SYSTEMS ONLINE•IST (UTC+5:30)
Bengaluru, Karnataka, India
Software & Systems

Ankush A

[Developer & Systems Builder]

Building software, exploring distributed systems, and crafting reliable cloud architectures. Passionate about clean code, Linux environments, latency optimization, and systems that feel snappy and deterministic.

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Background in Physics and Mathematics with practical experience developing full-stack web applications, containerized services, and automated delivery pipelines. Fascinated by systems internals, latency optimization, and tools that turn complexity into simple, deterministic code.

#SoftwareEngineering#DistributedSystems#Python#Kubernetes#Docker#Linux

[01] // FEATURED_PROJECTS

Select systems architectures, APIs, and software builds.

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shipped19 tests • <2ms cache
2026-08

Production-Grade AI Question-Answering Platform & DevOps Architecture

Architected and containerized a multi-tier AI Q&A API with Kubernetes autoscaling, Redis caching, multi-provider LLM failover, Prometheus metrics, and zero-downtime migration designs.

PythonFastAPIDockerKubernetesRedisPostgreSQLPrometheusJWT
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shippedMulti-AZ • Auto-scaled
2026-06

AWS Production-Grade Web Application Deployment

High-availability, fault-tolerant AWS network across 2 Availability Zones featuring custom VPC, ALB, Auto Scaling Group in private subnets, and secure Bastion host.

AWSVPCEC2ALBAuto ScalingSecurity GroupsPythonLinux
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shippedServerless • 100% IaC
2026-04

Serverless News Aggregator

End-to-end serverless RSS ingestion and distribution pipeline using AWS Lambda, EventBridge, DynamoDB, API Gateway, S3, and CloudFormation.

AWS LambdaEventBridgeDynamoDBAPI GatewayS3CloudFormationPython
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[02] // EXPERIENCE

Industry Background

Cloud & DevOps Intern

Aicera Systems Pvt. Ltd. • Bengaluru, India

Mar 2026 – Sep 2026
  • ›Cost Optimization & FinOps: Reduced a client's overall cloud infrastructure expenses by 30% by right-sizing compute resources based on AWS Compute Optimizer data.
  • ›Utilization Telemetry: Tracked real-time performance and utilization metrics with Amazon CloudWatch to eliminate idle and over-provisioned capacity.
  • ›Automated Pipelines: Built and managed CI/CD pipelines using GitHub Actions and ArgoCD to deploy Terraform-managed infrastructure, cutting manual deployment overhead by ~50%.
  • ›Environment Scheduling: Automated deployment schedules so development resources remained active only during work hours, reducing idle compute runtime by ~70%.

[03] // EDUCATION_&_CREDENTIALS

Foundations
DegreeGraduated 2025

BSc in Physics and Mathematics

Sahyadri Science College, Kuvempu University

Rigorous mathematical modeling, numerical analysis, classical physics, and problem-solving foundations.

Shivamogga, Karnataka
CredentialIssued Jun 2026

AWS Certified Cloud Practitioner

Amazon Web Services (AWS)

Validated understanding of cloud infrastructure, core services, security compliance, and economics.

[04] // TECHNICAL_TOOLKIT

Core Proficiencies

Languages & APIs

Python 3, FastAPI, Bash, TypeScript, REST APIs, pytest

Containers & Systems

Docker, Kubernetes (HPA, Ingress), Linux Administration, Nginx

Infrastructure & CI/CD

AWS (VPC, EC2, ALB, Lambda), Terraform, GitHub Actions, ArgoCD

Data & Observability

PostgreSQL, Redis, DynamoDB, Prometheus, CloudWatch