Hey there! I'm Pranav Saraswat 👋

Slightly obsessed with automation, infrastructure reliability, and developer experience.

I am a Cloud Engineer & DevOps Architect with a passion for designing resilient systems, optimizing deployment workflows, and building modern platforms. With a strong software engineering foundation and specialized cloud credentials, I bridge the gap between application development and low-level infrastructure operations.

My work centers on Site Reliability Engineering (SRE) and Platform Engineering principles—reducing cognitive load for developers through self-healing systems, automated Infrastructure as Code (IaC) deployment pipelines, and robust observability structures. Whether it is tuning database queries, containerizing complex microservices, or planning multi-region disaster recovery routes, I build with scale, performance, and security in mind.

A curated catalog of the languages, frameworks, and cloud-native systems I work with:

💻 Languages & Core	☁️ Cloud & Platforms	⚙️ DevOps & Tooling
🎨 Frontend & Web	📈 Observability	🤖 Developer Tools

• Google Cloud Certified Professional Cloud Architect
  Successfully verified expertise in designing, planning, and managing highly available, scalable, secure, and robust Google Cloud infrastructure.

I believe in proactive, continuous learning. Here is my structured trajectory for acquiring specialized credentials:

graph LR
    subgraph "Acquired"
        GCP_PCA["GCP Professional Cloud Architect"]
    end
    subgraph "In Progress / Targeted (2026-2027)"
        K8S["Kubernetes (CKA / CKAD)"]
        TF["HashiCorp Terraform Associate"]
        AWS_SAP["AWS Solutions Architect Professional"]
        PLAT["Platform Engineering (GitOps / ArgoCD)"]
    end
    GCP_PCA --> K8S
    K8S --> TF
    TF --> AWS_SAP
    AWS_SAP --> PLAT
    style GCP_PCA fill:#34A853,stroke:#fff,stroke-width:2px,color:#fff
    style K8S fill:#326CE5,stroke:#fff,stroke-width:1px,color:#fff
    style TF fill:#844FBA,stroke:#fff,stroke-width:1px,color:#fff
    style AWS_SAP fill:#FF9900,stroke:#fff,stroke-width:1px,color:#fff
    style PLAT fill:#2563EB,stroke:#fff,stroke-width:1px,color:#fff

Here is a deep dive into the systems I have designed, highlighting their architecture and technical challenges.

A globally scalable, enterprise-grade URL shortening and redirection platform built for high-throughput edge routing, secure redirects, and live bot-detecting analytics.

• Problem Solved: Traditional short-link systems suffer from edge latency, target validation gaps (which invite SSRF attacks), and analytical performance bottlenecks.
• Architecture & Internals:
  • Designed a decoupled layout: Next.js 15 frontend console, and a Fastify API core redirection engine for sub-millisecond execution.
  • Implemented edge-focused caching with Redis to intercept redirect configurations instantly.
  • Designed an event-driven click analytics ingestion pipeline: analytics metadata is buffered in Redis Lists before being batch processed, enriched with geolocation lookup (geoip-lite), scanned for scrapers, and saved to PostgreSQL via Prisma.
  • Mitigated SSRF attacks by validating targets against local CIDR blocks and standard URI patterns.
• Infrastructure: Deployed onto AWS EKS, GCP GKE, and Azure AKS using modular, reusable Terraform plans.
• Status & Roadmap: Production-Ready | Next up: Injecting ML-driven anomaly models for click-fraud classifiers.
• Links: 📁 Repository Target | 🌐 Architecture Documentation

A personal nutrition coach combining machine learning vision, asynchronous socket streaming, and localized target calculation models.

• Problem Solved: Manual macro-tracking is tedious. NutriAI simplifies it by using multi-modal AI to calculate meal nutrition directly from pictures or natural language phrases.
• Architecture & Internals:
  • Developed a dynamic client dashboard using React (Parcel) showing real-time circular SVG gauges.
  • Engineered a Node.js/Express REST backend integrating Groq Llama 3.2 Vision models to break down image ingredients into macro statistics.
  • Built a streaming WebSocket connection (chatSocket.ts) to deliver conversational diet advice.
  • Established strict safety limits, allowing users to inspect and correct macro evaluations prior to database commit.
  • Covered calculation logic with unit tests using Jest.
• Infrastructure: Orchestrated via a local multi-container Docker Compose stack with persistent volume database replication.
• Status & Roadmap: Active Development | Next up: Integrating smartwatch health data APIs (Apple HealthKit / Google Fit).
• Links: 📁 Repository Target | 🌐 API Reference Docs

A reliable data orchestration system built to secure, version, and synchronize object storage across multiple clouds.

