Lead DevOps/SRE Engineer (Multi-Cloud)

SANDEEP PENTYALA

Lead Devops Engineer / SRE

312-***-**** *********.****@*****.*** linkedin.com/in/sandeep-p-61265412b

Professional Summary

Lead DevOps Engineer / Site Reliability Engineer with 11+ years of experience designing, automating, and managing secure, scalable, and highly available cloud platforms across AWS, Azure, and Google Cloud Platform (GCP).

Proven expertise in architecting multi-cloud infrastructure, implementing Infrastructure as Code (Terraform, CloudFormation, AWS CDK), and standardizing cloud platforms to improve scalability, governance, and operational efficiency.

Extensive experience building enterprise-grade CI/CD and GitOps solutions using Jenkins, GitHub Actions, GitLab CI, Azure DevOps, AWS Code Pipeline, Helm, and Argo CD to accelerate software delivery and improve deployment reliability.

Strong background in Site Reliability Engineering (SRE) with expertise in production operations, observability, incident response, root cause analysis (RCA), capacity planning, performance optimization, and SLA/SLO management for mission-critical applications.

Hands-on experience designing and managing container platforms using Kubernetes (EKS, AKS, GKE), OpenShift, and Docker, enabling resilient, highly available, and cloud-native application deployments.

Experienced in implementing enterprise monitoring, logging, and alerting solutions using Prometheus, Grafana, ELK Stack, CloudWatch, Datadog, Dynatrace, and Splunk to improve system visibility and operational reliability.

Skilled in automating infrastructure provisioning, deployments, and operational workflows using Python, Bash, YAML, and REST APIs, reducing manual effort and improving platform consistency.

Experience supporting data and AI/ML platforms by building automated cloud infrastructure, CI/CD pipelines, Kubernetes environments, and data platform services for scalable analytics and machine learning workloads.

Strong collaborator with architecture, security, networking, and development teams, leading cloud modernization initiatives and delivering secure, resilient, and cost-optimized platform solutions aligned with business objectives.

Technical Skills:

Programming Languages – Python, Bash, YAML, JSON

DevOps & CI/CD – Jenkins, GitHub Actions, GitLab CI, AWS Code Pipeline, CI/CD Automation, Build & Release Pipelines

Cloud & Infrastructure – AWS (EC2, S3, Lambda, EKS), Azure (AKS), GCP (Compute, GKE), Serverless Architecture

Containerization & Orchestration – Docker, Kubernetes, Helm, Microservices Deployment, Argo CD, OpenShift Pipelines

Infrastructure as Code (IaC) – Terraform, CloudFormation, CDK, YAML/JSON Templates, Automated Provisioning

Monitoring & Observability – Prometheus, Grafana, CloudWatch, ELK Stack, Logging & Alerting

AI/ML Engineering – scikit-learn, TensorFlow, PyTorch, Model Training, Feature Engineering, Model Evaluation

MLOps – MLflow (Tracking, Model Registry), Model Deployment, Model Serving, Containerized ML Pipelines

Data Engineering Basics – Python (Pandas, NumPy), ETL Pipelines, Data Validation, Data Transformation

Automation & Scripting – Python Automation, Shell Scripting, REST API Integration

AI Platforms & APIs – OpenAI API, Hugging Face Transformers, LLM Integration, Prompt Engineering

Version Control & Collaboration – Git, GitHub, GitLab, JIRA, Confluence, Agile/Scrum EDUCATION

Projects

Charter Communications – Denver, Colorado

Project 1: Data Platforms

Job title: Lead Devops Engineer / SRE Duration: 01/2025 – Present

Responsibilities:

Deployed end-to-end MLOps pipelines using Kubeflow, Airflow, and Docker, automating lifecycle management for 68 production models processing over 5.6 TB of real-time trip and demand data across 27 urban markets.

Designed and deployed secure, scalable Google Cloud infrastructure using Terraform, provisioning VPCs, Shared VPC, Cloud DNS, Cloud NAT, Cloud Router, Compute Engine, Cloud Storage, and GKE across Development, QA, and Production environments.

Designed and implemented Harness CI/CD pipelines for containerized microservices, reducing deployment time by over 60%.

Owned the complete lifecycle of multiple application stack back-end services from platform setup, configuration, deployment support, CI/CD setup to monitoring, performing capacity planning, system performance optimization, delivery of SLAs, 24/7 support and development of system documentation.

