How To Build Scalable, Resilient API Architectures with Apigee

APIs are at the heart of business growth and innovation today. Even during times of disruption, companies have continued to prioritize digital transformation. In fact, according to Google Cloud's "State of API Economy 2021" report, 75% of companies maintained their digital transformation efforts, with almost two-thirds increasing their investments. This tells us just how crucial APIs have become in supporting modern businesses.

To stay competitive, APIs need to be scalable, resilient, and reliable. When APIs automatically adjust to changes in demand, businesses can deliver a smooth customer experience, even during peak periods, while minimizing the risk of downtime and keeping costs in check. When APIs are available and performing well, it not only keeps customers happy but also helps improve brand reputation and fuel business growth.

At Crystalloids, we build API architectures that are resilient, scalable, and easy to maintain. In this blog, we’ll show you how we leverage Google Cloud Apigee, Load Balancer, and Cloud Run to create high-performance APIs that drive business growth.

Our Approach to Scalability

We design distributed, multi-regional API architectures using Apigee. This setup ensures that our APIs are always available, have low latency, and can handle regional outages seamlessly. 

Using Google Cloud Load Balancer, we direct incoming requests to the nearest Apigee instance, which helps reduce latency and efficiently manage traffic.

Entire lifecycle of HTTP request going through Apigee

Tackling Core Challenges

Managing traffic between Apigee and backend services is a common challenge. While Google Cloud Load Balancer handles routing to Apigee, Apigee itself needs to balance traffic to the backend services effectively. 

We use Apigee's built-in load-balancing features to handle unexpected traffic spikes and regional incidents smoothly, ensuring high availability.

We also ensure that all Apigee instances and backend servers can auto-scale to handle traffic efficiently, keeping performance consistent even during peak times.

Auto-Scaling for Traffic Management

Our architecture heavily relies on auto-scaling to keep systems stable and efficient during traffic surges. Apigee instances and backend services can scale up or down as needed, allowing the architecture to adapt to changing loads and maintain optimal performance.

Scalable Backends with Cloud Run

To make our backend services scalable, we use Google Cloud Run.

Cloud Run supports autoscaling based on CPU usage and can adjust the number of instances based on demand. This allows our backend to grow with user needs, without compromising performance.

Caching and Load Balancing

Caching is a great way to improve efficiency, especially when backend responses don’t change often. We use Apigee's caching features to store responses, reducing the load on backend services and improving response times.

Security Considerations

Security is a core part of building scalable APIs. For those unfamiliar, OAuth 2.0 is a framework that allows secure, delegated access, meaning users can grant websites or applications limited access to their information without sharing passwords.

API keys are unique identifiers used to authenticate requests, and role-based access control ensures that only authorized users can access certain resources. Rate limits are also set to control the number of requests a client can make, preventing abuse and ensuring that services remain responsive for all users.

In Apigee, we use OAuth 2.0, API keys, and role-based access control to protect data and prevent unauthorized access. Apigee also helps enforce rate limits, validate requests, and encrypt data, making our API infrastructure secure and compliant.

Monitoring and Observability

Monitoring keeps APIs resilient. Apigee provides analytics to track API performance and troubleshoot issues in real-time. We also use Google Cloud’s monitoring tools to get visibility into the health of the entire API ecosystem, helping us quickly identify and resolve any problems. 

Integrating Google Cloud Apigee into our DevOps pipeline has brought significant benefits, particularly in enhancing security, ensuring consistency, and improving control. Learn how we achieved this, the challenges we faced, and the benefits gained.

Best Practices for Scalable API Architectures

To build a successful API architecture, we focus on three main components:

1. Load Balancer

The Load Balancer directs traffic to Apigee, ensuring consistent performance and secure communication. It prevents bottlenecks by distributing incoming traffic evenly.

2. Apigee

Apigee, Google Cloud's API management platform, has been recognized as a Leader in the 2024 Gartner® Magic Quadrant™ for API Management for the ninth consecutive time.

This consistent recognition highlights Apigee's robust capabilities in building and managing scalable, resilient API architectures.

Apigee acts as the gateway for managing APIs. It helps route, scale, and monitor traffic effectively. Choosing the right Apigee environment (development, testing, or production) is crucial for achieving the best performance.

3. Backend Servers

Our backend servers use Google Cloud’s Cloud Run to handle fluctuating loads efficiently. This setup ensures they can scale automatically, maintaining high availability even during traffic surges.

Final Thoughts

At Crystalloids, we leverage Google Cloud technologies like Apigee, Load Balancer, and Cloud Run to build scalable and resilient API architectures. Our approach helps companies stay competitive by ensuring that their APIs are ready for growth and can handle today’s challenges while preparing for tomorrow.

If you need help building scalable API architectures, contact Crystalloids. We’d love to help you achieve your technology goals and take your data strategy to the next level.