Open to Cloud, DevOps & Data Opportunities

Hi, I'm Someswararao Tarra

Cloud & DevOps Engineer|Data Science Professional

I build cloud infrastructure, automate workflows, troubleshoot Linux systems, and develop data-driven solutions using AWS, DevOps tools, Python, and machine learning.

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Someswararao Tarra Portrait
Active NowHyderabad, IN
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CloudDevOpsLinuxPythonData Science

My Journey & Mission

Aspiring IT Professional bridging Cloud Infrastructure and Data-Driven Decision Making.

Hi! I'm Someswararao Tarra, based in Hyderabad, Telangana, India. I recently completed my M.Sc. in Data Science (2025) from VIT Vellore (CGPA 8.60) and hold a B.Sc. in Mathematics, Physics & Computer Science from Padmavathi Degree College (CGPA 8.50).

I have hands-on experience in Linux Administration, Bash Scripting, Git/GitHub, AWS fundamentals, Python, SQL, Data Analytics, and Machine Learning. During my internship at SentinelGuard AI, I engineered ML models that improved predictive accuracy by 15% and processed 5M+ records using Python and SQL.

I'm passionate about automation, cloud technologies, cybersecurity, and data-driven decision-making — building systems that host, process, and secure data at scale.

Seeking entry-level opportunities in Linux Administration, DevOps, SOC Analyst, or Data Science roles.

Location

Hyderabad, Telangana, India

Specialization

Cloud / DevOps / Data Science / ML

M.Sc. Data Science — VIT Vellore

Completed M.Sc. in Data Science in 2025 from VIT Vellore (CGPA 8.60), building a strong foundation in statistics, ML, and programming.

Cloud, DevOps & Linux Enthusiast

Hands-on with AWS (EC2, VPC, RDS, IAM, Route 53, ACM, CloudFront, S3, EFS, EBS), Linux administration, Bash scripting, and automation pipelines.

Data-Driven Developer

Proficient in Python, R, SQL, Pandas, NumPy, Power BI, and ML frameworks — delivering predictive models and data insights from real datasets.

Technical Competencies

AWS Cloud

AWS EC2VPCAmazon RDSIAMRoute 53Certificate Manager (ACM)CloudFrontAmazon S3Amazon EFSAmazon EBSElastic Load Balancer (ALB)Auto ScalingCloudWatchInternet GatewayNAT GatewayRoute TablesSecurity GroupsNACL

DevOps & Automation

DockerKubernetesTerraformAnsibleCI/CD PipelinesGitHub ActionsJenkinsGitGitHubPrometheusGrafanaInfrastructure Troubleshooting

Linux & Scripting

Linux AdministrationBash ScriptingShell AutomationSSHSCPFile PermissionsProcess ManagementDisk ManagementNetworkingsystemctlLog AnalysisTroubleshooting

Programming

PythonR ProgrammingSQLBash

Data Science & Machine Learning

PandasNumPyScikit-learnTensorFlowKerasTime Series AnalysisMachine LearningDeep LearningData VisualizationStatistical Analysis

Cloud & DevOps Labs

AWS VPC Architecture

LAB-01
Problem Statement

Recruiters and applications require secure network isolation patterns where backend infrastructure is hidden from public access while maintaining controlled internet gateways.

Lab Architecture / Approach

Designed a VPC with public and private subnets across multiple availability zones, route tables, an Internet Gateway (IGW) for public servers, and a NAT Gateway for secure outbound private subnet routing.

Key Learning

Understood public vs. private subnets, routing tables, and the role of NAT Gateways in preventing incoming traffic to private instances while permitting outgoing requests.

AWS VPCSubnetsRoute TablesInternet GatewayNAT Gateway
View Lab Code

Private EC2 Connectivity

LAB-02
Problem Statement

Direct SSH access to private subnet instances poses severe security risks and exposes resources to public penetration attempts.

Lab Architecture / Approach

Configured secure connectivity models utilizing Bastion Hosts (Jump Boxes) and AWS Systems Manager Session Manager, restricting port access via Security Groups.

Key Learning

Mastered multi-hop SSH routing configurations, transit rules, and IAM permissions required to execute secure, keyless SSM-based shell access.

AWS EC2Security GroupsSSH Key ManagementSSM Session Manager

VPC Peering Lab

LAB-03
Problem Statement

Applications residing in separate isolated AWS networks (VPCs) need to exchange data securely without traversing the public internet.

Lab Architecture / Approach

Built VPC peering connectivity between two distinct VPCs. Configured corresponding route tables, resolved CIDR block conflicts, and security rules.

