Why do it?
Many of our customers have encountered challenges with their legacy EDW or on-prem Apache Hadoop deployments. Doing Data Analytics at scale is another area of concern. In many cases, workload variability has meant that they have provisioned more resources than required or too much effort and time is lost on governance of the workloads instead of focusing on critical projects.
Migrating to Amazon EMR offers lower infrastructure costs, more efficient IT staff, better risk mitigation, and easy-to-use environments to develop and operate big-data applications.
Below are the ways in which Wipro helps its customers migrate to EMR -
- Lift & Shift - This is the simplest scenario with less number of changes and risk. Changes are limited to only those required to make the application work on the cloud. It reduces the unknowns and unexpected work
- Re-Architect - Involves easy scaling of components due to separation of compute and storage leading to increased productivity and lowered costs. It gives the flexibility to use transient compute resources
- Hybrid Architecture - It leverages aspects of both lift & shift and re-architect. This approach benefits from being able to experiment and gain experience with cloud technologies and paradigms before moving to the cloud
- Workload Modernization - These are powered by Wipro’s Accelerators leading to
- Auto conversion of ETL jobs to Spark on AWS – Powered by Wipro’s tool - NextGenDI
- Automated modernization of Hadoop workloads to AWS – Powered by Wipro’s tools -IntelliProc, BDRE on EMR
- Automatic migration of EDW workloads to Hadoop on AWS – Powered by Wipro’s tools- Move to BD, CDRS for AWS
Workshop Delivery Approach
A customer-specific migration path is designed based on a comprehensive assessment of the technology landscape and applications to arrive at the best-suited approach.
It consists of three parts -
- Workload selection - A cross section of workloads (by Geo, Function, LOB...) are selected to perform a feasibility assessment
- Workload assessment - The workloads are then classified to determine the risk to effort ratio of the migration. The Key data collected here includes: Sizing information, Availability, Latency, SLA requirements, security, control and access requirements
- The workloads are then translated to cloud stack and recommendations are made regarding: separation of compute and storage, sizing effort, and service cost estimates. Proof of concept recommendations are also given as the next step
Our customers have used this exercise to figure out the best approach based on the landscape as well as to build capability through trainings/POC to embark on their AWS journey.
Click here to get an exclusive Wipro workshop done for you on AWS EMR Migration.