• Problem Solved: Protecting enterprise environments from cloud vendor downtime or ransomware threats by providing high-concurrency backup synchronizations.
• Architecture & Internals:
  • Designed a Next.js 14 management dashboard showing real-time host metrics, alerts, and backup job calendars.
  • Created a high-concurrency Express.js sync driver utilizing AWS, GCP, and Azure SDKs to replicate objects across S3, Google Cloud Storage, and Azure Blob Storage.
  • Wrote an automated cron manager mapping scheduled backup pipelines to dynamic, secure API keys.
  • Enforced encryption at rest using AES-256 for onboarding provider credentials.
  • Built integrations for Slack Webhook alert notifications on task failures.
• Infrastructure: Implemented horizontal scaling policies (HPA), Ingress NGINX rule layouts, and database state mappings in clean Kubernetes manifests.
• Status & Roadmap: Active | Next up: Introducing block-level deduplication algorithms to optimize bandwidth costs.
• Links: 📁 Repository Target | 🌐 Deployment Guide

A unified multi-cloud infrastructure orchestration and lifecycle platform designed to deploy, manage, and audit resources across AWS, GCP, and Azure using GitOps best practices.

• Problem Solved: Managing state and enforcing security guardrails across multiple cloud providers manually can lead to configuration drift, security vulnerabilities, and cost overruns.
• Architecture & Internals:
  • Designed a multi-stage parallel deployment CI/CD workflow in GitHub Actions checking for lint errors (TFLint, Checkov, TFSec), cost shifts (Infracost), and compliance policies (Open Policy Agent).
  • Developed a Next.js 16 App Router dashboard that reads remote state parameters directly, visualizes compliance violations, and streams execution logs using Server-Sent Events (SSE).
  • Enforced security guardrails utilizing OPA policies in Rego to block public S3 buckets, open ingress ports, and wildcard IAM permissions.
  • Created automation lifecycle shell scripts for remote state bootstrapping, local dry-run validation, and environment health checks.
• Infrastructure: Provisioned modular AWS, GCP, and Azure configurations, separated using hard env isolation Dev/Staging/Prod parameters.
• Status & Roadmap: Active | Next up: Multi-tenant dynamic environment creation and direct Slack alerts routing.
• Links: 📁 Repository Target | 🌐 Architecture Documentation

  ┌───────────────────────┐      ┌───────────────────────┐      ┌───────────────────────┐
  │   Declarative IaC     │ ───> │  Zero-Trust Security  │ ───> │ Proactive Observability│
  │  Terraform / GitOps   │      │ Principle of Least PV │      │ Prometheus / Grafana  │
  └───────────────────────┘      └───────────────────────┘      └───────────────────────┘

• Declarative Infrastructure: If it is not in source control, it does not exist. All resources should be declared as code, validated in CI pipelines, and modified via GitOps.
• Zero-Trust Security: Secure by default. Least-privilege IAM rules, isolated VPC networking, target scheme checks, and database encryption are non-negotiable from Day 1.
• Proactive Observability: Monitoring is more than charts. Effective systems define and track concrete Service Level Indicators (SLIs), logging warnings before failures trigger paging.
• Focus on Developer Experience (DX): DevOps is about collaboration. Platform engineering tools should abstract infrastructure complexity, allowing software engineers to deploy without friction.

Note: The contribution snake is automatically updated daily. To configure this automation, see the pipeline configuration instructions in .github/workflows/snake.yml.

• Deep Learning Kubernetes: Working on scheduling mechanisms, network policy optimizations, and multi-cluster orchestrations.
• GitOps Delivery: Hardening Continuous Deployment patterns via ArgoCD and cloud secret store engines.
• Open Source Collaboration: Actively looking to contribute to CNCF projects (Kubernetes, Terraform providers, Helm charts) and developer-focused tooling. If you have an automation puzzle, let's solve it!

Stay tuned! I am preparing articles on the following topics:

• Reducing Cloud Ingestion Costs for High-Frequency Redis Queues
• Securing API Redirections against SSRF Attack Vectors
• Multi-Cloud Terraform Deployments with Shared Prisma Abstractions
• How I Prepared for the GCP Professional Cloud Architect Exam

• 🤖 I write scripts to automate tasks that take longer than 90 seconds. Yes, even sending email replies or scheduling my calendar.
• ☕ My code quality is directly proportional to high-grade coffee consumption.
• 🐧 I enjoy customizing Linux kernel compilation configurations for lightweight hypervisors in my spare time.
• ☁️ I am in a committed relationship with the command line interface (bash/tmux/vim).

Thank you for visiting my profile! 🚀

"The best code is no code. The next best code is that which can be automated."

© 2026 Pranav Saraswat