Bikash Sundaray
About
I am passionate about what i do and what i build
"~15 years experience Scalable System, Cloud Native, Micro-Services, Big data, OpenSource LLM model, Machine learning, Building large scale product, Enterprise grade DevOps pratices, Driving 10 Scrum Teams, Security and Database"
- I am currently playing as a Solution Architect for end-to-end product development and deployment.
- Building Data pipeline using AWS DataLake and Opensource tools. Manage cloud cost using FinOps and bringing Data Governance
- Building LLM based Agent using ollma, LangChain and Splunk to monitor data pipeline
- As part of my role, I design new features, conduct system studies, participate in solution Train, and improve the DevOps pipeline and code.
- In addition, I work as a software engineer and cloud engineer to deliver valuable products that align with our program increment goals.
- I take the initiative to study and design new features, and I regularly present progress and outcomes to stakeholders.
- I actively practice and implement microservices, API gateways, cloud-native architecture, REST APIs, Java design patterns, and Python design patterns in my day-to-day work.
- I create high-level and low-level design documents that incorporate non-functional requirements, operations, security, business logic, flow diagrams, sequence diagrams, and architecture diagrams.
- I lead Communities of Practice (CoP) and Guilds for several service streams within our product.
- I play an active role in SAFe agile PI planning and program backlog refinement, working collaboratively with multiple scrum teams on design and development.
Designed and maintained enterprise grade DevOps pipeline product life-cycle.
I have integrated tools like Jenkins, SonarQube, Docker, buildah, JFrog, Jira, BlackDuck, FOSSA, Gitlab, Kubernetes, Container image scanning, Shell script and Notification System.
Build pipeline for Backend Java/Python Apps, DevSecOps, gitOps and Frontend react/angular Apps.
Designed 1 click Deployment for Continous Delivery to Azure and AWS.
Worked on Rollback. On Ops part i have deployed and configured Prometheus, ELK, Alert manager, Distributed trace tools like jaeger.
Also used CloudWatch and Azure contains insights for monitoring on Public cloud.
Skill
I upskill everyday and continous learner
- Domain Experience
IoT
Telecom
Manufacturing
Live Streaming
Corporate Banking
Healthcare
CSR
eGov
- Programming Language
Java
Python
JavaScript
- Data Pipeline
AWS Glue
AWS Athena
AWS S3
Data quality
Data Governance
Data Model
Apache Iceberg
AWS SQS and Kafka
RDS MSSQL, Postgres, MongoDB
Data Migration
Splunk Monitoring
DataOps
Terraform and CloudFormation
- Framework
Spring Boot
Quarkus
Flask
Open API
Kong
- Database
Cassandra
Postgres
Mysql
Redis
MongoDB
Dynamodb
- Machine Learning
NLP
Chatbot
Rasa
Spacy
Google DialogFlow
TensorflowJS Model use
Contextual Chatbots
ollma
crew.ai
Started Langchain
- Cloud
AWS
EKS
ECR
VPC, EC2
Auto-scaling
RDS
RDS scaling
HA
Load Balancer Types on AWS
Monitoring and logging using CloudWatch
- Cloud Native
kafka
Docker
Kubernetes
API Gateway
On-prim
AWS
Azure
Microservice
SRE
Observability
- AWS
VPC
ELB ALB
RDS
ECR
EC2
Scaling
EKS
IDM
CloudWatch
Container insight
Cost Optimization
- Azure
Azure VM
Resource Groups
Firewall
Container Insights
App services
Container Registry
- Tool
Postman
SoapUI
Jmeter
Git
Intellij
Docker Desktop
Virtual Box
Lens
SQL Developer
Pylint
PMD and FindBugs
Architect
Performance optimization, Architecture decision, HLD/LLD, Release plan, Automation, Migration, Code refactor, PI and Sprint Planning
Developer
Spring Boot, Quarkus, Rest API, Kafka, AWS, Kubernetes, Docker, Kong, Python Flask
DevOps and SRE
Observability, Open Source DevOps Stack, Monitoring, Scripting