• Red Hat And AWS Certified Engineer having more than 9+ years of overall professional IT experience and 4+ years of experience in dealing with Cloud service providers like AWS & GCP, DevOps Implementation, Build & Release engineering and Linux administration.
• Technologies used throughout my career include - AWS | GCP | Microsoft Azure | Docker | Kubernetes | Jenkins | Ansible | Linux | Git | Red Openshift | Python | PHP | MySQL | DataDog | NewRelic | Nginx | Networking | ElasticSearch | Chef | Terraform and many more.
• Learned new technologies and tools, and introduced them to the company; in which way it helped the company build up an agile development environment. It improved the product quantity and work efficiency.

Professional Certifications - AWS / Azure / Red Hat

• Certified Kubernetes Application Developer [Verify]
• AWS Certified SysOps Administrator – Associate [Verify]
• AWS Certified Developer – Associate [Verify]
• AWS Certified Solution Architect – Associate [Verify]
• Microsoft Certified: Azure Solutions Architect Expert [Verify]
• Microsoft Certified: Azure Security Engineer Associate [Verify]
• Microsoft Certified: Azure Data Scientist Associate [Verify]
• Microsoft Certified: Azure AI Engineer Associate [Verify]
• Microsoft Certified: Azure Administrator Associate [Verify]
• Red Hat Certified Specialist in Ansible Automation  [Verify]
• Red Hat Certified Engineer (RHCE) [Verify]
• Red Hat Certified Specialist in Openshift Administrator [Verify]
• Red Hat Certified System Administrator  [Verify]
• Red Hat Certified Specialist in Virtualization   [Verify]

Amazon Web Services (AWS) Kubernetes

Jenkins Git DevOps Python

ELK Stack / Splunk Terraform

Key  Skills Google Cloud Platform (GCP) Ansible

GitHub | GitLab SDLC

Shell Scripting Docker

Linux Chef

CAREER REVIEW

Microsoft Azure Agile Methodology Nginx Web Server Networking

Pandas | Numpy | Matplotlib Tableau | Power BI

Openshift Machine Learning

• Implementing CI/CD Pipeline in AWS using cutting edge technology
• Helping client to modernize their application to build cloud native application
• Dealing with Docker containers in ECS Clusters
• Designing and deploying infrastructure in AWS using Infrustructure as Code (IaC) tool called Cloud Development Kit (CDK)
• Strictly following and practicing Agile methodology with Scaled Agile Framework (SAF).

• Developing & deploying serverless applications into AWS environment using various AWS managed services.
• Working with different kinds of AWS Developers tools like AWS Lambda, API Gateway, AWS Cloud9, AWS Codestar, AWS Serverless Application Model (SAM) and so on.
• Working closely with a team of highly skilled data and API engineers to help connect and integrate web services across the enterprise.
• Being self-supportive in collaborating with team members to effectively deliver robust solutions for the business
• Working seamlessly in an agile environment with engineers, product managers, business analysts, and designers to understand end-user requirements
• Providing administrative support including monitoring, performance tuning, and responding to incidents
• Ensuring that deliverables meet specifications and quality requirements, as well as compliance with security policies and export/import regulations
• Identifying new features and requirements in support of our internal & external partners
• Evaluating current product documentation and updates existing operational documentation to ensure consistency of service documentation and service readiness
• Providing expert and creative solutions for problems to ensure external and internal partner satisfaction and productivity
• Automating API & portal deployment process through scripting & CI/CD pipelines
• Researching, developing or recommending, and test diagnostic tools and aids for improving diagnostic capability relative to developer tool set
• Closely working with Cloud service providers such as AWS & IBM cloud to increase the business values
• Data analysis & mining with Pandas, Numpy & Matplotlib, Tableau

• Manages and leads a team of employees. Communicated company goals, security best practices, and deadlines to the team.
• Motivates team members and assesses performance.

• Developing video content that brings deep technical expertise to a mass audience.
• Training DevOps Engineers on different technologies such as Docker, Kubernetes, AWS, GCP, Linux, Ansible, Python, Shell Scripting, Jenkins CI/CD

• Deployed applications, monitored operations of multiple projects, and maintained. enterprise. solutions too.

ensure that they meet target performance metrics

• Architected a Follow and Notify (FAN) social application in AWS using VPC, S3, Route 53, Auto-scaling, Elastic Beanstalk, SQS, SNS, RDS MySQL.
• Played a key role in evaluating, establishing and conducting proof of concepts of various API management products like 3-Scale, Nginx proxy, WSO2 API Manager etc.
• Architected a social engagement application in a short span of time that would replace current commenting application Echo. Application was designed and developed using Java/J2EE technologies with NoSQL DynamoDB as backend.
• Produced comprehensive architecture strategy for environment mapping in AWS that involved Siteminder, Scripps' AIM Application, Community Moderation Broker (CMB), Echo commenting apps etc.
• Produced a comprehensive strategy using AWS Identity and Access Management (IAM) Role for community platform systems and successfully implemented the same setting precedence for other teams to follow