Automated infrastructure provisioning using AWS CDK integrated with GitHub Actions and Jenkins CI/CD pipelines, enabling consistent and repeatable deployments across Development, QA, and Production environments.

Administered and supported TechnoTree Digital Catalogue Manager (DCM) across Development, SIT, UAT, and Production environments, ensuring platform stability and high availability.

Implemented AWS Control Tower to establish secure multi-account landing zones and centralized governance across enterprise AWS environments.

Designed and implemented API-led integrations using RESTful web services to enable seamless communication between enterprise applications and cloud-native microservices.

Configured comprehensive observability using Cloud Monitoring, Cloud Logging, Prometheus, Grafana, and log-based alerting, performing root cause analysis, incident troubleshooting, and proactive performance optimization for production workloads.

Designed and maintained scalable GCP data pipelines using Dataflow, Dataproc, BigQuery, and GCS, supporting high-volume batch and distributed data processing workloads.

Experience building enterprise Platform Engineering capabilities supporting AI-enabled software delivery, reusable platform services, developer self-service, automation frameworks, and cloud-native engineering practices.

Exposure to AI-assisted engineering workflows including Azure OpenAI, Azure AI Foundry, GitHub Copilot, automation agents, and enterprise developer acceleration initiatives.

Designed, deployed, and administered Azure Kubernetes Service (AKS) clusters across Development, QA, UAT, and Production environments, performing cluster upgrades, node pool management, autoscaling, workload optimization, and production support.

Migrated legacy Jenkins pipelines to Harness CI/CD, enabling standardized build, deployment, rollback, and approval workflows.

Built reusable platform engineering services enabling AI-assisted application development using Azure OpenAI, GitHub Copilot, Microsoft 365 Copilot, and enterprise automation frameworks.

Supported AI-enabled SDLC workflows by integrating GitHub Copilot, Azure DevOps pipelines, automated code validation, release automation, and deployment governance.

Designed reusable Terraform modules, CI/CD templates, deployment accelerators, automation frameworks, and shared platform services that improved developer productivity and reduced onboarding effort.

Automated environment provisioning across Development, QA, UAT, and Production using Infrastructure as Code, standardized templates, and platform governance controls.

Installed, configured, upgraded, backed up, and restored MongoDB databases while ensuring high availability and disaster recovery.

Performed AWS Well-Architected Framework reviews and implemented CIS AWS Foundations Benchmark recommendations to improve security, reliability, and operational excellence.

Applied FinOps best practices by optimizing AWS resource utilization using Savings Plans, Reserved Instances, AWS Budgets, Cost Explorer, and lifecycle policies.

Authored operational runbooks and infrastructure documentation for AWS Control Tower, Service Catalog, AFT workflows, and enterprise cloud governance.

Implemented Istio Service Mesh on AKS for secure microservices communication by configuring Ingress/Egress Gateways, Virtual Services, Destination Rules, mTLS, traffic routing, circuit breaking, retries, fault injection, and observability.

Developed enterprise-grade GitLab CI/CD pipelines with automated build, testing, artifact management, release automation, approval workflows, rollback mechanisms, and deployment validation for cloud-native applications.

Built reusable Terraform modules to provision Azure resources including AKS, VNets, Subnets, NSGs, Azure Key Vault, Azure Monitor, Log Analytics, Managed Identities, Azure Container Registry (ACR), and Storage Accounts.

Developed and orchestrated Apache Airflow DAGs using Google Cloud Composer to automate ETL workflows, dependency management, scheduling, monitoring, and failure recovery.

Developed reusable reference architectures for cloud onboarding covering identity, networking, governance, infrastructure provisioning, and security controls.

Designed and standardized GCP landing-zone architecture including Organization hierarchy, Folder structure, Shared VPC, IAM model, project provisioning standards, and security guardrails for enterprise application onboarding.

Configured Azure Virtual Networks (VNets), Subnets, NSGs, Azure DNS, and Application Gateway for secure enterprise application deployments across Development, QA, and Production environments.

Designed Hub-and-Spoke network architecture integrating Azure Firewall, VPN Gateway, ExpressRoute, and Virtual Network Peering to enable secure hybrid cloud connectivity.

Designed and maintained cloud infrastructure for TechnoTree DCM using Terraform and Kubernetes, ensuring high availability, scalability, and repeatable deployments.

Configured Harness Delegate across Kubernetes clusters for secure deployment execution.