Key Learning

Learned how CIDR blocks overlap checks work, how to create peering requests and accept them, and how route tables handle trans-VPC network routes.

VPC PeeringCIDR blocksRoute TablesSecurity Groups

Load Balancer & Health Checks

LAB-04
Problem Statement

Ensuring high availability and load distribution across multiple web servers while isolating unhealthy node failures.

Lab Architecture / Approach

Configured target groups and an Application Load Balancer (ALB) to handle incoming requests. Established custom HTTP path checks to run regular health monitors.

Key Learning

Acquired deep understanding of load balancing layers (Layer 7), path-based routing, target group registrations, and automatic traffic redirection from failing instances.

AWS ALBTarget GroupsHealth ChecksSecurity Groups

Linux Server Troubleshooting

LAB-05
Problem Statement

Servers routinely crash due to disk capacity exhausts, permission blocks, high CPU/Memory load spikes, or listening port conflicts.

Lab Architecture / Approach

Simulated and successfully resolved real-world production outages: diagnosing SSH failures, high CPU/memory spikes, disk-full bottlenecks, systemd service crashes, and port conflicts.

Key Learning

Learned to triage system limits, read service logs via journalctl, isolate disk bloats, and identify process port usage dynamically to restore operation.

Linux Administrationsystemctldf / dutop / htopnetstat / lsofchmod / chown

Shell Automation

LAB-06
Problem Statement

Repetitive system maintenance, log rotation, and server backups consume manual hours and are prone to human operational error.

Lab Architecture / Approach

Created production-ready Bash scripts that automate system health checks, log file rotations, folder backups, conditional process checks, and cron scheduling.

Key Learning

Gained proficiency in write-safe bash scripting using error handling (set -e), environment variables, conditional checks, loop structures, and automated scheduling.

Bash ScriptingShell UtilitiesCron JobsProcess Automation

AWS ECS Fargate CI/CD Pipeline (Terraform)

LAB-07
Problem Statement

Manual container deployments lead to configuration drift, deployment downtime, and brittle environments without reproducible infrastructure or automated CI/CD.

Lab Architecture / Approach

Built modular Terraform IaC to provision multi-AZ VPC, ALB, and serverless AWS ECS Fargate. Automated GitHub webhook-triggered Jenkins CI/CD to build Docker images, push to Amazon ECR, and orchestrate zero-downtime rolling deployments.

Key Learning

Mastered end-to-end Infrastructure as Code with reusable modules & S3 remote state, Dockerized deployments, automated Jenkins webhooks, and ECS rolling updates.

TerraformAWS ECS FargateDockerJenkinsAmazon ECRALBCloudWatch

Featured Projects

Academic and personal projects demonstrating applied Data Science, Machine Learning, and Cloud Engineering skills.

Machine Learning / Deep Learning

Disease & Pest Detection in Coffee Leaves using Efficient DET Algorithm & CNN

Designed and deployed a CNN with the Efficient DET algorithm achieving 96.71% accuracy for early disease detection in coffee plants. The model enables early intervention strategies that minimize crop losses at scale.

  • 96.71% test accuracy on disease classification
  • Deployed CNN + Efficient DET pipeline
  • Enables early-stage crop loss prevention
PythonTensorFlowKerasCNNEfficient DETOpenCVNumPy
GitHub CodeView Project (Code Only)
Data Science / Deep Learning

National GDP Prediction using Time Series, Deep Learning & Hybrid Models

Engineered a hybrid ARIMA-GRU model to forecast national GDP with a 37% reduction in forecast error (RMSE 122, R² 0.9998). Applied wavelet transforms and outlier smoothing to optimize data quality before modelling.

  • 37% reduction in forecast error vs. traditional methods
  • RMSE: 122, R²: 0.9998
  • Hybrid ARIMA-GRU architecture
PythonTensorFlowKerasARIMAGRUTime SeriesPandasstatsmodels
GitHub CodeView Project (Code Only)
Data Science / Machine Learning

Cryptocurrency Price Prediction using Time Series Analysis

Built and compared ARIMA and LSTM forecasting models to predict volatile cryptocurrency price trends using historical exchange data. Enhanced model reliability by 18% through iterative architecture improvements.

