The document summarizes Hailo's journey scaling their taxi booking app from 1 user to over 10 million users on AWS. It describes how their architecture evolved from a monolithic PHP/Java application running on a single AWS region in 2011, to a microservices architecture using Go and Java running on multiple regions by 2013. This allowed them to develop features faster, seamlessly deploy code changes, and scale servers automatically based on demand. The new architecture also improved reliability with fault tolerance and automated failover between availability zones.

1. Scaling from 1 to 10 million users
Boyan Dimitrov,
Senior Systems Engineer at Hailo

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The world’s highest-rated taxi app - over 13,000 five-
star reviews
To date, Hailo has carried more than 9 million
passengers
Hailo has over 50,000 registered taxi drivers
worldwide

5. November 2011: Hailo 1.0 Launch
Users: 1
Regions: eu-west-1
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6. eu-west-1
Java
MYSQL
PHP
Architecture specifics
• Monolithic PHP and Java applications
• Built and supported by 3-4 backend
engineers
• MySQL master-master replication for
resilience
• Multi-AZ since day 1
• City-specific environments
AWS specifics
Route 53 ELB S3
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7. Challenges
• Hard to develop new features
• Painful to push code changes
• Adding new instances and adding more capacity is a very slow process
• Unreliable and slow failover procedures
• SPOF
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8. December 2013: Hailo 2.0
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Users: 1 000 000+
Regions: eu-west-1, us-east-1, ap-northeast-1

9. Architecture specifics
• SOA architecture based on Go and Java
• Seamless service discovery, service to service communication,
monitoring and instrumentation
• Everything is automated
• Ability to scale services up and down based on demand
AWS specifics
Route 53 ELB S3
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Autoscaling Cloudfront Redshift

10. eu-west-1
Message
Bus+
Go
Services
Proxy Layer
Java
Services
C*
us-east-1
Proxy Layer
C*
ap-northeast -1
Proxy Layer
C*
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Distributed
Queue+
Message
Bus+
Distributed
Queue+
Message
Bus+
Distributed
Queue+
Go
Services
Java
Services
Go
Services
Java
Services

11. Challenges
• Hard to develop new features
Completing new features in days, not months
• Painful to push code changes
Seamless service deployment and ability to run multiple versions of a service
• Adding new instances and adding more capacity is slow
Our servers scale up and down based on demand
• Unreliable and slow failover procedures
Automated reaping of misbehaving services and AZ failover
• SPOF
Fault-tolerant distributed services architecture
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12. Important KPI
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13. The Future
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16. Tooling
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20. Thank you, any questions?
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