Building DevOps pipeline with Docker Containerization
Development of frameworks and reference implementations with Microsoft Azure and Docker containers.
Real-time data ingestion and streaming analytics needed to be added to client’s current Systems of Intelligence (SOI), to facilitate capabilities for meaningful and actionable information for making informed business decisions and providing needed business support.
WATI provided the development of frameworks and reference implementations with underlying technologies: Microsoft Azure and Docker Containers. WATI’s solution included
- Develop, design, build microservices using Java/Spring/J2EE technology stack.
- Design, build and maintain the CI/CD infrastructure and tools to deliver products being developed Azure Cloud Service.
- Design and Develop the test automation to validate the builds in the CI/CD pipeline using Jenkins, Ansible and Python Scripts.
- Work closely with development teams and support teams to ensure that solutions are designed and developed with Analytics digital foundation architecture standards.
- Troubleshoot SOA/Rest Services, network, WAF/firewall, load balancer, HTTP/HTTPS communication, and browser clients as it pertains to a large-scale web application environment for the Applications which are developed using the Java/J2ee Standards.
- Integrate various data platforms using a wide variety of protocols like REST, SOAP, MQ, TCP/IP, JSON and others
- Develop scripts to a runtime infrastructure built on Docker, Kubernetes, Helm and other open source systems.
- Building and maintaining Kubernetes clusters in the cloud for service orchestration.
- Work with a team to automate management and orchestration tasks, streamline processes and perform standard administration functions as needed
- Monitor system performance, make recommendations to improve and implement system-wide changes to enhance overall system proficiency
WATI’s solution enabled data acquisition and staging capabilities that collect, tag and securely distribute structured and unstructured data (data in-motion and at rest) from internal and external sources to data stores or other processes in a timely manner. The availability of immense additional data positively impacted decision makers – people from senior leadership and management – from various disciplines such as point of care—service and sales, and members/patients who use diverse systems of engagement.