About the Customer
Alligator Manufacturing is a leader in design, manufacturing, and sourcing, supplying promotional and retail products to clients worldwide. Their head office is in South Africa, with strong representation in China and sourcing agents worldwide, and they have grown extensively, supplying major corporations with a comprehensive range of products and providing end-to-end merchandising solutions.
Constantly innovating bespoke branded products; successfully manufacturing and sourcing single products or entire ranges; providing warehousing; developing and hosting online shops; and managing sales and distribution worldwide. They have successfully leveraged AWS core network to their advantage and created their shadow footprint expansion across contents by being able to scale with AWS EFS and AWS S3.
AWS S3 is designed to provide 99.999999999% durability and 99.99% availability of objects over a given year. Alligator has leveraged AWS to scale and grow the business extensively in developing and hosting online shops and managing sales and distribution worldwide.
Customer Overview – Storage Architecture
Primary Storage
- The best practice for Symantec Veritas data backup and recovery on an on-prem server was met.
- The backup was manually set up.
- The backups that were to expire were not placed on the same tape as the new backups.
Back Up & Recovery
- Backups and restorations are automated in AWS S3. Lifecycle rules were created to automate and carefully transition data through its lifecycle. Transitioning from 30-day Standard Storage to 60-day Standard Infrequently Accessed (IA) storage, where we set the transition to S3 Glacier for Archiving after 120 days.
- Data is securely preserved in all tiers of AWS S3 using bucket-level encryption and blocking all public access to account buckets by default.
- Thereafter, another rule was set to transition bucket objects to AWS S3 Deep Archive after 515 days being dormant, and then expires when the rule is triggered by the time factor set on the bucket as a rule.
- Data that has been archived can be retrieved based on retrieval timelines, depending on the type of storage the data resides in, upon a request to restore.
The Challenge
Data Storage
- Local storage has a limit on retention of Backups, and this led to the deletion of old, stale backups. The cost factor arising from an on-premise solution is redundant and unreliable disk failures.
Availability
- Disks would crash, and due to wear and tear, the devices would eventually fail, adding to the cost of ownership associated with such storage devices.
- Unpreparedness for unexpected power outages, weather conditions, and internet weather issues affecting availability, resulting in increased Latency.
- Data recovery and restoration is slower on-prem and would result in increased downtime
Durability
- Device Type – 90% of HDDs service for 3 years and 80% for 4 years, leading to an increase in procuring new HDDs in the long term.
- SSD usually has longer life spans; however, the customer issue was around the costs of ownership and maintenance of the drives.
Scalability
- Scaling Factor – Storage scaling with HDD and SSD would have to mean more overhead costs and system failures as a result of unplanned/unanticipated scaling.
The Solution
AWS Best Practices
Achieved all set out guidelines and standards.
AWS Well-Architected Framework
Based on best practices, we formulated the best architecture for customers to be able to use AWS Storage solutions with maximum security and minimum permissions.
Back Up and Recovery Plan
AWS provides 99.999999999% durability and 99.99% availability of objects stored on AWS S3, so there is minimal room for data loss if any should occur. Objects that are Infrequently Accessed (IA) are migrated to AWS Glacier (Deep Archive).
