Cloud DevOps & Automation Engineer with 11+ Years

Lakshmi Narayanareddy M S

DevOps/Cloud Engineer

Mail Id: *******.*****************@******.** Phone: +1-505-***-****

LinkedIn: LinkedIn

PROFESSIONAL SUMMARY

11+ years of IT experience across AWS, Azure, and GCP, designing and managing cloud-native and hybrid infrastructures for secure and reliable applications.

Enhanced CI/CD pipelines and developed new automation workflows using Jenkins, uDeploy, Groovy, and PowerShell scripting to streamline build and deployment processes for API management utilities.

Integrated IBM API Connect CLI for automating API product deployment across environments, ensuring standardized release governance and reduced manual intervention.

Implemented Splunk-based observability dashboards for CI/CD pipeline health, troubleshooting, and performance visibility.

Experienced in the Non-Healthcare Insurance domain, collaborating closely with DevOps governance teams to align automation standards and operational best practices.

Automated provisioning and configuration using Terraform, CloudFormation, and ARM templates, reducing manual effort and deployment time.

Built and optimized serverless applications with AWS Lambda, Azure Functions, and GCP Functions to enhance scalability and cost efficiency.

Designed and implemented CI/CD pipelines with Jenkins, GitHub Actions, Azure DevOps, and GCP Cloud Build, integrating DevSecOps practices (SonarQube, security scans, code quality).

Experienced in designing and managing enterprise-scale CI/CD pipelines using Octopus Deploy, enabling automated multi-environment releases with zero-downtime deployment strategies.

Implemented Octopus Deploy for release orchestration across Dev, QA, UAT, and Production environments, improving release consistency, compliance, and rollback efficiency.

Developed and optimized Node.js microservices and backend automation APIs integrated with AWS/Azure/GCP services, enabling scalable CI/CD workflows, cloud provisioning, and event-driven automation using Express.js, async patterns, Docker, and Kubernetes.

Implemented full-stack observability using Datadog APM, Logs, Metrics, Dashboards, and Tracing, integrating with CloudWatch, Azure Monitor, GCP Ops Suite, and Prometheus to improve visibility, detect performance bottlenecks, and reduce MTTR across distributed systems.

Integrated enterprise CI/CD solutions using Atlassian Bamboo and Concourse CI, automating complex build, test, and deployment workflows across multi-cloud environments (AWS, Azure, GCP).

Optimized CI/CD pipeline performance and reliability by incorporating Concourse CI’s event-driven architecture and Bamboo’s build agents for parallelized, version-controlled deployments with rollback support and artifact promotion between environments.

Expertise in Kubernetes (AKS, EKS, GKE) and Docker, with deployments managed using GitOps (ArgoCD), release automation with Helm charts, and scaling/replica scheduling.

Developed monitoring and observability frameworks with CloudWatch, Azure Monitor, GCP Operations Suite, Prometheus, and Grafana, ensuring high system availability.

Developed high-performance backend automation tools and microservices using Rust, focusing on concurrency, safety, and performance optimization for DevOps workflows.

Implemented modern identity and access management (IAM) frameworks using PlainID, OPA (Open Policy Agent), and Okta, driving policy-based authorization (PBAC/ABAC) for microservices and APIs across multi-cloud environments.

Integrated Styra DAS for centralized policy lifecycle management, ensuring consistent enforcement across Kubernetes, Terraform, and CI/CD pipelines.

Designed and deployed reverse proxy architectures (NGINX, Envoy) for secure traffic routing, authentication, and SSO integration with Okta and PlainID for API and service protection.

Automated compliance validation using OPA Gatekeeper and Styra DAS within Kubernetes clusters, enhancing visibility and policy compliance.

Collaborated with security teams to align PBAC frameworks with enterprise identity governance, streamlining role-based and attribute-based access controls across AWS, Azure, and GCP workloads.

Experienced in Siebel CRM deployment automation, integration with API management platforms, and CI/CD pipelines for CRM-related workloads.

