Abhishek Gupta

Deployed a food delivery app during live events. I worked as a DevOps engineer to set up the complete infrastructure using Terraform. It involved migrating Amazon EC2 apps to Docker images and deploying the pipeline via AWS CodeBuild, AWS CodeDeploy, and AWS CodeCommit.

With every change committed to GitHub, the release pipeline is triggered, pushing the updated change to development, staging, and production (via manual approval).

AWS ECS has two containers running via blue-green deployment with load balancers for each app. It was deployed securely on private subnets using proper rule setup in security groups.

Overall, the infrastructure used Terraform code to deploy VPCs, subnets, AWS ECS, task definition, Amazon Route 53, AWS CodePipeline, and more.

Set up a reporting workflow using AWS Lambda and AWS CloudWatch that runs daily on all AWS accounts added to AWS organizations to check for missing tags on all resources.

The main objective of this project was to replace the costly AWS Config. The project setup benefited the company as it became 100% reliable with zero downtime, and the execution cost was reduced to a few dollars a day.

Terraform was used to automate deployment and create all the AWS internal resources to simplify the upgrade process for software development.

Currently, there is no tool on the market to ensure that a security group is replicated across and region or any AWS account. During migration or disaster recovery, the security group must be created manually by comparing it to existing AWS EC2 instances or AWS services.

I worked as a freelancer on this project, which involved planning, architectural design, implementation, execution, and code deployment to AWS infrastructure.

The code was written in Python 3 using the Boto3 module, with proper error-handling checks. Each day, Lambda runs to collect information on the existing production and saves the information in an AWS S3 bucket. As the data is saved in AWS S3, it allows us to use it to restore any disaster recovery times system.

Using AWS CloudWatch, Cloud Monitoring, and CloudFormation, the execution and deployment of all the resources related to it, such as IAM roles and AWS S3 bucket policies for access, were configured.

I delivered all the components from development to production.

TECHNICAL-STYLE SUMMARY
Design and implement AIOps solutions using AI/ML to automate monitoring, anomaly detection, and remediation across cloud-native environments. Integrate with AWS, Terraform, Kubernetes, and CI/CD pipelines to enable predictive insights, self-healing, and resilient operations.

EXECUTIVE-STYLE SUMMARY
Leverage AIOps to transform IT operations by reducing incidents, accelerating root cause analysis, and automating remediation. Drive operational efficiency, system reliability, and business continuity through intelligent monitoring and proactive operations.

I worked as a DevOps Engineer on a 3-month project where I played a key role in architecting and implementing the infrastructure for a low-latency, real-time video-streaming platform. My primary focus was designing and optimizing a Kubernetes-based architecture that could support interactive streaming workloads with strict performance and latency requirements. This involved evaluating network paths, refining service communication patterns, and ensuring the platform’s components were tuned for sub-second responsiveness.

I collaborated closely with the existing DevOps and engineering teams to implement scalable cluster designs, optimize ingress and egress routing, and improve data flow for high-frequency video and event traffic. I introduced automation using Python/Bash to streamline provisioning, configuration, and deployment processes, ensuring consistent and reproducible environments across stages. Throughout the engagement, I also troubleshot networking bottlenecks, improved internal routing rules, and enhanced observability to track latency, packet flow, and real-time performance metrics.

I helped deliver a robust, scalable, and latency-optimized infrastructure foundation that significantly improved streaming reliability.