Automated TechnoTree DCM application deployments using Jenkins, GitHub Actions, Helm, and GitOps (Argo CD), reducing manual deployment effort and improving release consistency.

Automated infrastructure provisioning and operational workflows using Python, Bash, REST APIs, and Terraform, eliminating manual deployment activities and improving platform consistency.

Managed Kubernetes workloads using Helm Charts, Kubernetes manifests, ConfigMaps, Secrets, RBAC, Namespaces, Network Policies, Ingress Controllers, Horizontal Pod Autoscaler (HPA), and Pod Disruption Budgets.

Configured Azure security using Azure RBAC, Azure AD integration, Managed Identities, Azure Key Vault, Private Endpoints, Azure Policy, and Secrets Store CSI Driver to secure enterprise Kubernetes environments.

Implemented deployment strategies including Rolling Updates, Blue-Green Deployments, Canary Releases, Automated Rollbacks, and Release Governance using GitLab CI/CD, Helm, and Kubernetes.

Configured and managed AWS API Gateway to publish, secure, monitor, and manage REST APIs across multiple environments.

Developed Python-based middleware API services to orchestrate data exchange between cloud platforms, databases, and third-party applications.

Hands-on experience implementing enterprise CI/CD modernization, platform governance, environment management, observability, RBAC, API security, and secure automation across Azure and AWS.

Optimized MongoDB performance through index optimization, query tuning, schema validation, and database health monitoring.

Automated Kafka cluster provisioning and configuration using Terraform, Ansible, and Infrastructure as Code principles.

Performed Kafka cluster upgrades, broker maintenance, partition rebalancing, and capacity planning with minimal downtime.

Integrated AWS CDK deployments with AWS Code Pipeline and CloudFormation change sets, enabling automated infrastructure validation, approvals, and rollback capabilities.

Developed Python-based AWS Lambda functions integrated with EventBridge and AWS Config for automated security remediation and compliance enforcement.

Configured AWS Organizations, Organizational Units (OUs), and Service Control Policies (SCPs) to enforce enterprise governance and least-privilege access.

Implemented AWS Config, Security Hub, and CloudTrail to continuously monitor compliance and automate remediation of non-compliant resources.

Supported Azure AI Foundry environments by automating infrastructure provisioning, model deployment pipelines, identity integration, monitoring, and operational governance.

Integrated GitHub Copilot and Microsoft Copilot capabilities into enterprise engineering workflows to improve developer productivity and software delivery efficiency.

Implemented enterprise platform governance using RBAC, Managed Identities, Azure Key Vault, secrets management, policy enforcement, audit logging, and standardized environment controls.

Supported Responsible AI governance by implementing AI lifecycle monitoring, secure access controls, operational validation, compliance checks, and audit logging.

Configured proactive monitoring and observability using Azure Monitor, Azure Log Analytics, Prometheus, Grafana, Application Insights, OpenTelemetry, and custom alerting for Kubernetes clusters and cloud infrastructure.

Provided 24x7 Production Incident Support, troubleshooting critical production issues, performing Root Cause Analysis (RCA), coordinating bridge calls, implementing corrective actions, and improving system reliability through automation.

Guided application development teams in adopting DevOps best practices, Kubernetes deployment standards, Infrastructure as Code, CI/CD automation, container security, and cloud-native architecture.

Implemented Azure Monitor, Application Insights, Azure Log Analytics, Prometheus, Grafana, OpenTelemetry, and distributed tracing for centralized observability and operational dashboards.

Implemented OAuth 2.0, JWT, API Keys, and IAM-based authentication mechanisms to secure enterprise APIs.

Delivery and implementation of SRE analytics, log management, monitoring and automation solutions. Managing SLAs, project resource and delivery management.

Built operational dashboards using Splunk, Grafana, Prometheus, and Dynatrace for application performance monitoring and proactive alerting.

Extensive involvement in Monitoring & Automation architecture design, engineering, implementation and delivery. Implementation and delivery of SRE tools in CI/CD pipeline utilizing GitHub, Jenkins, Puppet, JIRA, Confluence, ServiceNow and other tools.

Involved in Performance Trend Analysis, Log Analysis and Error resolution, Tuning of Platform Monitoring and Root Cause Analysis

Participated in architecture design reviews, Terraform code reviews, Kubernetes deployment reviews, and CI/CD pipeline reviews, ensuring compliance with enterprise standards and secure deployment practices.

Optimized AKS cluster performance through resource tuning, node scaling, workload balancing, capacity planning, and cost optimization while maintaining high availability and SLA commitments.

