Anish Anandan

• Worked on the DevOps project, where my key task Defining and setting development, testing, release, updating, and support processes for DevOps operation
• Worked on the GEN3 migration activity, as part of migration I worked on provisioning the new infrastructures in the AWS accounts using Bogie Pipeline (Terraform, Jenkins).
• Worked with the Platform team to identify the gaps in the manual deployment process and automate that with CI/CD pipeline using Github, Terraform and Jenkins and train them to use the pipeline for their day to day tasks.
• Worked on performing rehydrations for EC2-based ECS instances to maintain the latest AMI and SG updates
• Experience creating and managing infrastructure as code using Terraform
• Familiarity with Terraform modules and wrote terraform modules to provision AWS resources like EC2, EBS Lambda, Kinesis, and SNS
• Deployed the application which pulls images from the artifactory and provisions the required ECS/EKS clusters with the tasks and services.
• Written docker files and K8's configuration files for deployment and services in the YAML format and deployed them.
• Knowledge of Kubernetes concepts such as pods, services, and deployments
• Familiarity with the kubectl, eksctl and kubeadm tools commands
• Worked on pipeline automation by creating new Jenkins jobs to deploy the resources based on terraform script
• Worked on migrating data dog monitors to the new relic and created new relic monitor dashboards and metrics for infra resources and integrated with the PagerDuty for critical notifications
• Experience with deploying code to various environments, such as development, staging, and production
• Experience with managing and maintaining GitHub organization, teams, and permissions
• Familiarity with Jenkins pipeline as code and how to use Jenkins file for defining the pipeline
• Mentoring and guiding the team members and sharing knowledge with another team on how to use the automated pipelines.
• Troubleshooting techniques and fixing the code bugs.

• Worked in an enterprise team where I was responsible for developing infrastructure in the cloud for enterprise-level tools such as Apigee, Terraform Enterprise, and many more.
• This is achieved by using the DevOps tools like UCD, Jenkins, Bitbucket/GitHub.
• Worked on creating infrastructures (required EC2/ALBS) for Apigee Platform service.
• Experience working with APIGEE Edge, Developer Portal & APIGEE Baas platform.
• Skilled in Infrastructure Development and Operations involving AWS Cloud platforms, EC2, EBS, S3, VPC, RDS, SES, ELB, Auto scaling, Cloud Front, Cloud Formation, Elastic Cache, Cloud Watch, SNS.
• Used Route53 to route traffic between different regions
• Involved in AWS Cloud IaaS stage with components EC2, VPC, ELB, Auto-Scaling, Security Groups, Route53, IAM, EBS, AMI, RDS, S3, SNS, SQS, Cloud Watch, Cloud Formation, Cloud Front, & Direct Connect.
• As terraform infrastructure team, I have written multiple modules and sentinel policies.
• Experience in Build automation tools like Jenkins, Maven.
• Expert in using different source code version control tools like GIT, Bitbucket.
• Experience in writing a Python program to automate resources through lambda.
• Worked on writing multiple lambda functions to perform desired tasks.
• Written a python script to perform a few tasks for terraform deployment.
• Worked on integrating application logs with Splunk and wrote several custom Splunk queries for monitoring and alerting.

• Designing and building of generic data pipelines and distributed data processing framework using distributed computing architectures such as AWS services (EC2, EMR, Elastic search, CloudFormation), Hadoop and Python.
• Interacting with business end-users, architects and other stake holders to understand the business requirements prepare functional design documents based on the requirements and prepare detailed design/technical document that encompasses all the requirements.
• Providing technical thought leadership on Big Data strategy, adoption, architecture and design, as well as data engineering and modeling.
• Created Lambda Functions to trigger Ec2 instance through which all the required installation set up is done in Ec2 and calling the shell script from the lambda.
• Migrating application data from On-prem to Cloud with the help of build in pipeline.
• Designing highly scalable and fault tolerant, highly available and secured, distributed computing services using EC2 instances, EMR, EBS, S3, RDS, Auto Scaling, Lambda, Snowflake, Redshift etc.
• Creating python scripts and integrate with boto3 module for developing services in AWS like S3, EC2, EMR and VPC etc.
• Developing a python Script to stop all the instances with a specific tag in AWS instance using Lambda functions and made it into Cloud Watch Scheduler to schedule it every day.
• Designing and creation of complete Cloud Formation Templates (Json/YML Template) to implement the whole AWS infrastructure through scripting.
• Designing different performance testing includes regression testing, failover testing, stress testing, capacity testing, spike testing, and soak testing and segmented testing to address the performance issue.
• Participating in software release and post-release activities, including support for product launch evangelism (e.g
  developing demonstrations and/or samples) and competitive analysis for subsequent product build/release cycles.
• Responsible for leading team and helping team members manage their career.
• Guided all the teams across commercial LOB to work on One Lake Migration and prepared clear documentation on Enterprise level.

• Developed MapReduce programs to parse the raw data, populate staging tables and store the refined data in partitioned tables in the EDW.
• Provided design recommendations and thought leadership to sponsors/stakeholders that improved review processes and resolved technical problems.
• Creating Hive tables and working on them using Hive QL.
• Managed and reviewed Hadoop log files.
• Tested raw data and executed performance scripts.
• Shared responsibility for administration of Hadoop, Hive and Pig.
• Manage and maintain Hadoop clusters for uninterrupted job.
• Good Knowledge on Hadoop Cluster architecture and monitoring the cluster.
• Responsible for creating Hive tables, loading data and writing Hive queries.
• Dealing with humongous amount of data, analyze them and derive insights using Spark SQL.
• Worked in teams and as individual contributor as well as trained several people in Hadoop and Spark.

• Troubleshooting the technical issues reported in the prod environment and fixing it.
• Troubleshoot the problems related to Control M batch jobs for the various customer-specific applications on UNIX and Windows platforms.
• Performing analysis on the reoccurring problems, troubleshooting them, and suggest the client how to prevent the recurrent failures.
• Documenting all the processes daily.
• Have actively provided contributions in handling the sessions on Unix, Storage, and the Client specific applications.
• Perform various changes involving Deployments, Application upgrades in the Unix and Windows servers, and performing restarts of the application as and when required.
• Worked on the Peregrine tool and HPSM tool to provide time-to-time status of the work on the tickets related to any Batch job issues.
• Support server infrastructure and application availability with the help of HP SiteScope and BSM monitoring.
• Coordinating with Onsite and providing training on Client specific applications supported and Mentor the new joiners to perform business as usual.
• Coordinating with different teams working on different applications to provide them with data as per their requirements.
• Helping and guiding other team members to carry out their responsibilities and meet their deadlines.
• Handling high-severity bridge calls and gauges the required team to drive solutions to the issue.