- Shaping future course of the organisation with innovative, cutting edge technology solutions.
- An industry veteran with 20 years of experience on Technology Leadership positions.
- Hands on Coding Architect on Pivotal Cloud Foundry and full stack java technologies
- Principal Architect on Enterprise technology stack comprising Cloud, SOA and Big Data Analytics.
- Enterprise Technology evangelist and enabler of Agile, Daikibo, SAFe and CI&CD.
- Pivotal Cloud Foundry
- Cloud Native Application development
- BOSH - App lifecycle management
- CI&CD - Concourse / Jenkins
- Service and Integration Telemetry
- Cloud Native Design Patterns
- Microservices Brick and Mortar design patterns
- RabbitMQ - AMQP messaging patterns
- Saga model of Distributed and Compensating transactions
- Microservices Development Frameworks, tools and components
- Spring Cloud
- Kafka Frameworks
- Netflix Microservices development tools (Eureka, Hystrix, Ribbon, Zuul)
- Java Full stack
- Data structures and Algorithms
Frameworks: Spring, Mybatis, Hibernate
Relational Databases: Oracle, MySQL, SQL Server
NoSQL Databases: MongoDB, Cassandra.
In-memory databases: Redis, Memcached
Backend languages: Node.js, Python, Ruby
Distributed architecture: RESTful Web Services and JSON.
Gradle and Maven build: Junit and Mockito
DevOps using Jenkins: Big Data (Hadoop, Pig, Hive, Hbase, Spark, Kafka, HortonWorks, BigInsights)
Agile: DevOps, Scrum, SAFe, Daikibo Legacy computing environment
Mainframe: COBOL/400, VAX COBOL, S/390
Midrange: VAX/VMS, AS/400
Client Server: Oracle, Visual Basic, Unix, C, Pro C, Pro COBOL
- Chief architect on Cloud native architecture, Microservices and DevOps platforms working on IP's and unique product / framework offerings on cloud-based technology perspective for the company. Also playing an advisory role on Big Data / Analytics solutions.
- Technology used:
- Spring boot
- Pivotal Cloud Foundry
- RabbitMQ / Kafka
- Cloud Native Architectures
- Netflix OSS
- MongoDB and Cassandra
- Rewrite an existing messaging app from a monolith MQ-series based architecture to a springboot based Microservices architecture using cloud native tools hosted on Pivotal Cloud Foundry. The app was developed using a Saga model of distributed transaction to mimic the XA distributed transaction over disparate resources. Zipkin traces were used along with Spring sleuth to have the traceability of the requests.
- The following features were used:
- Saga model for compensating distributed transactions
- XA Distributed transaction
- Zipkin and Spring cloud sleuth traces
- API Gateway
- Config server
- Circuit breaker
- Spring boot / Spring retry framework
- Asynchronous event driven messaging framework
Enterprise Solution Architect
- Development of Microservices - Authentication (OAuth), Logger, Push Notification and Data Management System (using Spring Cloud Data flow) which was deployed in Cloud Foundry and available in the market place. For the end users Rest services with JSON were exposed to utilize the functionality. Implementation done using the following:
- Spring Boot based architecture running on Pivotal Cloud Foundry
- RDBMS as MySQL and NoSQL as Cassandra
- Patterns for constructing individual (micro)services.
- Concurrent execution
- Brick Telemetry
- External Configuration and Runtime Reconfiguration
- Patterns for composing individual microservices into complete distributed systems.
- Service discovery and API gateway
- Service Aggregation
- Event Sourcing and CQRS.
- AMQP messaging with RabbitMQ
- Redis based in-memory caching.
- About the project:
- The source application was a monolith developed in legacy struts and JSF framework. It was broken down to the level of Microservices using the Domain Driven Design and Bounded Context techniques. The JSF sessions data was scaled using Redis in-memory cache. This is done using spring boot’s embedded tomcat along with springboot’s redis dependencies and JoinFaces JSF dependencies (Joinfaces is a library that enabled JSF with springboot). The application used a shopping cart with a payment gateway which was re-architected to use RabbitMQ as the event-queue as well as doubling up to be an asynchronous repository of items to be checked out eventually.
- The deployment of the application was done using Concourse and the app lifecycle was maintained using a manifest driven BOSH.
- Created a hybrid Data Lake solution with an on-premise IBM ODP along with a AWS hosted data lake on Amazon S3.
- A tableau reporting architecture was created using in-memory TDE’s and a parallel computing strategy. The semantic layers consumed by Tableau are built upon the Hive abstractions of the Data Lake as well as on the Data Mart of the downstream snapshots/aggregates hosted on a Netezza AMPP Data warehouse.
- The dashboard for customer 360 was done using an open source solution of reporting tool Jasper which was deployed onto AWS with a scaling factor to counter the elastic demand of consumers.
- The analytics solution is created in IBM PCI/SPSS stack as well as custom R code. An Analytics server pushes the propensities over to a MapReduce / Spark framework via an Ambari cluster. An Optimization node is used to run the iLOG/CPLEX rules. The entire solution being orchestrated with an event based on-premise IIB instance. The event queues refresh the analytics / propensity scores as well as the Tableau reports.
- The solution also deploys Confidential home grown Pristine MDM solution. It publishes best-of-breed master data to a cloud hosted IIB server and gets consumed by AWS hosted upstream applications.
- Created a customer 360 application hosted as a service over a hybrid IIB deployment topology on-premise as well as on Amazon S3. This enables to have a single view of the customer with a 360-degree coverage of all possible intelligence across the org and business silos.
- Creating a QlikView based Reporting Solution hosted in AWS.
- Working as Technology advisory for Enterprise architecture platforms for SOA, Big Data, Massively parallel processing architecture, Data / process replications and BI.
Technical Program Manager
Technology Stack: Java, JEE, Spring, Hibernate, Apache, Node.js, SOLR, Redis, Oracle, Weblogic, Linux, Alfresco, Hadoop, Liferay.
- Benefit related documents ingested at a rate of 125 files per second, parsed and getting stored in PDF formats on a zookeeper administered SOLR and Alfresco cluster on a two node Weblogic server hosted on Linux boxes - with in-memory session state replication.
- The parsers run on Node.js and redis platform to achieve a seamless non-blocking I/O.
- The application later was re-written with a horizontally scalable key-value data store with in-built replication / share capability.
- The other project of the same program enabled the contents ingested to be viewed over the OSB through a Web Service consumed by a solution built on top of a Liferay portal platform.
- The total portfolio opportunity was close to a million dollar in the short term and a few billion dollars in the long term.
Group Project Manager
Technology Stack: Java, JEE, Spring, Hibernate, Apache, Hybris, Linux, Android, Objective C, iOS, Hadoop, SAS.
Agile Processes: SCRUM, XP, TDD, BDD
- Hosting an iOS mobile app on betting and gaming domain with social and analytics plugin. The app used to host the mobile version of Ladbrokes in it’s native safari and used to handle the external value adds like push notifications, social and analytics plugin.
- Incubated the practice of Big Data analytics, clickstream analytics and AaaS (Analytics as a Service) for customers - specially in social media, travel and retail space. This comprised accessing data of demand fluctuation and pricing, as well as value / frequency analysis of shopping’s and purchases against external factors such as seasonal aspects.
- Incubated the concept and led the project to implementation for the product prototype on clicksteam analytics on social media, travel and retail space.
- Was also responsible for setting up the Agile practices (SCRUM, XP, TDD and BDD) for the programs and showcased a number of best practices to our customers. Moving from a traditional iterative process to Agile process had enabled a 40% direct and 68% indirect revenue impacts on the Gross and Delivery margins across the organization.