Automated release management using GitLab pipelines integrated with Terraform, Helm, Kubernetes, and Azure services, reducing deployment time and increasing release reliability.

Collaborated with Development, QA, Security, Networking, and Operations teams to design, deploy, and maintain secure, scalable, and highly available cloud infrastructure supporting mission-critical applications.

Developed reusable DevOps standards, infrastructure templates, deployment automation frameworks, and operational runbooks to standardize enterprise cloud platform implementations.

Assist Managed Services Technical Writers in creation of Runbooks and other solution documentation

Managed network security using Load balancer, Auto-scaling, Security groups and NACL.

Automated Kafka deployments on Amazon EKS and Google Kubernetes Engine using GitOps workflows with Jenkins and GitHub Actions.

Setup Kubernetes Kubelets that talks to the API server in Kube Master. Created Pods, Deployments, Services and Replication Controller in Kubernetes. Used Spinaker for Kubernetes Continuous Deployment and Rolling Updates.

Administered Red Hat OpenShift Container Platform (OCP 4.x) clusters for Development, QA, and Production environments.

Automated OpenShift application deployments using Jenkins, Helm, Terraform, and GitHub Actions.

Configured OpenShift Routes, Security Context Constraints (SCC), ConfigMaps, Secrets, and RBAC to secure enterprise workloads.

Developed reusable platform templates, automation scripts, connectors, deployment accelerators, and self-service engineering capabilities supporting multiple enterprise product teams.

Integrated Playwright automated testing, security scanning, pipeline quality gates, regression validation, and release approval workflows into Azure DevOps CI/CD pipelines.

Implemented deployment validation, health checks, automated rollback, canary deployments, and release controls to improve platform reliability and resiliency.

Designed secure REST API integration patterns using OAuth2, JWT authentication, Managed Identity, API Gateway, and enterprise integration standards.

Collaborated with Enterprise Architecture, Cybersecurity, Cloud Engineering, and AI teams to implement standardized platform capabilities aligned with enterprise governance.

Automated operational tasks using Python, PowerShell, Bash, Terraform, and Azure DevOps pipelines, reducing manual intervention and improving operational efficiency.

Optimized cloud infrastructure cost through automated resource provisioning, monitoring, rightsizing recommendations, and operational dashboards across Azure and AWS.

Supported AI agent orchestration, reusable automation services, enterprise integrations, and intelligent workflow automation for AI-enabled applications.

Improved developer experience through reusable CI/CD templates, self-service deployment tooling, infrastructure modules, and standardized engineering practices.

Developed automated CI/CD pipelines using Jenkins, GitHub Actions, and Azure DevOps for TechnoTree DCM application deployments

Integrated OpenShift GitOps (Argo CD) for continuous deployment and automated application synchronization.

Developed CI/CD workflows for model delivery through Jenkins, Terraform, and Kubernetes, enabling continuous deployment of microservices and cutting model release turnaround by 10.4 hours per sprint.

Provisioned Azure App Services, Azure Functions, Azure SQL Database, Azure Storage Accounts, Azure Key Vault, Azure Event Hub, and Azure Data Lake Storage Gen2 using Terraform modules and Azure DevOps pipelines.

Integrated Azure Key Vault with AKS workloads and Azure DevOps pipelines for centralized secrets management and certificate rotation.

Defined IAM architecture using least-privilege access, custom roles, service accounts, workload identity, and Cloud Identity groups to support secure enterprise onboarding.

Designed highly available multi-region AWS infrastructure using VPC, Route Tables, Security Groups, NAT Gateways and Internet Gateways to support enterprise production workloads.

Developed OpenAPI (Swagger) specifications and maintained API documentation for internal and external consumers.

Integrated enterprise applications with Salesforce, ServiceNow, Oracle, and other third-party platforms using secure REST and SOAP APIs.

Built reusable infrastructure modules using AWS CDK to standardize networking, security, monitoring, and application deployment patterns, reducing infrastructure provisioning time by over 60%.

Optimized GCP infrastructure costs by implementing Committed Use Discounts (CUDs), autoscaling policies, rightsizing recommendations, storage lifecycle management, and idle resource cleanup, significantly improving resource utilization.

Optimized middleware API performance through connection pooling, payload compression, caching, and load balancing, reducing response latency.

Guided application teams through enterprise onboarding into GCP landing zones, resolving complex identity, networking, IAM, and infrastructure integration challenges.

