Hadoop Rapid Start Services
Big Industries’ Hadoop Rapid Start Services help you get up and running quickly with Hadoop in your organization, whether on-premise or on the Cloud. Our certified experts will build you a working implementation, demonstrate core functionality and prepare your users to take full advantage of the new features and benefits of the technology.
– Conduct Discovery session to discuss key points that will dictate deployment decisions
– Plan software layout for each server
– Discuss dimensioning and data requirements
– Validate environment readiness
Installation & Deployment
– Install & configure management console
– Setup HDFS (incl. High Availability)
– Configure Kerberos
– Setup YARN (incl. High Availability)
– Enable HDFS encryption
– Install Hive or Impala PDWH
– Install & configure HUE for LDAP authentication
– Install & configure Sentry for Hive/Impala access control
– Validate deployment
Transition to Operational support
– Hadoop cluster installed & configured ready for data ingestion
– Knowledge transfer on activities performed
– Integration & Operation Design document comprising High Level architecture and a detailed description of the configuration
– Hardware or Cloud environment is procured, installed, networked and operating systems are installed before the project starts.
Effort is based on the scope of the project, functional and technical requirements, size of the cluster and deployment context.
Build a custom Big Data Pipeline
Data ingestion and transformation is the next step in all Big Data projects. Hadoop’s extensibility shines of large volumes of varied and complex data, but the identification of key data sources and ingestion of the data into Hadoop can prove challenging. Big Industries will architect and implement a custom data ingestion pipeline to get your Big Data solution quickly bootstrapped.
A typical Hadoop Data Ingestion Pilot consists of the following activities:
– identify solution requirements to include data sources, transformations and egress points.
– Architect and develop a pilot implementation for up to 3 data sources, 5 transformations and 1 target Hadoop component
– Develop a deployment plan appropriate for the volume and velocity of data to be ingested
– Review the Hadoop cluster and application configuration
– Handover to application deployment team and support operational readiness testing cycles as required