Pankaj Saha Email & Phone Number

Hyderabad, Telangana, India

Hyderabad, Telangana, India

1. I took ownership of building a Kubernetes cluster instantaneously using CROSSPLANE as Infrastructure As A Code.2. I migrated the Cluster AutoScaler to KARPENTER, resulting in a 35-50% reduction in INFRA costs, particularly EC2 instances.3. I integrated the Flowable engine framework with the KEYCLOAK for authentication and user role-mapping functionality.4. I set up an all-in-one instrumentation and observability tool using GROUNDCOVER, which leverages ebpf as a source.5. I used HashiCorp Packer to convert a standard Rocky Linux instance into a customized EKS AMI for AMD64 and AARCH64 (ARM64) architecture.

Hyderabad, Telangana, India

1. I migrated our KOPS Kubernetes cluster to an AWS EKS cluster.2. I created a dashboard for application metrics using Prometheus and Grafana to monitor resource utilization metrics and send important alerts via messaging tools like GChat spaces and SMTP servers.3. I had independently worked on setting up the strimzi cluster operator (Kafka & zookeeper) for jobs used for batch processing.4. I learned to build a single source of YAML files using Kustomize, reducing manual effort and helping to fast-track deliverables for Kubernetes deployments.

Hyderabad, Telangana, India

1. I created a CI/CD pipeline using GitLab CICD and Maven Repositories to build and publish Developer code to Artifactory for Deployment in the cloud with KOPS.2. Streamlined process to extract code-coverage of code using Jacoco auto instrumentation via CICD.3. I have integrated SONARQUBE into our CICD pipeline to detect and prevent bugs.

Bhubaneswar, Odisha, India

(1) Worked in various use cases to perform EDA, Data Preprocessing, Feature Extraction, and Modelling.(2) Achieved a Recall of 89 in one of the live projects, which was far better than industry standards.

1. Performed EDA(Exploratory Data Analysis) on IMDB CSV Dataset with Data Pre-Processing, Data Visualisation.2. Performed EDA(Exploratory Data Analysis) on a Loan case study for approval of Credit application with Data Pre-Processing, Feature-Extraction, Data Visualisation.Libraries used were :- [ 1. Pandas 2. Numpy 3.Matplotlib ]