Skilled in front-end and automation frameworks including TypeScript, Cypress, and Playwright, enabling reliable UI, API, and integration test automation across microservice architectures.

Experience with GraphQL for building scalable API query layers, schema design, and integrating federated services across distributed systems.

Implemented observability and root-cause analysis workflows using BigPanda, Mezmo (LogDNA), and Nucleus, improving incident response, monitoring, and operational intelligence.

Hands-on experience in developing reusable test components using TypeScript, enhancing code maintainability and CI/CD integration.

Hands-on experience in LoadRunner for performance, stress, and scalability testing across microservices and API-based applications.

Built Rust-based CLI utilities for multi-cloud infrastructure management, integrating with AWS SDK, Azure SDK, and GCP APIs to automate provisioning, policy validation, and compliance checks.

Implemented cloud security and identity management solutions with AWS IAM, Azure AD, and GCP IAM, meeting compliance and governance standards.

Automated cloud operations and workflows using Python, Shell scripting, AWS CLI, Azure CLI, and GCP SDK.

Configured SonarQube quality profiles and rules for Java, Python, and Terraform codebases to ensure consistent security, maintainability, and reliability standards.

Automated multi-environment deployments using IBM UrbanCode Deploy (uDeploy) integrated with Jenkins and GitHub for consistent and auditable releases.

Developed and maintained Batch and Perl scripts to automate configuration, log analysis, and routine operational tasks, improving efficiency and reliability.

Streamlined legacy automation scripts into modern CI/CD workflows, enhancing deployment speed and reducing manual intervention across environments.

Delivered data integration and transformation using Informatica IICS (CDI, CAI, DQ, Intelligent Structure Parser) for enterprise data needs.

Built dashboards by integrating Databricks outputs with monitoring tools for real-time insights and anomaly detection

Integrated Databricks with CI/CD pipelines for automated deployment of data workflows

Designed and integrated Databricks-based data processing pipelines with AWS S3 for log analytics and observability workloads

Skilled in writing and maintaining unit test cases using frameworks such as Jest, Postman, Mocha, and Chai to ensure code quality and reliability.

Configured and managed Databricks clusters for scalable data processing and monitoring use cases

Experienced in developing and deploying MERN stack applications (MongoDB, Express.js, React, Node.js) with CI/CD automation, containerization (Docker, Kubernetes), and cloud-native integrations.

Hands-on experience in building cloud-native microservices and CLI tools using Go (Golang) for high-performance, concurrent applications.

Developed automation frameworks and cloud SDK utilities in Go, integrating with AWS, Azure, and GCP APIs.

Implemented distributed systems and API services in Go, improving performance, scalability, and resource efficiency.

Built and optimized serverless applications with AWS Lambda, Azure Functions, and GCP Functions to enhance scalability and cost efficiency.

Developed PySpark jobs in Databricks notebooks for transforming large-scale application and infrastructure logs

Designed and implemented CI/CD pipelines with Jenkins, GitHub Actions, Azure DevOps, and GCP Cloud Build, integrating DevSecOps practices (SonarQube, security scans, code quality).

Configured and managed Kafka clusters with security (authentication, authorization) and implemented RabbitMQ for enterprise-grade messaging.

Managed application server clusters (Tomcat, WebLogic), optimized DNS traffic routing with Route53, and supported load balancing and auto-scaling.

Strong experience with SQL and NoSQL databases including MySQL, PostgreSQL, Oracle, SQL Server, DynamoDB, MongoDB, Cassandra, Redis, and CouchDB.

Skilled in build and release engineering using Maven, ANT, NPM, and Yarn to build deployable artifacts (WAR/EAR, Node.js apps, iOS/Android apps).

EDUCATION:

Bachelor’ s in Electronics and Communication Engineering from Lovely Professional University in 2011.

Master’ s in computer science from Concordia University in 2014.

