About
Category
SaaS ,
Services
AWS infrastructure ,
A growing leader of SaaS-based solutions for taxi providers worldwide contacted Peerbits. Their platform empowers businesses with tools to manage drivers, taxis, live tracking, passenger delivery, food delivery, and parcel services. As their business evolved from a taxi-focused solution to a multi-service platform, they faced several challenges related to scalability, cost-efficiency, security, and high availability. As demand surged and complexities grew, they needed a system to support rapid growth and seamlessly scale to meet future demands.
The Challenges
- Scalability challenges : Struggling to handle rapid growth, from 10-20 customers to 200-1000, while maintaining system performance.
- Cost management issues : Difficulty in controlling infrastructure costs as the platform scales, risking exponential expense growth.
- Security concerns : Ensuring strong data protection and secure operations required constant vigilance that in turn increased complexity.
- Availability risks : Manual interventions in maintaining high availability led to inefficiencies and potential downtime risks.
The Solution
Scalable deployment
ECS : Enabled independent deployment and scaling of microservices like taxi management and food delivery.
MQTT Protocol : Ensured low-latency communication for real-time updates.
Apache Kafka : Facilitated high-throughput data streaming.
Autoscaling : Resources are scaled dynamically based on demand, ensuring cost-effectiveness.
Optimized data management
Layered database architecture : Segregated data into transactional, processing, and reporting layers for optimal performance.
AWS ElasticCache : Cached frequently accessed data to reduce response times.
Continuous deployment
Green/Blue pipeline : Enabled updates without downtime, with instant rollback.
Automation : Fully automated deployments reduced human error.
Robust Security
VPC : Provided a secure, isolated environment for resources.
WAF : Protected against DDoS attacks and malicious activities.
Data Encryption : Safeguarded sensitive customer and transactional data.
Monitoring & Alerting
Monitoring tools : Datadog, Grafana, Prometheus, and New Relic provided real-time insights.
Threshold alerts : Notified the team of anomalies for proactive resolution.
Key features
- ECS setup : Independent scaling of microservices.
- MQTT Protocol : Real-time, low-latency communication.
- Apache Kafka : High-throughput data streaming.
- Autoscaling : Dynamic resource scaling based on demand.
- Layered databases : Optimized performance for transactional, processing & reporting.
- ElasticCache : Reduced response times with data caching.
- Green/Blue pipeline : Zero downtime updates with rollback.
- VPC : Secure, isolated resource environment.
- WAF : Protection against DDoS and malicious attacks.
- Monitoring stack : Real-time insights with Datadog, Grafana, Prometheus & New Relic.
- Threshold alerts : Proactive anomaly detection and resolution.
Results
- Scalability : They can now scale effortlessly to meet the demands of a growing customer base, handling increased loads for each of their services.
- Cost efficiency : The layered architecture, autoscaling resources, and caching solutions optimized resource usage, keeping operational costs in check.
- Enhanced security : The secure VPC setup, along with WAF and other security measures, ensured data protection and compliance.
- High availability : With a robust deployment pipeline and real-time monitoring, the taxi service provider has achieved near-zero downtime and improved reliability.
Tech stacks we used
Programming language
Python, Apache Kafka (Java, Scala)
Cloud provider
Amazon Web Services (AWS)
Frameworks & Tools
Datadog , Grafana , Prometheus
