Design, Architecture, and Migration of Data Services and Pipelines to GCP

  • Quickly assess, design, and deploy a solution and architectural patterns in GCE and GKE that will enable a series of microservices-based applications (currently running in AWS) that leverage Apache Kafka, MongoDB, and Streamsets or Confluent Kafka, Cloud Pub/Sub, Firestore, and Apigee

  • Design, implement and deliver an MVP Data Pipeline that includes data acquisition from an API into a message queue and data movement and or ELT/ETL into a data persistence layer

  • Design, implement and deliver an option for an MVP DevOps pipeline for failover, redundancy, auto-scaling, self-healing, and monitoring

  • Delivered detailed design and architectural documentation

  • Migrated application infrastructure onto GCP for the targeted architecture

  • Configured and deployed DevOps pipeline

  • Facilitated code review, testing, and provided testing scripts

  • Discover – Reviewed current capabilities, data flow, operational requirements, and technology and organizational constraints

  • Design – Architectural patterns, key technology components, short and long term roadmap

  • Develop – Pattern implementation and application migration, infrastructure and tools codified in an IaC paradigm

  • Deliver – Review all monitoring and CI/CD pipelines as well as pattern applicability to future use cases 

  • GCE and GKE

  • Terraform and Spinnaker

  • MongoDB, Kafka, Streamsets, Fluentd

  • Hashmap Data & Cloud Consulting Services including Solution Design, Architecture, Data Engineering, Migration, and Cloud Automation

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