecture) Server Performance Monitoring CPU, RAM, load average Disk usage and disk I/O Network traffic and errors System and process health (via exporters) Application Performance Monitoring (APM) RED metrics   (Rate, Erro...

How to Set Up AWS RDS Proxy for Applications in a Private Subnet

  Introduction In production environments, database connection management is a common challenge—especially with   Lambda, ECS, or EC2-based applications   that open too many connections. AWS   RDS Proxy   solves this by pooling and managing database connections securely. In this blog, I’ll walk through a   real-world RDS Proxy setup , focusing on applications running in a   private subnet without public IPs —a scenario many teams struggle with. Why Use RDS Proxy? Common problems without RDS Proxy: Too many open DB connections Connection storms during traffic spikes Slow cold starts (especially with Lambda) RDS Proxy benefits: Connection pooling Improved scalability Faster failover IAM-based authentication Better security Architecture Overview Private EC2 / ECS / Lambda │ ▼ RDS Proxy │ ▼ RDS MySQL Key idea:   The application never connects directly to the RDS instance. Prerequisites RDS MySQL or PostgreSQL i...

Building a Real-Time Analytics Pipeline with AWS Amplify, Kinesis, Lambda, InfluxDB, and Grafana

  Introduction Modern applications often need   real-time analytics —tracking user activity, events, or metrics as they happen. In this blog, I’ll walk through a   production-style architecture   where a frontend app sends data to AWS, processes it in real time, visualizes it on dashboards, and also stores raw data for long-term analysis. Architecture Overview Amplify App → Kinesis Data Stream → Lambda → InfluxDB → Grafana ↓ Firehose → S3 This setup enables: ⚡ Real-time dashboards 🧱 Durable raw data storage 📈 Scalable, serverless ingestion Use Case Track real-time events from a web/mobile app Visualize metrics instantly (active users, events/sec) Store all events in S3 for audits or batch analytics Typical examples: IoT telemetry User activity tracking Live operational metrics Components Explained 1. AWS Amplify (Frontend) AWS Amplify hosts the frontend (React / Next.js / Mobile app). The app sends event data directly to ...
  ⚙️ Bridging the Gap: Understanding the Power of DevOps You've likely heard the term DevOps buzzing around the tech world. It’s often mistaken for just a job title or a set of tools, but it's much more profound. At its heart, DevOps is a cultural movement that is revolutionizing how we build, deliver, and maintain software. If you're curious about the future of tech and how companies like Google, Amazon, and Netflix deploy changes thousands of times a day, read on. What Exactly Is DevOps? The name itself is a portmanteau: Development (Dev) and Operations (Ops) . Traditionally, these two teams worked in silos. Developers were rewarded for creating new features quickly, while Operations was rewarded for stability and keeping the lights on. This often created tension: Dev's mindset: "It works on my machine!" Ops's mindset: "If we change it, it might break!" DevOps aims to tear down this wall. It is a philosophy that emphasizes communication,...