Singapore, Singapore
Experienced Cloud Site Reliability and Platform Engineer with 3+ years specializing in AWS cloud platforms and Kubernetes infrastructure. Proven track record of optimizing cloud environments, enhancing system reliability, and implementing scalable solutions. Passionate about automation, container orchestration, and driving cloud-native innovations.
- Built and maintained Elastic Kubernetes Service (EKS) and Compute platform services using Terraform and Helm charts for scalable deployments while ensuring security posture and compliance with security baseline requirements. - Provides observability and monitoring by enabling FluentBit, Grafana and Prometheus for log aggregation and forwarding, real-time system monitoring and centralized log management as an addon. - Investigates and troubleshoot system issues, identifying root causes and implementing preventive solutions to improve platform stability. - Created and maintains documentation for system configuration and troubleshooting. - Provided L1, L2 and L3 support.
- Assist in troubleshooting AWS Kubernetes clusters and conducting root cause analysis with the application teams. - Supported application teams with troubleshooting, deployment, and ensuring compliance with company rules, security standards before deploying of RBAC. - Reviewed and provide guidance to application team on Kubernetes Role-Based Access Control (RBAC) configurations, role and role-binding to prevent excessive permissions, ensuring secure access control and enforcing least privilege principles. - Provided L1 and L2 support.
- Multi-cloud expertise of supporting AWS & Azure environments, ensuring system reliability and adherence to company policies. - System reliability & issue resolution on investigating and diagnosing system issues, identifying root causes and implementing preventive solutions to improve platform stability. - Maintained and configured cloud-based systems, documented processes, and automated tasks using scripting. - Provided L1 support.
• End to End Data Migration with two technologies: Microservice and Azure Data Factory • Used .NET Core microservices to migrate on-premises to cloud by implementing data cleansing and Extract Transform Load (ETL) transformation of business rules before pushing it to Kafka to be migrated to the cloud database. • Uses Azure DevOps CI/CD automation for continuous integration and delivery, for .NET Core source codes it includes Sonarqube that does static analysis, code smells, automatic reviews, code quality and for Azure Data Factory, it will verify the syntax of the SQL queries. • Gathered transformation requirements from the stakeholders of the system and discuss the feasibility and suggest alternatives approach if it is not feasible. • Used Azure Data Factory pipeline to perform ETL of the data with the business requirement elicited from the stakeholders. • Reconciliation to ensure data integrity of the data migrated over and check for discrepancy. • Developed an Azure Data Factory pipeline to automate data extraction for verification via blob storage from SQL DB to excel that reduces a substantial amount of manpower and time required.
• Utilize Pega workflow to digitalize client's day to day work that enable efficient work through near real-time collaboration between departments, reduces time taken to retrieve physical documents and enable multiple departments to work together in an end to end case management. • Display visualization by designing trend lines and reporting by extracting data from Pega to Qlik Sense for Dashboarding using extract, transform and load data sets to Qlik Sense Dashboard.
• Created AngularJS front end UI with the help of in-house tools, based on detailed requirement specifications • Defect fixes for both AngularJS and Java with version control • Develop JUnit class to test backend services with Mockito for functional and method test coverage • Develop new backend services for customized Processing Framework, based on functional requirements • Investigate issues raised and communicate with functional team to resolve design gaps
Through this project i had work with a few technologies mainly, nodeJS, android, docker, MQTT, firebase messaging and part of Microsoft Azure.