AREAS OF EXPERTISE

•Cloud Platforms: AWS Cloud, Microsoft Azure, Google Cloud Platform (GCP)

•Compute: EC2, Auto Scaling, ELB, Azure Virtual Machines, AKS, Compute Engine, GKE, Cloud Functions, Azure Functions

•Storage: S3, EBS, Azure Blob Storage, Azure File Storage, Cloud Storage, Persistent Disks

•Networking: VPC, Elastic Load Balancer, Azure Virtual Network, Azure Front Door, Cloud Load Balancing

•Security & Identity: IAM, Security Groups, CyberArk, Defender, Azure AD, Key Vault, Azure Command Center, Cloud IAM, Cloud KMS, Security Command Center

•Operating Systems: Linux, Windows, QNX OS

•Monitoring & Logging: CloudWatch, CloudTrail, Azure Monitor, App Insights, Cloud Monitoring, Cloud Logging

•Database: RDS, DynamoDB, Azure SQL, Azure Cosmos DB, Cloud SQL, Firestore, BigQuery

•Container Management: ECS, EKS, Azure Container Instances, AKS, GKE, Cloud Run, Artifact Registry, ACR

•Serverless: AWS Lambda, Azure Functions, Cloud Functions

•CI/CD Tools: AWS CodePipeline, CodeBuild, Azure DevOps, GitHub Actions, Cloud Build, Artifact Registry

•Infrastructure as Code: CloudFormation, Terraform, ARM Templates, Deployment Manager

•Monitoring Tools: CloudWatch, CloudTrail, Azure Monitor, App Insights, Operations Suite (Stackdriver)

•Configuration Management: Ansible, Azure Automation, Deployment Manager

•Artifact Management: ECR, CodeArtifact, Azure Container Registry, Jfrog, Nexus, Artifact Registry

•Logging & Observability: CloudWatch Logs, AWS X-Ray, Azure Monitor, Log Analytics, Application Insights, Cloud Logging, Cloud Trace

•Version Control: CodeCommit, GitHub, BitBucket, Azure Repos, Cloud Source Repositories

•Programming Languages: Python, Java, Rust, Go, Shell Scripting, C, C++

•Monitoring & Management: CloudWatch, AWS Config, Azure Monitor, Log Analytics, Cloud Monitoring, Cloud Logging

•Collaboration Tools: Confluence, SharePoint, Azure Boards, ServiceNow, Google Workspace, Jira

CERTIFICATIONS:

●Microsoft Certified Azure Administrator

●Certified Kubernetes Administrator

●AWS Developer – Expert

WORK EXPERIENCE:

Client: Fidelity Investments, Remote Sep 2023 to Present

Role: Sr DevOps Engineer

Delivered enterprise-grade multi-cloud solutions across Azure, AWS, and GCP, leveraging services like Azure Monitor, CloudWatch, and GCP Operations Suite with ELK/Databricks integrations to enhance observability and reduce MTTR.

Engineered robust CI/CD pipelines using Azure DevOps, GitHub Actions, Jenkins, and Harness (multi-stage, canary rollouts), integrating Terraform, CloudFormation, Deployment Manager, and Ansible for automated infrastructure provisioning.

Developed Groovy and Python automation frameworks to streamline artifact versioning, REST API integrations, compliance enforcement, and microservice onboarding, reducing manual intervention and increasing release velocity.

Designed and developed Go-based microservices for cloud resource provisioning, monitoring, and compliance enforcement, reducing latency and improving scalability.

Developed microservices and automation utilities using TypeScript, ensuring type safety, code maintainability, and improved development workflow across CI/CD pipelines.

Built and deployed Node.js-based microservices for automation, data processing, and API orchestration; containerized using Docker, deployed to AKS/EKS/GKE using Helm/ArgoCD, and integrated with CI/CD pipelines for zero-downtime releases.

Integrated Datadog APM and Infrastructure Monitoring with Kubernetes workloads and cloud-native microservices to track latency, errors, resource utilization, and service health; created real-time dashboards and alerts that improved troubleshooting efficiency and on-call response times.

Built concurrent automation tools in Go to manage multi-cloud workloads, leveraging goroutines and channels for efficiency.

Built and deployed containerized applications using Docker and Kubernetes (AKS, EKS, GKE), implementing GitOps (FluxCD, ArgoCD, Istio) and Helm-based strategies for secure, repeatable, and scalable application delivery.