Built end-to-end Azure DevOps CI/CD pipelines integrating Terraform, GitHub Actions, Jenkins, Helm, and Kubernetes manifests for automated infrastructure and application deployments.

Implemented resilient integration patterns including retry logic, circuit breakers, timeout handling, and dead-letter queues for fault-tolerant API communication.

Configured Cloud Monitoring, Cloud Logging, and alerting policies to proactively monitor application performance and infrastructure health across GCP environments.

Configured cross-region networking, VPC peering and hybrid cloud connectivity supporting secure application communication.

Automated AWS infrastructure provisioning using Terraform and CloudFormation ensuring repeatable deployments.

Implemented CloudWatch dashboards, Grafana monitoring and proactive alerting for production infrastructure.

Integrated monitoring and model drift detection systems with Prometheus, Grafana, and AWS SageMaker Model Monitor, tracking 2.3 billion inference events monthly and improving model reliability across ride prediction and pricing systems.

Optimized data ingestion and feature store performance by refactoring ETL pipelines in Python and Spark, reducing data preprocessing latency by 7.8 seconds per batch across multi-region ML clusters.

Architected and maintained hybrid CI/CD pipelines using Jenkins, Terraform, and Kubernetes, supporting 1,800+ monthly deployments across multi-cloud infrastructure and improving release reliability across 12 enterprise-grade product lines.

Automated data ingestion and deployment workflows via Airflow and Python-based ETL jobs, processing 6.2 TB of telemetry and product analytics data weekly, enabling data science teams to run real-time model validations.

Optimized cloud resource utilization using Committed Use Discounts, autoscaling, and rightsizing recommendations, reducing overall GCP infrastructure costs.

Provisioned scalable infrastructure using AWS (EKS, EC2, and S3) and Azure DevOps, standardizing compute environments for 35 distributed microservices and reducing environment setup time from 14 hours to under 4 hours.

Integrated observability and performance monitoring using Prometheus, Grafana, and Datadog, tracking 1.4 million daily container events, improving fault detection response by 2.3 hours per incident.

Developed infrastructure-as-code templates with Terraform and Ansible, automating lifecycle management of over 240 cloud resources, ensuring consistency and compliance across dev, staging, and production clusters.

Optimized storage and compute resource allocation by analyzing S3 and EBS utilization metrics, reclaiming

Orchestrated blue-green deployment strategy using Docker and Kubernetes namespaces, enabling seamless version rollouts and reducing service downtime to less than 2 minutes per release.

Collaborated with cross-functional DevOps, Security, Networking, and Application teams in an Agile/Scrum environment to deliver highly available cloud infrastructure, improve deployment reliability, and maintain service quality through automation and infrastructure-as-code.

Collaborated with platform engineering teams to define standardized onboarding automation using Terraform modules, CI/CD pipelines, and infrastructure templates.

Collaborated with data engineering and security teams to implement data pipeline reliability metrics and IAM role-based access policies, ensuring compliant data transfers for 9 internal analytics workloads and external APIs.

DirecTV LLC – Dallas, Texas

Project: Software Engineering

Job title: Sr. Devops Engineer/SRE Duration: 10/2022 – 01/2025

Responsibilities:

Gather technical, functional requirements of applications to be set-up on AppDynamics from the concerned Tech Architect / Application teams.

Deploy, configure and troubleshoot application performance in Microsoft Azure and Pivotal Cloud Foundry environment.

Write shell scripts to automate agent deployments using HPSA.

Install the AppDynamics agent manually on the application servers depending upon the type of Operating Systems (Windows, Linux) the servers are hosted on.

Performed root cause analysis for Kafka performance bottlenecks, optimizing broker configurations, partition distribution, and JVM tuning.

Create the applications in the Dashboard using separate AppDynamics controllers for NON-PROD and PROD environments. Also, carry out the setting up of multiple tiers and nodes as required.

Configured Route 53 DNS, VPC networking, Security Groups, Network ACLs and Load Balancers for highly available applications.

Optimized Azure infrastructure costs using Azure Cost Management, Reserved Instances, autoscaling, storage lifecycle policies, and rightsizing recommendations.

Implemented Microsoft Entra ID (Azure AD), RBAC, Managed Identities, Network Security Groups, Private Endpoints, and Azure Key Vault policies to enhance cloud security and compliance.

Configured Azure App Services and Azure Functions for hosting cloud-native microservices integrated with Azure SQL and Azure Storage.

