π Exploring how LLMs work in real systems
Recently, I explored how to take a Large Language Model beyond simple testing and design a scalable, secure, and production-ready architecture around it.
Instead of focusing only on prompt β response, I worked on building a complete system flow:
β’ Multiple users interacting through applications
β’ A backend API layer handling requests, validation, and control
β’ A security layer ensuring proper access and safe communication
β’ An LLM inference layer generating responses in real time
β’ Monitoring and logging to track performance and reliability
Also explored how CI/CD pipelines can be used to automate deployment and testing for such systems.
This helped me understand that working with LLMs is not just about models β itβs about building reliable, scalable systems around them.
#AI #LLM #DevOps #Cloud #SystemDesign #LearningInPublic
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π Server Security Hardening with Ansible
Excited to share a project focused on automating server security hardening using Ansible, ensuring consistency, scalability, and strong security across infrastructure.
πΉ Overview:
Implemented automated configuration management to enforce standardized hardening policies across multiple environments, reducing manual effort and improving compliance.
πΉ Key Highlights:
βοΈ Automated Hardening Playbooks
Developed Ansible playbooks to secure Operating Systems, Web Servers, and Databases, ensuring uniform configurations across all systems.
π‘οΈ Security Best Practices (VAPT)
Applied Vulnerability Assessment and Penetration Testing (VAPT) guidelines to strengthen system defenses and minimize attack surfaces.
π’ Enhanced On-Premises Security
Improved the overall security posture of on-premises VMs by enforcing strict access controls, configurations, and security policies.
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π Cloud-Native DevSecOps CI/CD Platform
Excited to share a secure, scalable, and fully automated DevSecOps pipeline built on AWS, integrating GitOps practices and continuous security at every stage of deployment.
πΉ Key Highlights:
β End-to-End Secure CI/CD Pipeline
Designed a cloud-native pipeline with built-in security, ensuring safe and reliable deployments across all environments.
β‘ 70% Faster Deployments
Optimized delivery speed using GitHub Actions, significantly reducing deployment time and improving release efficiency.
π Continuous Security Scanning
Integrated SonarQube and Trivy for automated code quality checks and vulnerability scanning throughout the pipeline.
π GitOps-Based Deployments
Implemented Argo CD for declarative, version-controlled deployments to Kubernetes clusters, ensuring consistency and traceability.
π Multi-Environment Pipeline Strategy
Structured pipelines for Dev, UAT, and Production, enabling controlled releases and environment-specific configurations.
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π SmartATP β Enterprise Automation Platform
Proud to share a production-ready, cloud-native SaaS platform built on AWS, designed for scalability, automation, and multi-tenant architecture.
πΉ Key Highlights:
β Cloud-Native SaaS Architecture
Built on AWS with a fully scalable, secure, and resilient infrastructure supporting multi-service workloads.
β Microservices with ECS Fargate
Deployed containerized services including API, Admin, Report, and Worker for efficient workload separation and scaling.
β Modern Frontend Delivery
Leveraging CloudFront + S3 for high-performance static hosting with SSL and custom domain integration.
β Robust Data & Event Handling
Integrated RDS MySQL, WebSocket API Gateway, and EventBridge for real-time communication and scheduled job processing.
β CI/CD Automation
Seamless deployment pipelines using AWS CodePipeline and Azure DevOps, ensuring faster and reliable releases.
β Multi-Tenant Client Onboarding
Automated infrastructure provisioning using parameterized CloudFormation templates for scalable client onboarding.
β High-Performance Load Balancing
Architected with Application Load Balancer (ALB) and Network Load Balancer (NLB) to handle diverse traffic patterns across application and reporting layers.
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π¨ Downtime doesnβt wait β and your cloud monitoring shouldnβt either.
In todayβs always-on digital world, even a few minutes of downtime can result in lost revenue, security risks, and reduced customer trust.
Thatβs why 24/7 cloud monitoring is no longer optional β itβs essential.
With continuous monitoring, businesses can:
β Identify issues before they affect users
β Enhance performance and uptime
β Improve security posture
β Optimize cloud costs proactively
At EloxTech, we help enterprises stay ahead with real-time monitoring, smart alerts, and proactive incident management.
π Want to learn why 24/7 monitoring is critical for your business?