Implemented end-to-end monitoring for high-traffic web applications using Datadog, Dynatrace, Prometheus, Grafana, Splunk, and CloudWatch—enabling real-time visibility into performance, latency, and user experience.

Configured APM, distributed tracing, log pipelines, and synthetic monitors for web and API workloads across Kubernetes (AKS/EKS/GKE), improving issue detection and reducing MTTR by 40%.

Designed and implemented Octopus Deploy for application release automation, managing multi-tenant deployments across Dev, QA, UAT, and Production environments.

Standardized Octopus Deploy deployment templates and variables, reducing deployment failures by 40% and improving deployment consistency across microservices.

Designed and integrated Databricks-based data processing pipelines with AWS S3 for log analytics and observability workloads

Integrated Octopus Deploy with Azure DevOps and Jenkins pipelines to automate build, test, and release workflows for Kubernetes and VM-based applications.

Used Octopus Deploy for blue-green and canary deployments, minimizing downtime and improving production stability during critical releases.

Automated environment configurations and secret management using Octopus variables, Key Vault, and role-based deployment permissions.

Built advanced dashboards and automated alerting for HTTP errors, response times, database performance, memory/CPU hotspots, and service availability—enhancing application reliability and on-call readiness.

Implemented cloud-native security practices by integrating AWS IAM, CyberArk, HashiCorp Vault, SSL/KMS, and Packer into CI/CD workflows, embedding dependency scanning and policy validation to enforce DevSecOps standards.

Developed Rust-based microservices and CLI tools to automate cloud provisioning, compliance validation, and resource optimization across AWS, Azure, and GCP.

Integrated SonarQube into multi-cloud CI/CD pipelines (Azure DevOps, Jenkins, GitHub Actions, Harness) to enforce code quality and security gates across microservices and IaC templates (Terraform, CloudFormation).

Integrated PlainID and Okta with microservices for dynamic authorization, enabling centralized access policy enforcement across CI/CD and API layers.

Implemented OPA and Styra DAS for policy governance and compliance-as-code within Kubernetes (AKS/EKS/GKE), ensuring consistent security posture across environments.

Designed and implemented CI/CD pipelines leveraging Bamboo and Concourse CI for microservice orchestration, enabling automated builds, canary deployments, and security scanning within multi-cloud environments (Azure, AWS, GCP).

Integrated Bamboo with Bitbucket and SonarQube to enforce code quality gates and streamline continuous delivery workflows, reducing deployment time by 40%.

Developed reusable Concourse pipelines for Terraform and Ansible provisioning, integrating with GitOps tools like ArgoCD for fully automated infrastructure delivery.

Implemented pipeline observability and alerting via Prometheus, Grafana, and BigPanda, ensuring proactive detection of CI/CD performance bottlenecks.

Deployed reverse proxy and API gateway security layers using NGINX/Envoy integrated with Okta SSO and PlainID for token-based access and session validation.

Automated policy lifecycle management and audit trail generation using Styra DAS APIs, improving compliance reporting and DevSecOps maturity.

Partnered with IAM and platform teams to design PBAC and ABAC models aligned with enterprise Zero Trust initiatives.

Configured SonarQube quality profiles and security rules for Java, Python, and Go-based applications, ensuring compliance with DevSecOps best practices.

Integrated Siebel CRM APIs within CI/CD workflows to automate configuration updates and data synchronization across environments.

Conducted LoadRunner-based performance testing for API-driven microservices, ensuring scalability under peak loads.

Automated SonarQube scan triggers within pipelines to identify vulnerabilities early in the SDLC and reduce technical debt by over 35%.

Integrated Rust applications with Terraform and Ansible automation workflows to enhance infrastructure reliability and execution speed.

Built and deployed containerized Rust workloads on Kubernetes with Helm and ArgoCD, ensuring observability via Prometheus and Grafana.

Implemented IBM UrbanCode Deploy (uDeploy) pipelines to automate multi-tier application deployments, integrating with Jenkins, GitHub, and ServiceNow for seamless release management.

