American Security is one of the largest providers of connected safes to both consumers and small businesses. Their CashWizard online portal enables their customers to modify safe configurations and view a wide variety of reports to track and audit user activity with a safe.
“Protagona has been great to work with. They quickly understood our technical needs, resources capabilities and adapted to them. Throughout the engagement communication and transparency has been key in keeping the project moving forward. I particularly appreciate their ability to help bridge the understanding of the non-technical individuals.” – Mara Ghisani
Challenge
As American Security’s customer base grew, the volume of data CashWizard was required to process became too large for a traditional relational datastore. Complex aggregation and archival jobs needed to be run on a consistent basis to keep the data at a manageable size for reporting performance. Quickly approaching the limits of their relational database cluster, American Security recognized they needed to pivot. They partnered with Protagona to rethink their data strategy.
Solution
Protagona began by analyzing the current volume of data and the payloads for each request. They then explored what the end state of the data should look like to end users as they generate audit reports and other analytics. Taking into consideration the expected customer growth, Protagona designed a multi-stage data lake to accommodate both current and future pain points related to data ingestion and report processing. As the structure of the data lake was deployed, AWS Database Migration Service was used to migrate data from SQL Server into the data lake. This was a huge foundational step to add more external system integrations, and ingest data feeds from their IoT implementation.
Tech Stack
- AWS VPC
- AWS Lambda
- Amazon S3
- Amazon SQS
- Amazon DynamoDB
- AWS API Gateway
- AWS Database Migration Service
- AWS ElastiCache
- Terraform
Outcome
Performance
By moving away from batch processes and embracing an event-driven architecture in AWS, the average processing time for event data used by customer reports was reduced by more than 80%.
Data Retention
Leveraging Amazon S3 as the primary datastore eliminated the need to continually run complex data archival jobs. This also enabled American Security to define data retention policies based on the classification of data.
Cost
Shifting to Amazon S3 reduced the need for secondary reporting databases and the infrastructure required to support execution of background aggregation and archival jobs. Not only did this increase data retention limits, but these efficiencies have also led to cost savings of more than 70%.