Cloud Modernization for Tribesquare Technologies Inc

Problem Statement/Definition

Tribesquare Technologies Inc, a fast-growing technology company in Africa, encountered increasing challenges with resource allocation, system performance, and data security as their customer base and platform complexity expanded. Their existing cloud infrastructure lacked the flexibility and efficiency needed to scale dynamically, manage high traffic volumes, and ensure compliance with modern cloud security standards. This limited their ability to innovate and respond to user needs effectively.

Proposed Solution on AWS

Transnet Cloud delivered a comprehensive modernization roadmap using AWS Maturity Services and Growth Optimization. The engagement involved:

1. Migration & Assessment using AWS Cloud Migration Services (S-0066090) for seamless transition to AWS with minimal downtime.
2. Cloud Growth Optimization (S-0066096) for long-term efficiency, using auto-scaling, monitoring, and right-sizing strategies.
3. Deployment of Cloud Management Tools through a hybrid Managed + Professional Services model.
4. Implementation of IAM policies, network segmentation, and security best practices across workloads.
5. Integration of monitoring dashboards and CloudWatch metrics to gain visibility into system health and usage

Database Optimization Highlights:

1. Application refactoring to split read/write workloads, utilizing RDS Read Replicas for performance.
2. CloudWatch enabled for proactive monitoring (CPU, latency, IOPS)
3. Tuning of RDS Parameter Groups and use of Reserved Instances (RIs), resulting in 30% cost savings.
4. Multi-AZ Deployment, enhanced security posture, and 99.99% uptime guaranteed critical availability.
5. Daily automated backups, right-sizing, and storage auto-scaling helped reduce operational overhead and manual intervention.e

Solution Characteristics

1. Database Engine: Amazon RDS for MySQL
2. Multi-AZ Deployment: Yes.
3. Initial DB Size: 10 GB (with 10% projected annual growth)
4. DB Structure: 95 Tables, 60 Constraints, 12 Indexes
5. Peak Concurrent Connections: 140 during peak hours (12PM-6PM WAT)
6. Backups: Daily, 7-day retention
7. Monitoring: Enhanced monitoring enabled via CloudWatch

Outcomes & Success Metrics

60% improvement in infrastructure scalability to support increased traffic without latency.

45% increase in operational efficiency through automation and optimized deployment.

Zero downtime during migration due to phased rollouts and failover planning.

Full AWS integration for production and test environments, improving agility and innovation capacity

TCO Analysis

A thorough Total Cost of Ownership (TCO) assessment was conducted to compare legacy cloud and on-prem infrastructure with AWS’s optimized service model. Results showed:

1. 38% projected savings over 24 months
2. Reduction in CAPEX through elimination of hardware overhead
3. Improved budget management via AWS tagging, auto-scaling, and Reserved Instance usage
4. Higher ROI from faster performance, enhanced uptime, and developer productivity

This analysis helped gain leadership buy-in and AWS support alignment.

Lessons Learned

1. Early stakeholder alignment is critical, especially in high-growth environments.
2. Modular cloud architecture simplified scaling during traffic spikes.
3. Continuous feedback loops improved delivery and client satisfaction.
4. Visibility into cost, performance, and usage is key to sustainable growth.

Use Cases

Cloud Modernization, Database Optimization, Scalability, Performance Tuning, Managed Services

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