Enhanced and optimized CI/CD pipelines using Jenkins, uDeploy, and Groovy scripting to automate the deployment of API management utilities.

Developed and maintained PowerShell scripts for build, configuration, and environment automation within pipeline stages.

Integrated IBM API Connect CLI for packaging and deploying API products, ensuring consistent governance across multi-cloud environments.

Collaborated with internal DevOps and platform engineering teams to align automation with organizational standards and best practices.

Built Cypress end-to-end automation frameworks integrated with GitHub Actions/Azure DevOps pipelines for regression validation and release gating.

Designed reusable test suites covering UI flows, API contracts, and auth workflows, reducing manual testing effort by 40%.

Improved observability by integrating Splunk dashboards and alerts for pipeline metrics, deployment success rate, and anomaly detection.

Automated error handling, notification, and audit trails to enhance deployment visibility and reduce troubleshooting time.

Partnered with application teams within the Non-Healthcare Insurance domain to streamline release automation and API deployment workflows.

Implemented Playwright for cross-browser automation testing (Chromium, WebKit, Firefox), integrated with Azure DevOps CI/CD for automated smoke and regression pipelines.

Configured parallel execution and distributed test runners to reduce execution time by 60%.

Utilized CMake and Bazel for efficient dependency management and build automation in CI/CD pipelines.

Modernized legacy automation frameworks by integrating Perl and Batch scripting within CI/CD workflows, enabling faster and more reliable deployments across cloud and on-prem environments.

Migrated legacy workloads to modern IaaS platforms, including Azure VMs, AWS SMS, and GCP Migrate, ensuring secure configurations, encrypted storage, and optimized performance across hybrid environments.

Integrated Nucleus Security Platform into CI/CD workflows for vulnerability scanning, SBOM generation, compliance reporting, and remediation tracking.

Automated vulnerability risk scoring and dashboarding to enforce DevSecOps governance policies.

Led SDK Central modernization at Fidelity, enabling GitHub-based workflows, Python/CI automation, and troubleshooting support for development teams, significantly improving developer productivity and release efficiency.

Integrated ServiceNow with DevOps pipelines, synchronizing change requests and approvals with GitHub/Azure pipelines for governance, traceability, and automated release compliance.

Collaborated with AI/ML teams to embed Azure Cognitive Search and GCP AI services into ServiceNow workflows, automating knowledge retrieval and accelerating resolution times.

Integrated Go SDKs with AWS, Azure, and GCP for automated infrastructure provisioning and policy validation.

Developed CLI utilities in Go for DevOps teams, streamlining deployments, debugging, and observability across Kubernetes clusters.

Wrote unit and integration tests in Go to ensure code quality, reliability, and smooth CI/CD integration.

Designed and deployed distributed messaging & data systems, including RabbitMQ (Chef-based migration from IBM MQ), Kafka clusters, Redis/Memcached, and SQL/NoSQL databases, ensuring high availability and scalable data flows.

Implemented SRE practices such as SLIs, SLOs, and error budgets, balancing reliability with innovation while reducing operational risk during change management.

Designed and implemented MERN stack applications with RESTful APIs and React-based frontends, integrated into CI/CD pipelines for automated testing, security scanning, and cloud-native deployments.

Containerized and deployed Node.js + MongoDB services in Kubernetes (AKS/EKS/GKE), ensuring scalability, observability, and high availability with Prometheus and Grafana monitoring.