• Developed automation and deployment utilities using Ruby, Bash, Powershell, Python and Rundeck.
• Designed and developed automated deployment and scaling processes based on Vagrant and Chef for a wide  range of server types and application tiers, including Elasticsearch, and Zend PHP and IIS Clusters.
• Wrote custom monitoring and integrated monitoring methods into deployment processes to develop self-healing solutions.
• Created automation and deployment templates for relational and nosql databases (standalone and RDS), including MSSQL, Mysql, MongoDB, Redis and NodeJS.
• Conducted team meetings to update members on best practices and continuing expectations
• Ensuring team members understand the requirements of their work, and are equipped with tools and training required for successful performance and effective decision making

• Developed projects using MVC framework, AngularJS, Bootstrap.
• Experienced SQL programming on MS SQL Server and MySQL.
• Created Crystal Reports.

• Implemented Test Driven Development(TDD) in ASP.NET and PHP.
• Worked with Dependency Injection in ASP.NET
• Designed AWS solution such as EC2, S3, VPC.
• Had experience to work with Entity Framework.
• Went through software development life cycle with Agile methodology.
• Developed projects with HTML5, XML and CSS, AJAX, JSON , JavaScript, JQuery and other JS Frameworks.
• Wrote complex SQL queries, Stored procedures and SQL functions

• Designed and developed responsive web applications using PHP and Bootstrap for photography studio

management, online social savings network and product management

• Designed and developed RESTful style web services to manipulate dynamic datasets using AJAX calls
• Created a Content Management System (CMS) which serves as an interface for clients
• Visualized large datasets for analysis that allows gaining deeper insights
• Developed rigorous test cases using RSpec to ensure bug-free code

• July, 2007 – May, 2008: Evoknow Inc. (US Based Company) Web Developer

  
  Deployed and supported the application code across various system servers
• Worked with a team to design and develop an interactive social studies website, for elementary students, using

Dreamweaver, CSS, Flash, HTML, JavaScript, and Photoshop

• Responsible for overall web project management from development to execution and maintenance
• Performed validation of completed sites including the debugging and testing of code
• Evaluated code to ensure that it is valid, is properly structured, meets industry standards and is compatible with browsers, devices, or operating systems.
• Modified current systems, writing and testing code
• Documented test plans, testing procedures, or test results

PROJECT HANDLED

• Building & Deploying a Serverless Web Application into GCP
  • Hosted the frontend application into Google Storage
  • Managing & Authenticating the users through Amazon Cognito
  • Building the serverless backend with Lambda, NoSQL & Python
  • Building & Deploying RESTful APs with API Gateway
• Automated software delivery life cycle using CI/CD pipeline ini GCP
  • Successfully generated a release pipeline that automates software delivery process using GCP DevOps toolchain.
  • Presented automated code deployments by connecting pipeline
  • Managed and plugged build service, including Jenkins with the CI/CD automation.
• Created a build server for Continuous Integration (CI) on GCP

• • Introduced and presented a virtual application server to host Jenkins server using GCP Virtual Instance. In that single-node setup, both the Jenkins server and agent run on the same instance.
  • Efficaciously installed Jenkins on instances
  • Configured the Jenkins with build servers in order to spin up additional instances as build servers, based on resource consumption.
• Migrated a GIT repository from GitHub into GCP Repository
  • Migrated a big project to the GCP repository. As the project was too big, the migration process has been done incrementally with a python script.

• Hosted a static website in AWS (Using AWS S3, Route53 & CloudFront)
  • Installed, arranged and configured a static website using Amazon S3. Amazon S3
  • Connected the domain name with that website using Amazon Route 53. Amazon Route 53 for describing Domain Name System (DNS) where to find that website.
• Break a Monolith Application into Microservices
  • Containerize the application
  • Deploying the application into ECS cluster
  • Breaking the application into several interconnected services and push each service's image to an Amazon ECR repository
  • Deploying the application as a set of interconnected services behind an Application Load Balancer (ALB)
• Deploy a Kubernetes Application in Google Kubernetes Engine
  • Launching a Python web application environment using GCP App Service. App Service provisions and manages the underlying infrastructure such as GCP instances and stack components such as OS, web server, language/framework)
  • Deploy the web application using App Engine
• Migrating database from Oracle to Amazon Redshift
  • Converted the data warehouse schema and code from an Oracle data warehouse running on Amazon Relational Database Service (Amazon RDS) using the AWS Schema Conversion Tool (AWS SCT).
  • Migrated data from the Oracle data warehouse to Amazon Redshift using the AWS Database Migration Service (AWS DMS).
  • Performed post-migration activities such as running SQL queries to validate object types, object count, and number of rows for each table between source and target data warehouses.

