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Case Study: Skyscanner and AWS: Accelerating Growth with Cloud Solutions
Case Study: Skyscanner and AWS: Accelerating Growth with Cloud Solutions
OverviewSkyscanner, a leading travel search engine founded in 2003, connects over 100 million travellers monthly to flight, hotel, and car-hire options worldwide. As the company rapidly expanded, it faced significant challenges in maintaining performance and scaling its infrastructure. To future-proof its business and ensure a seamless user experience, Skyscanner migrated its technological stack to Amazon Web Services (AWS), improving reliability, reducing costs, and accelerating innovation.
Problem StatementIn 2020, Skyscanner's infrastructure faced a critical vulnerability: its entire global traffic was routed through one Amazon EC2 instance in a single region. This setup created a single point of failure, risking downtime and poor user experience due to latency issues. Skyscanner, a platform handling over 100 million unique users and 1.5 billion daily API requests, could not afford these risks. Downtime, slow response times, and failures could lead to users migrating to competitors.
Challenges:
Solution: Migrating to AWS Global Accelerator and Amazon CloudFrontSkyscanner tackled these challenges by adopting AWS Global Accelerator and Amazon CloudFront, improving fault tolerance, optimizing costs, and boosting overall performance.
Results and AchievementsBy leveraging AWS services, Skyscanner significantly improved its operational efficiency, performance, and scalability.
Future Strategy: Blue-Green Deployment and Continuous InnovationSkyscanner’s success with AWS has paved the way for future innovations. The company plans to adopt a blue-green deployment strategy to enhance its release processes and minimize downtime during updates. This method will allow Skyscanner to maintain two identical environments for safe deployment and rollback of changes, further improving service reliability.The migration to AWS also allowed Skyscanner’s engineers to focus on more valuable work. By relying on AWS’s global infrastructure and services like AWS Shield (for DDoS protection) and CloudFront, the company can continue innovating and maintaining its leadership in the competitive travel market.
ConclusionSkyscanner’s migration to AWS transformed its business operations, delivering cost savings, increased scalability, and enhanced fault tolerance. With AWS Global Accelerator and CloudFront, Skyscanner improved response times by 98%, reduced costs by 50% for CDN usage, and maintained zero downtime across its global operations. These strategic moves have positioned Skyscanner to continue innovating and growing, ensuring that it can meet the demands of its global user base with high performance and reliability.
Skyscanner Improves Response Time by 98% Using AWS Global Accelerator
Problem StatementIn 2020, Skyscanner's infrastructure faced a critical vulnerability: its entire global traffic was routed through one Amazon EC2 instance in a single region. This setup created a single point of failure, risking downtime and poor user experience due to latency issues. Skyscanner, a platform handling over 100 million unique users and 1.5 billion daily API requests, could not afford these risks. Downtime, slow response times, and failures could lead to users migrating to competitors.
Challenges:
- Single point of failure in traffic routing
- High latency affecting user experience
- Limited fault tolerance, risking global outages
- Increasing costs related to content delivery
Solution: Migrating to AWS Global Accelerator and Amazon CloudFrontSkyscanner tackled these challenges by adopting AWS Global Accelerator and Amazon CloudFront, improving fault tolerance, optimizing costs, and boosting overall performance.
- AWS Global Accelerator: AWS Global Accelerator allowed Skyscanner to distribute traffic across multiple AWS regions, eliminating the risk of a single point of failure. It provided static IP addresses for users to connect through the closest AWS edge locations, reducing latency and improving user response times.
- Improved Response Time: Skyscanner achieved a 98% reduction in response time, decreasing it from 200 milliseconds to under 4 milliseconds.
- High Fault Tolerance: AWS Global Accelerator’s failover mechanism ensured that traffic was rerouted to the next healthy region within 30 seconds in case of regional outages.
- Cost Savings: By shifting from Amazon EC2 On-Demand Instances to Spot Instances, Skyscanner reduced infrastructure costs by 70%, more than covering the cost of AWS Global Accelerator.
- Amazon CloudFront: Skyscanner also migrated its content delivery network (CDN) to Amazon CloudFront, streamlining its technology stack and enhancing global content delivery.
- 50% CDN Cost Reduction: By utilizing AWS CloudFront’s efficient content distribution, Skyscanner halved its CDN costs while maintaining high performance.
- Improved Cache Efficiency: CloudFront delivered a 99.99% cache-hit rate for images, speeding up content delivery and enhancing the user experience.
- Serverless Image Handling: Skyscanner developed a serverless image handler using CloudFront, automating the compression of static content and further optimizing costs.
Results and AchievementsBy leveraging AWS services, Skyscanner significantly improved its operational efficiency, performance, and scalability.
- Performance Improvement: AWS Global Accelerator drastically improved Skyscanner’s response times. The platform’s response speed increased by 98%, from over 200 milliseconds to less than 4 milliseconds, enabling a more seamless user experience.
- Global Availability and Zero Downtime: Through multi-region deployments and AWS’s automated failover capabilities, Skyscanner achieved zero global downtime. Even with traffic rerouted across AWS regions during outages, user experience remained unaffected.
- Cost Optimization: Migrating to Spot Instances and leveraging CloudFront’s cost-effective CDN management allowed Skyscanner to cut costs by 50% for content delivery, while the shift to Spot Instances resulted in 70% monthly savings on infrastructure.
- Increased Scalability: With CloudFront’s 99.99% cache-hit rate and the ability to handle up to 1.5 billion API requests per day, Skyscanner was able to scale its operations without incurring significant additional costs. The serverless architecture enabled by AWS CloudFront further allowed the company to innovate rapidly while managing large volumes of content.
- Simplified Infrastructure Management: The AWS migration reduced the complexity of managing Skyscanner’s infrastructure. By consolidating various services into AWS-managed solutions, Skyscanner reduced the number of components needed to operate its platform, cutting lines of code from 26,000 to just 1,000.
Future Strategy: Blue-Green Deployment and Continuous InnovationSkyscanner’s success with AWS has paved the way for future innovations. The company plans to adopt a blue-green deployment strategy to enhance its release processes and minimize downtime during updates. This method will allow Skyscanner to maintain two identical environments for safe deployment and rollback of changes, further improving service reliability.The migration to AWS also allowed Skyscanner’s engineers to focus on more valuable work. By relying on AWS’s global infrastructure and services like AWS Shield (for DDoS protection) and CloudFront, the company can continue innovating and maintaining its leadership in the competitive travel market.
ConclusionSkyscanner’s migration to AWS transformed its business operations, delivering cost savings, increased scalability, and enhanced fault tolerance. With AWS Global Accelerator and CloudFront, Skyscanner improved response times by 98%, reduced costs by 50% for CDN usage, and maintained zero downtime across its global operations. These strategic moves have positioned Skyscanner to continue innovating and growing, ensuring that it can meet the demands of its global user base with high performance and reliability.
Skyscanner Improves Response Time by 98% Using AWS Global Accelerator
I have written this case study with help from ChatGPT. I used AWS Machine Learning, along with other websites and blogs to compile the information and then used ChatGPT to format it for me in a more concise and structured manner. I have also added YouTube videos on the topic.
I have written this case study with help from ChatGPT. I used AWS Machine Learning, along with other websites and blogs to compile the information and then used ChatGPT to format it for me in a more concise and structured manner. I have also added YouTube videos on the topic.
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