Environment: Azure, AWS, GCP, Azure DevOps, AWS CodePipeline, Rancher, GCP Cloud Build, Active Directory, Azure CLI, AWS CLI, GCP gcloud, ACS, AKS, EKS, GKE, Datadog, Git, Maven, Harness, QNX OS, CMake, Bazel, Splunk, Nagios, Java/J2EE, Linux, Cosmos DB, RDS, Cloud SQL, RedHat, Python, Prometheus, Grafana, Alertmanager,Terraform, PlainID, Open Policy Agent (OPA), Styra DAS, Okta, reverse proxy, NGINX, Envoy, PBAC, ABAC, policy-as-code, Zero Trust, access management, authorization, Kubernetes admission control, compliance-as-code,Ansible, Kubernetes (EKS/AKS/GKE), Jenkins, ELK, Ubuntu, PostgreSQL, Octopus Deploy,RabbitMQ, Microsoft SQL Server, NuGet, HashiCorp Vault, SonarQube, CyberArk, Data Factory, AWS Lambda, Azure Functions, Redis, GCP Cloud Functions, Docker, DORA metrics, Kafka, GitOps, Kubernetes, Helm, Function Apps, Web Apps, Logic Apps, IAM, Windows PowerShell, JSON, GitHub Actions, Ansible, YAML.

Client: LTIMindtree, Seattle, WA Aug 2021 to Sep 2023

Role: SRE Engineer

Led multi-cloud SRE teams and contractor resources across AWS, Azure, and GCP, resolving incidents efficiently and improving MTTR by 30%.

Automated cloud infrastructure provisioning and management using Terraform, CloudFormation, GCP Deployment Manager, Ansible, and Python, reducing manual deployment time by 50%.

Deployed and managed multi-cloud Kubernetes clusters (AKS, EKS, GKE) with Helm and ArgoCD, integrated CI/CD pipelines via GitLab/GitHub for scalable AI/ML workloads.

Used microservices that were developed using Spring Boot and deployed on Amazon EC2 container services using AWS admin console.

Implemented C/C++ modules for performance-critical data collection and observability functions, integrated with Prometheus and ELK-based monitoring stacks.

Collaborated with system engineering teams to automate real-time operations on QNX OS for edge devices and IoT monitoring within cloud-native environments.

Migrated legacy Jenkins workflows to Bamboo and Concourse CI, improving CI/CD scalability, fault tolerance, and compliance alignment with enterprise DevSecOps standards.

Built Concourse resource types and custom tasks using Python and Go for automating container builds, Helm chart validation, and artifact promotion workflows.

Integrated Databricks with ELK/Splunk pipelines to enhance observability and centralized logging

Designed centralized log pipelines using ELK/Mezmo/Splunk integrated with Kubernetes workloads, drastically improving debugging speed and root-cause identification for web applications.

Built real-time dashboards and synthetic monitors to track web application availability, API performance, CDN latency, SSL expiry, and user journey failures across global regions.

Automated data ingestion into Databricks from cloud storage (S3/Azure Blob).

Automated alerting strategies using Datadog, Dynatrace, CloudWatch Alarms, Azure Monitor Alerts, and GCP Cloud Monitoring to detect anomalies, reduce false positives, and improve on-call responsiveness.

Built and deployed Node.js-based microservices for automation, data processing, and API orchestration; containerized using Docker, deployed to AKS/EKS/GKE using Helm/ArgoCD, and integrated with CI/CD pipelines for zero-downtime releases.

Integrated Datadog APM and Infrastructure Monitoring with Kubernetes workloads and cloud-native microservices to track latency, errors, resource utilization, and service health; created real-time dashboards and alerts that improved troubleshooting efficiency and on-call response times.

Worked on cluster optimization and job scheduling to improve performance and cost efficiency.

Migrated manual release process to Octopus Deploy, automating deployments across multiple environments and reducing deployment time by 45%.

Created reusable Octopus Deploy deployment processes and runbooks for infra, middleware, and application updates.

Integrated Octopus with Terraform + Ansible workflows for full Infrastructure + Application continuous deployment automation.

Enabled end-to-end deployment automation for containerized workloads across AKS, EKS, and GKE, integrating Concourse pipelines with Vault, PlainID, and Okta for secure secrets and access management.

Implemented SonarQube-based static code analysis across multiple product teams to maintain consistent code quality standards in Java, Python, and .NET applications.

Refactored legacy JavaScript codebases to TypeScript, improving error detection and reducing runtime failures by enforcing strict typing.

Integrated SonarQube scans into Jenkins and GitLab CI pipelines, automatically enforcing thresholds before deployment to production environments.