• Set Up an Email-Receiving Pipeline
  • Set up a domain to receive email using Amazon SES
  • Saved the emails in raw format to an Amazon S3 bucket. Amazon SES saved the email to the Amazon S3 bucket in raw format, so that we can have the flexibility to process and displayed the email with our own application.

• Deploy a Data Warehouse

• • Created an Amazon Redshift cluster from the AWS Management Console.
  • Configured the cluster by choosing the instance type and specifying the number of nodes.
  • Secured the cluster using AWS IAM and set it up for access.
  • Loaded the data to the cluster from Amazon S3 after defining a schema and creating the tables.
  • Setting up SQL Workbench/J to access the data in the Amazon Redshift cluster using the Amazon Redshift JDBC driver.
  • Analyzed the data with standard SQL from SQL Workbench/J.
• Design a database for a mobile app with Amazon DynamoDB

o    The DynamoDB contained a single-table design that combined multiple entity types in one table and a composite primary key that allow for many-to-many relationships. The table also had an inverted index to allow reverse lookups on our many-to-many entities. We also normalized the data to make the information consistent and redundancy free.

• Implementing Amazon ElastiCache for caching session data using Redis

o    Configured Amazon ElastiCache nodes for Redis as a distributed cache to handle the sessions from the application.

• Deploy WordPress with Amazon RDS, CloudFront, Cloud Formation and EC2 in AWS

o    I also make sure Automated backup and recovery are there so that we won’t lose data in the event of any accident

• CloudFormation script has been written so that the wordpress application can be deployed into another region or infrastructure with ease and without any human intervention.
• Scripts has also been written in Python to take automated backup of the application and database and stored them in Amazon Simple Storage (S3) service.

• Implementing Continuous Delivery Pipelines with Spinnaker and Google Kubernetes Engine (GKE)

o    Set up an environment by launching Google Cloud Shell, created a Kubernetes Engine cluster, and configured the identity and user management scheme.

• Deployed Spinnaker to Kubernetes Engine using Helm chart.
• Build the Docker image and created triggers to re-build the docker images when the application changes.
• Configured a Spinnaker pipeline to reliably and continuously deploy the application to the Kubernetes Engine

• Setting up a Development Environment for Python using AppDev in GCP

o    Set up a Python development environment on Google Cloud Platform, using Google Compute Engine to create a virtual machine (VM) and installed software libraries for the development.

• Launch a service using Deployment Manager in GCP

o    Installed and configured an advanced deployment using Deployment Manager templates.

• Enabled Stackdriver monitoring.
• Configured Stackdriver Uptime Checks and notifications.
• Configured a Stackdriver dashboard with two charts, one showing CPU usage and the other ingress traffic.
• Performed a load test and simulate a service outage.

• Automating cloud infrastructure with Ansible / Chef

o    Used Ansible/chef to automate cloud infrastructure such as virtual machines, load balancer, storage etc in AWS/GCP

o automated configuration management such as installing software packages, updating patches and configurations etc. within the virtual machines

• Build a Log Analytics Solution in AWS

o    Set up a Kinesis Agent on data sources to collect data and send it continuously to Amazon Kinesis Firehose.

• Created an end-to-end data delivery stream using Kinesis Firehose. The delivery stream transmitted the data from the agent to destinations including Amazon Kinesis Analytics, Amazon Redshift, Amazon Elasticsearch Service, and Amazon S3.
• Processed incoming log data using SQL queries in Amazon Kinesis Analytics.

• Loaded the processed data from Kinesis Analytics to Amazon Elasticsearch Service to index the data.
• Analyzed and visualized the processed data using Kibana.

• Build a Serverless Real-Time Data Processing App in AWS

o    Created a stream in Kinesis and wrote to and read from the stream to track information

• Build a Kinesis Data Analytics application to read from the stream and aggregated metrics
• Persisted aggregate data from the application to a backend database stored in DynamoDB and run queries against those data.
• Used Kinesis Data Firehose to flush the raw sensor data to an S3 bucket for archival purposes.

• Implementing CI/CD Pipeline with Azure DevOps for the following Stack
  • Kubernetes
  • Node.JS Application
  • Java Application
  • .NET Core App
  • Web App & SQL Server Database
• Securing the Secrets in the pipelines using Azure Key Vault
  • Accessing Secrets from Azure Key Vault
  • Linking Secrets from Azure Key Vault
• Data Analysis & Visualization with Various Python Libraries
  • Data analysis, cleaning, transformation with Pandas Library
  • Data visualization with Matplotlib and Tableau
  • Implementing data ingestion pipeline using various AWS services like Lambda Function, Simple Storage Service (S3), Step Functions etc.
• Implementing Configuration Management using Terraform
  • Deploying three tier web application in Azure with Terraform
  • Deploying Terraform infrastructure using Azure DevOps
  • Deploying Terraform infrastructure in Azure using Jenkins
• Automating infrastructure deployments in the Cloud with Terraform and Azure Pipelines