  • 18% improvement in prediction reliability
  • ARIMA vs LSTM model comparison
  • Historical price trend forecasting
PythonPandasARIMALSTMScikit-learnMatplotlibSeaborn
GitHub CodeView Project (Code Only)
AWS / DevOps

AWS Three-Tier Web Architecture

Architected and deployed a highly available, secure, and resilient 3-tier web architecture on AWS across multiple Availability Zones, implementing Web, Application, and Database tier isolation.

  • Multi-AZ VPC with public, private app, and isolated DB subnets across 2 Availability Zones
  • CloudFront CDN & S3 static frontend with SSL/TLS termination via AWS Certificate Manager (ACM) & Route 53 DNS
  • App Tier EC2 Auto Scaling Groups behind ALB with Amazon EFS & EBS for scalable state & persistent storage
  • Database Tier Multi-AZ Amazon RDS with automated failover, IAM authentication, and Security Group / NACL isolation
AWS EC2VPCAmazon RDSIAMRoute 53ACMCloudFrontAmazon S3EFSEBSALBAuto Scaling
AWS / DevOps

AWS VPC with Servers in Private Subnets & NAT Gateway

Designed and implemented a secure AWS network infrastructure featuring a custom VPC, public and private subnets, NAT Gateways for outbound internet connectivity, and isolated application servers, based on AWS official guidelines.

  • Configured NAT Gateways to enable private subnet resources to reach the internet securely
  • Implemented robust network isolation using private subnets for application servers
  • Set up custom route tables, security groups, and internet gateways for strict access control
AWSVPCNAT GatewaySubnetsRoute TablesEC2Security Groups
AWS / DevOps

AWS ECS Fargate CI/CD Pipeline using Terraform

Engineered an end-to-end automated CI/CD pipeline deploying containerized microservices to AWS ECS Fargate using modular Terraform Infrastructure as Code (IaC), Jenkins, and Amazon ECR.

  • Modular Terraform IaC provisioning custom multi-AZ VPC, subnets, NAT Gateways, and S3 remote state backend
  • Automated Jenkins pipeline with GitHub webhooks for Docker builds, linting, and automated Amazon ECR image push
  • Serverless container deployment on Amazon ECS Fargate with zero-downtime rolling task definition updates
  • Application Load Balancer (ALB) traffic routing, target group health checks, and AWS CloudWatch logging
TerraformAWS ECS FargateDockerJenkinsAmazon ECRALBAWS VPCCloudWatch

Certifications & Goals

Active Certifications

Oracle Cloud Infrastructure 2025 Certified AI Foundations Associate

Oracle Cloud Infrastructure (OCI)

Issued: 12 October 2025
Credential ID: [Oracle Credential ID]
Verify Credential

Currently Preparing For

AWS Certifications

Amazon Web Services

Actively studying for AWS certifications (such as Cloud Practitioner or Solutions Architect Associate) to validate practical networking, IAM, VPC, and EC2 experience.

Target Date:In Progress

Academic & Career History

Data Science Intern

Oct 2024 – Nov 2024
SentinelGuard AI
VIT, Vellore (Internship)
  • Developed and integrated a custom CNN model on SentinelGuard AI platforms, improving prediction accuracy by 15% across real-world testing environments.
  • Managed preprocessing and feature extraction on structured datasets containing 5M+ sensor events using Python, pandas, and SQL databases.
  • Collaborated in design pipelines to write automation test scripts validating local server processes and deployment containers.

Master of Science (M.Sc.) in Data Science

2023 – 2025
Vellore Institute of Technology (VIT), Vellore
Tamil Nadu, India
CGPA: 8.60

Key Core Coursework

Machine Learning & Pattern Recognition
Deep Learning & Neural Networks
Time Series Analysis & Forecasting
Statistical Methods & Hypothesis Testing
Database Management Systems (SQL)
Data Structures & Algorithm Fundamentals

Bachelor of Science – Mathematics, Physics & Computer Science

2019 – 2022
Padmavathi Degree College, Narasannapeta
Andhra Pradesh, India
CGPA: 8.50

Board of Intermediate Education

2017 – 2019
Santha Junior College, Narasannapeta
Andhra Pradesh, India
Andhra Pradesh Board

Board of Secondary Education

2016 – 2017
ZP High School, Peddagugram
Andhra Pradesh, India
Andhra Pradesh Board

Building In Public

Let's Build Something Meaningful

Get In Touch

I'm open to opportunities in Cloud Engineering, DevOps, Linux Systems Administration, Infrastructure Operations, Data Science, and Machine Learning engineering roles. Drop a message or connect through social channels.

LocationHyderabad, Telangana, India
Connect Directly
* Messages are delivered directly to someshtarra@gmail.com.