Helping RSAC, a Fortune 500 manufacturing company take the Data to Insight leap

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Highlights

98%
of time potentially reduction
15 minutes
of Infrastructure deployment process reduced ETL
30 minutes
of processing reduced
Quick report generation
Scaled and reduced latency of ADHOC ETL processing requests

Client Profile

Reliance Steel and Aluminum Company (RSAC) is North America’s largest metals service center company, offering 100,000+ products and value-added processing and serving over 125,000 customers primarily by providing metals processing, inventory management services, and quick delivery.

Business challenges

  • Reliance Steel and Aluminum Company (RSAC), a Fortune 500 metal  services provider in North America holds 60 companies under its umbrella.  Each of these businesses operated independently of each other with their own  unique processes and on-premise technology setup. All data was siloed, and  the company had no way of analyzing it to derive insights. This lack of  insight to make data driven decisions impacted multiple aspects of their  business – from supply chain and sales optimizations to vendor and inventory management.  The business needed to be more responsive and become a data driven company.
  • Agilisium was hand-picked by AWS for our competency in helping organizations take the Data-to-Insight leap. As consultants, we provided a multi part solution that would onboard RSAC’s disparate on-premise data sources and systems into a Consolidated Enterprise Data Warehouse (CEDW). With this move up the information maturity curve, RSAC could then enable and accelerate strategic data initiatives, product development, and R&D.

Agilisium Solution

Enabling arobust technical foundation on cloud using DevOps

AUTOMATEDIAAS

  • IaaS was split into 4 broad categories like microservices. The setup aspects were automated via CloudFormation Templates with an emphasis on fail safe environment.

CI/CDPIPELINE

  • Cost effective open source tools were used to automate the CI/CD pipeline, drastically cutting time to market.

AUTOSCALE OUT ENVIRONMENT

  • Architecture incorporated AWS Autoscaling for EC2 instances and CloudWatch to ensure a reliable and scalable environment whatever the load.

STANDARDIZEDPROCESS

  • All Cloud Formation templates configured into an Ansible playbook for ease of use for end user.

Tech-stacks Used

AWS – S3
AWS EMR
AWS Aurora
AWS cloudTrails
AWS Cloudwatch
AWS SNS
AWS IAM
Airflow
Gitlab
Python

Business outcome

  • Infrastructure employment process reduced to 15 minutes, potentially reduction of 98% time when compared to manual deployment.
  • Faster ETL job deploy and execution process via CI/CD.
  • Increased productivity as developers can now focus on core jobs
  • DevOps culture encourages collaboration &eliminates silos..
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