Transforming Video Hiring Platform Infrastructure with AWS Modernization
Optimizing infrastructure through AWS-managed services and automated scaling
15% Cloud cost reduction
due to serverless migration
60% Improvement
in infrastructure management efficiency
About the Client
A human resources technology company offering a video-first recruitment platform that modernizes hiring through short-form candidate profiles and swipe-based interactions. The platform helps employers assess candidates holistically, improving hiring efficiency, engagement, inclusivity, and long-term employee retention.
Industry
Human Resources Technology
Years in business
3+ years
Employee count
10+
Presence
United States
“Forgeahead helped us modernize our cloud infrastructure in a way that improved scalability, reliability, and overall efficiency for our research platform.”
Dr. Michael Harrington
Chief Information Officer
the need
A video-based hiring platform faced growing infrastructure and cost challenges as it scaled. It required stronger data security and access controls to protect sensitive candidate and organizational data.
Operational overhead increased due to reliance on EC2 and EBS management, while always-on infrastructure drove rising costs for predictable workloads. Inefficient autoscaling led to overprovisioning during traffic spikes, and non-critical workloads lacked a cost-optimized execution approach. Limited visibility into cloud spending further constrained financial governance and risk control.
The platform needed a more secure, scalable, and cost-efficient infrastructure model with improved operational visibility.
the solution
Forgeahead implemented a comprehensive AWS-native modernization strategy to enhance scalability, strengthen security, and optimize cost efficiency across the platform.
Data security was significantly improved by enforcing encryption across storage and transport layers. AWS services such as S3, EFS, and EBS were configured with encryption at rest, while TLS was used to secure data in transit, ensuring end-to-end protection of sensitive information.
To reduce infrastructure management overhead, the platform adopted a suite of AWS-managed services, including AWS Lambda, SQS, SNS, SES, S3, and Load Balancers. This shift improved operational efficiency and reduced the need for manual infrastructure maintenance.
A dynamic scaling architecture was introduced using AWS Auto Scaling and Launch Templates, enabling the system to automatically adjust capacity based on real-time demand and eliminate overprovisioning. Non-critical workloads were migrated to AWS Lambda, improving cost efficiency by eliminating the need for persistent infrastructure for background processing tasks.
Traffic and load optimization mechanisms, including rate limiting and throttling, were implemented to handle spikes more effectively and ensure consistent resource utilization. A resilient processing model based on a fail-fast approach and queue-based processing improved system responsiveness and prevented failure propagation across services.
To strengthen financial governance, AWS Cost Explorer, Cost Anomaly Detection, budgeting tools, and TCO analysis were implemented, providing deeper visibility into cloud spending and enabling proactive cost control.
The Impact
60% Faster Deployments
Reduced deployment time through optimized pipelines and streamlined release processes.
15% Reduction in Cloud Costs
Achieved cost savings through workload optimization, right-sizing, and improved resource utilization.
Stronger Security Posture
Enhanced protection through encryption, controlled access, and proactive threat detection.
Simplified Infrastructure Management
Reduced operational complexity by shifting to AWS-managed services.
Improved Financial Visibility
Enabled full cost transparency with real-time monitoring and anomaly detection.
High Availability at Lower Cost
Maintained resilient performance through auto-scaling and right-sized infrastructure.
Role of AWS
AWS played a foundational role in enabling a secure, scalable, and cost-efficient transformation of the platform. AWS Lambda supported serverless execution for non-critical and event-driven workloads, improving efficiency and reducing infrastructure dependency.
Secure data storage was achieved through AWS S3, EFS, and EBS with encryption enabled across all layers. AWS WAF and rate-limiting mechanisms strengthened traffic control and enhanced platform security. AWS Auto Scaling ensured dynamic capacity management aligned with real-time demand, improving performance and cost efficiency simultaneously.
Financial governance was significantly improved using AWS Cost Explorer and Cost Anomaly Detection, which provided real-time insights into spending patterns and enabled proactive cost optimization.
Tech Stack
The platform leveraged AWS EC2 and AWS Lambda for compute and serverless workloads. Storage and data services included AWS S3, AWS EFS, and AWS EBS. Messaging and integration were handled through AWS SQS and AWS SNS.
Security and networking were strengthened using AWS WAF and TLS encryption, while AWS Auto Scaling and Launch Templates enabled dynamic scaling. Cost management was supported by AWS Cost Explorer and AWS Cost Anomaly Detection.