Sailaja K Email & Phone Number

Morrisville, Nc, Us

Us

 Worked on Automation of security baseline based on AWS Systems Manager and AWS Inspector and terraforming it. Experience on working with AWS Cloud services like EC2, CloudWatch, CloudTrail, S3, VPC, Redshift, RDS, MWAA (Amazon Managed Workflows for Apache Airflow), IAM, SNS, Trusted Advisor etc. Involvement in designing, implementing, and maintaining the (development, staging, and production) cloud infrastructure environments. Experienced in configuring, deploying, and managing high-availability production cloud environments using Terraform/Terraform Enterprise (AWS/Azure). Experience on KMS for storing the secrets that are used for building cloud components. Implemented Clam AV for Azure solution for Antivirus scanning on blob storage by creating a storage account, container instance using the clam AV image which will do the scanning. when any upload happens, this will help to trigger the azure function. Created AWS Secrets Manager for passing secrets or sensitive data to containers in ECS tasks.

New Delhi, In

❖ Guided a team of cloud engineers through the design, implementation, and optimization of cloud solutions, ensuring alignment with business objectives and technical standards.❖ Designed and deployed containerized applications using AWS EKS and Google Kubernetes Engine (GKE), facilitating seamless cloud-native deployments in multi-cloud environments.❖ ensure system reliability.❖ Managed data pipelines and analytics workflows on AWS Redshift and GCP BigQuery, optimizing for performance, scalability, and cost-efficiency in data storage and analytics across clouds.❖ Orchestrated machine learning workloads across SageMaker and Vertex AI, utilizing cloud-native tools from both AWS and GCP to build and deploy scalable AI/ML solutions.❖ Optimized ML workflows by collaborating with cross-functional teams to streamline data preprocessing, feature engineering, and model deployment using AWS Glue, Kinesis, and S3.❖ Ensured seamless integration between data engineering and ML pipelines by developing CI/CD workflows that automate data preprocessing, model training, and deployment, using AWS Glue, S3, and SageMaker.

White Plains, New York, Us

 Comprehensive knowledge and hands-on experience with service offerings from Amazon Web Services. Actively manage, improve, and monitor cloud infrastructure on AWS, EC2, S3, and RDS, including backups, patches, and scaling. Worked closely with the marsh digital teams to onboard micro services into AWS Shared infrastructure. Worked on AWS Cloud platform and its features which includes EC2,VPC,EBS,AMI,SNS,CloudWatch,AutoScaling,IAM,Lambda, Step function and S3. Also worked on creating load balancers based on the application requirement. Deployed application which is containerized using Docker onto a Kubernetes cluster which is managed by Amazon Elastic Container Service for Kubernetes (EKS). Configured ‘Kubectl’ to interact with Kubernetes infrastructure and used AWS Cloud Formation Templates (CFT) to launch a cluster of worker nodes on Amazon EC2 instances. Configured the Docker/kubernetes containers and creating Docker files for all the environments. Day to day activities include build and deployments in lower environments and troubleshooting applications on dev, stg and prod environments. Involved in generating and installing SSL Certificates for production domains.

St. Louis, Mo, Us

> Configured AWS application deployment infrastructure services like VPC, EC2, S3, RDS, Dynamo DB, IAM, EBS, Route53, SNS, SES, SQS, CloudWatch, CloudTrail, Security Group, Auto Scaling Group ASG, and RDS using CloudFormation, Terraform templates. > Experienced in Bluegreen Deployment in the production of Kubernetes cluster in the rollback and rollout methods in the deployment strategies, and Kubernetes clusters and services are packed by Helm charts.> Created Tekton pipelines in Kubernetes to create and deploy images, manage version control of infrastructure, and perform easier rollbacks. Deployed Flux in Kubernetes Cluster for continuous delivery of Helm Charts by integrating Flux with the Helm repository.> Used Flux for automation to ensure that the state of the cluster matches the config file in git and also to make sure that the new container images and config changes are propagated to the cluster.> Used Kubernetes Service to route traffic to particular pods based on pod labels and added production label to the pod definition when testing a new backend pod.

New York, Ny, Us

New York, New York, Us

> Participated as a Team member in performing POT’s in Azure and POC’s for implementing Azure and involved in migrating AWS cloud to Azure cloud.> Actively worked on configuring and provisioning of virtual machines, storage accounts, App Services, Virtual Networks, OMS, Azure SQL Database, Azure Search, Azure Data Lake, Azure Data Factory, Azure Blob Storage, Azure Service Bus, Function Apps, Application Insights, Express Route, Traffic Manager, VPN, Load Balancing, Application Gateways, Auto-Scaling and Azure Batch Jobs.> Created Azure infrastructure using ARM templates, Azure pipelines to build, test, and release, and managed Azure Container Registry to store private Docker images, which are deployed. Grafana Monitor to collect metrics and logs. Configured Monitor to track performance and maintain security, and used Grafana tool to collect metrics, queries.> Deployed two-tier .NET, Python applications to Azure DevOps to focus on development by using services such as Repos to commit codes, Build Pipelines using PowerShell scripts.> Worked with Terraform Templates to automate the Azure Infrastructure as a Service virtual machine using terraform modules and deployed virtual machine scale sets in the production environment.> Evaluated Kubernetes for Docker container orchestration and managed Kubernetes charts using Helm and created reproducible builds of the Kubernetes applications, templatize Kubernetes manifests, provide a set of configuration parameters to customize the deployment, and Managed releases of Helm packages.