Deployed containerized Python-based data processing services using Cloud Run and Cloud Functions, integrating with GCS and BigQuery for event-driven and serverless processing.

Managed Linux servers including provisioning, patching, shell scripting, troubleshooting and performance tuning.

Worked closely with database administrators supporting Oracle, MySQL and Amazon RDS environments including backup and recovery.

Automated provisioning and deployment of GCP data services using Terraform, Docker, Jenkins, and CI/CD pipelines, ensuring consistent deployments across Development, QA, and Production environments.

Automated application deployments using Cloud Build, Terraform, and Docker, enabling consistent deployments across multiple GCP environments.

Developed and maintained robust CI/CD pipelines with integrated DevSecOps practices, reducing deployment times.

Spearheaded Deployment automation initiatives, cutting manual tasks through scripting in AWS EKS environment with Terraform.

Automated deployment of serverless applications using AWS CDK with Lambda, API Gateway, Event Bridge, CloudWatch, and IAM integration.

Experience to build CICD Pipeline to automate the code release process using Integration tools like GIT, GitHub, Jenkins and artifact repo.

Create application health check rules and set-up alerts to notify the concerned application teams about the performance abnormality detected.

Developed standardized Azure DevOps release pipelines supporting environment governance, deployment approvals, release controls, and enterprise platform standards.

Automated cloud environment provisioning using Terraform, Azure DevOps, and Infrastructure as Code across Development, QA, UAT, and Production environments.

Performed and deployed Builds for various Environments like QA, Integration, UAT and Productions Environments.

Worked with various components of AWS to Build servers by Importing volumes, launching EC2, RDS, creating security groups, auto-scaling, load balancers (ELBs) in the defined virtual private connection. And setup RDS, ROUTE 53, SES, SNS.

Wrote Ansible playbooks from scratch in YAML. Installed, set up & Troubleshoot Ansible

Automated local development environment using Chef configuration management tool and Chef Automate as continuous delivery tool.

Developed build and deployment scripts using Gradle and MAVEN as build tools in Jenkins to move from one environment to other environments.

Provided engineering support by: Provisioning servers with Terraform provisioning tool

Virtualized the servers using the Docker as per the test environments and dev-environments needs. And performed configuration automation using Docker containers.

Worked on Deployment Automation of all microservices to pull image from private Docker registry and deploy to Kubernetes Cluster.

Configured Azure Monitor, Application Insights, Azure Log Analytics, telemetry dashboards, and alerting solutions for enterprise platform monitoring.

Implemented Managed Identity, RBAC, Azure Key Vault integration, OAuth2 authentication, and secrets management for secure cloud platform services.

Built reusable deployment pipelines, infrastructure templates, and release automation frameworks that accelerated software delivery.

Integrated GitHub Copilot-assisted engineering workflows into CI/CD pipelines to improve developer productivity and code quality.

Supported Power Platform integration through REST APIs, Azure Functions, Logic Apps, and enterprise automation services.

Developed secure API integration patterns using OAuth2, REST APIs, JWT authentication, and API Management.

Supported cloud-native application deployments using Azure App Services, Azure Functions, Kubernetes, and serverless services.

Collaborated with cloud engineering and security teams to implement platform governance, compliance controls, and operational excellence initiatives.

Deployed enterprise microservices on Red Hat OpenShift using Helm Charts and OpenShift templates.

Managed Image Streams, BuildConfigs, and OpenShift Routes for secure container deployments.

Integrated OpenShift with enterprise authentication and centralized secrets management.

Wrote Ansible playbooks with Python SSH as a wrapper to manage configurations and the test playbooks on AWS instances using Python.

Deployed Applications into PROD & Pre-Prod environments with various Application server technologies like Web Sphere & Apache Tomcat.

Configured and managed the ELK (Elastic Search, Log stash and Kibana) for Log management.

Implemented DevOps best tools and practices such as centralized logging (ELK) server monitoring Nagios and Automation Ansible.

Worked on security management and security troubleshooting as well as, configuration of DHCP, DNS (BIND, MS), web (Apache, IIS), mail (SMTP, IMAP, POP3), & file servers on Linux servers.

Troubleshooting Linux network, security related issues, capturing packets using tools such as IPtables, firewall, TCP wrappers

Worked on Configuration Management policies and practices with regards to SDLC; along with automation of scripting using BASH/Shell, Perl and Ruby scripting.

Environment: AWS, S3, EBS, Elastic

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