Partnered with application developers to resolve high-severity code smells, vulnerabilities, and maintainability issues, improving release quality and security posture.

Developed and consumed GraphQL APIs for internal application services, implementing schema stitching, resolver logic, and caching strategies.

Designed and deployed OPA Gatekeeper policies for Kubernetes cluster governance, ensuring compliance with network, resource, and RBAC policies.

Integrated PlainID and Okta for centralized user access management across multi-cloud and hybrid environments.

Implemented reverse proxy configurations (NGINX, HAProxy) to enforce SSO, JWT validation, and API-level security with PBAC frameworks.

Used Styra DAS to manage and distribute OPA policies across distributed Kubernetes clusters, improving visibility and policy version control.

Collaborated with cloud security architects to integrate PBAC and policy-as-code principles into CI/CD pipelines, ensuring continuous compliance and audit readiness.

Implemented Mezmo (LogDNA) for log aggregation and real-time troubleshooting across Kubernetes workloads with structured logging and parsing rules.

Built dashboards and log pipelines to improve traceability, root cause identification, and on-call efficiency.

Integrated BigPanda into observability workflows by correlating alerts from Grafana, Prometheus, Splunk, and Datadog to reduce noise and speed up incident triage.

Optimized GraphQL query performance, reducing response time and network overhead for data-intensive workloads.

Designed and executed LoadRunner performance scripts for REST and SOAP APIs to validate reliability of multi-cloud deployments

Supported Siebel CRM automation workflows to improve data consistency and reduce manual configuration efforts.

Implemented centralized observability and monitoring using Prometheus, Grafana, Dynatrace, ELK, Splunk, and CloudWatch, enabling proactive incident detection and alerting.

Secured application secrets and sensitive data using AWS Secrets Manager, Azure Key Vault, and GCP Secret Manager, adhering to CIS benchmarks and industry standards.

Implemented Kafka-based event-stream processing in Java and Python, automating log ingestion and improving real-time analytics across cloud platforms.

Built Rust-based concurrent services for data ingestion and log aggregation, integrated with Prometheus, Grafana, and ELK Stack.

Enhanced multi-cloud automation frameworks by introducing Rust microservices for fast event-driven monitoring and incident correlation.

Collaborated with DevOps teams to integrate Rust utilities into Terraform, Jenkins, and Ansible workflows, improving reliability and reducing deployment errors.

Used Micro service architecture with Spring Boot based services interacting through a combination of REST and Apache Kafka message brokers and also worked with Kafka Cluster using Zookeeper.

Led lift-and-shift migrations of CI/CD tools and infrastructure from on-premises to AWS cloud, ensuring zero downtime and improved deployment consistency.

Implemented SLOs, SLAs, penetration testing, and AI/ML-driven predictive alerts in ServiceNow, improving reliability, security, and speeding root cause analysis.

Implemented the application using Spring Boot Framework and handled the security using Spring Security.

Mentored new hires and internal teams cloud best practices, automation, and observability, reducing onboarding time and improving productivity.

Environment: Azure, AWS, GCP, Azure DevOps, AWS CodePipeline, GCP Cloud Build, RedHat, Ubuntu, Windows Server 2008/2012R2/2016, Microsoft SQL Server, NPM, Microsoft Visual Studio, Octopus Deploy, PlainID, Open Policy Agent (OPA), Styra DAS, Okta, reverse proxy, NGINX, Envoy, PBAC, ABAC, policy-as-code, Zero Trust, access management, authorization, Kubernetes admission control, compliance-as-code, Spring Boot, NuGet, Data Factory, Jenkins, Docker, Kubernetes, Ansible, Terraform, Function Apps (.Net Core and C#), Web Apps, Gitops, C/C++, QNX OS, CMake,Sonar qube, Kafka, CyberArk, Helm, Automation Accounts, Logic Apps, IAM, Windows PowerShell, JSON, Shell, Pester, GitLab, Prometheus, Grafana, ELK Stack, Splunk, Dynatrace,

Contact this candidate