7 ways to step up your API performance.

User nowadays expect performant system, immediate response and seamless interactions with their day-to-day applications. Here comes in the use of API (Application Programing Interfaces) to improve user experience and to have potential positive business impact. The good performance of your system relies on your API performance. It is critical to perform some few actions to ensure the proper functioning of this software. Before any deep dive, let's review some basic notions.

What is an API?

This is a bridge that enables communication between software components. It is a collection of a set of protocols and subprograms that allows applications or/and different programs to interact together. APIs are mostly found on different servers and often refer to as server side.

How APIs work?

Client-side developers also known as frontend developers are the ones who mostly interact with APIs. A request from the client side is sent to via the APIs which is processed, and a response follows this and sent to the frontend. This communication is basically what an API is meant for.

Some few API use cases:

• Implementation of various functionalities in software like login and signup
• Creation of efficient software
• Cloud collaboration
• Twitter bots
• PayPal payments

Types of APIs

An API provide set of rules which defines how one application can communicate with another. We have about four types of APIs which describe or defines how communication between our application components is achieved.

1. REST (Representational State Transfer):
   This is a style of API that uses HTTP methods (such as GET, POST, PUT, DELETE) to perform operations on resources identified by URLs. REST APIs are based on the principle of statelessness, meaning that each request contains all the information necessary to process it, and the server does not store any client state. REST APIs are widely used for web applications, mobile applications, and cloud services, as they are simple, flexible, and scalable.
   Companies like Spotify, Instagram, HubSpot, The Practical Dev and Twitter make use of REST APIs.

2. SOAP (Simple Object Access Protocol):
   SOAP (Simple Object Access Protocol): This is a protocol that uses XML to exchange structured data between systems over the internet. SOAP APIs are based on the concept of remote procedure calls (RPCs), meaning that the client invokes a specific function or method on the server and receives a response. SOAP APIs are often used for enterprise applications, web services, and distributed systems, as they are standardized, secure, and reliable.
   Amazon AWS, Salesforce, Microsoft Dynamic, Telecommunication operators, some banking and fintech applications.

3. GraphQL:
   This is a query language and a runtime system that allows the client to specify the exact data it needs from the server. GraphQL APIs are based on the concept of a schema, which defines the types of data and the operations that can be performed on them. GraphQL APIs are useful for complex applications, dynamic data sources, and performance optimization, as they reduce over-fetching and under-fetching problems, and allow for flexible and efficient data fetching.
   Some companies who use this include GitHub, Netflix, Shopify, Facebook, Coursera.

4. gRPC (gRPC Remote Procedure Calls):
   This is a framework that uses HTTP/2 and protocol buffers to enable fast and efficient communication between microservices. gRPC APIs are based on the concept of bi-directional streaming, which allows the client and the server to send and receive multiple messages in a single connection. gRPC APIs are suitable for low-latency, high-performance, and scalable applications, as they support multiple languages, platforms, and environments.
   Slack. Microsoft, Netflix, Cisco extensively use this type of APIs.

The choice of the API type you are to make solely depends on your skills set, requirements and use case.

Step up the API performance

After choosing the API we might encounter some performance issues and making it better can be summarized in 7 different ways.

1. Design and Architecture:

• Using lightweight data formats like JSON or protocol buffers for faster serialization.
• Implementation of caching mechanisms to store frequently accessed data reducing the hits and the database and the loads on the server.
• Using HTTP compression like GZIP to reduce the size of the file and data being transferred.
• Proper API versioning helps manage changes efficiently without impacting performance.

2. Database Optimization:

• Ensure proper indexing of database columns that are frequently queried.
• Use connection pools to reduce the overhead of establishing connections to the database.
• Write efficient database queries to minimize response times and resource consumption.
• In some cases, denormalizing your database can reduce complex joins and improve read performance.
• For extremely fast data retrieval, consider in-memory databases like Redis.
• Package your API into containers (like Docker) for portability, scalability, and resource isolation. Usually known as containerization.
• Replicate data across geographically dispersed servers for faster access and improved disaster recovery.

3. Infrastructure:

• Add more servers to handle increased load, improving throughput and redundancy.
• Distribute incoming requests across multiple servers to ensure no single server becomes a bottleneck.
• CDNs can cache API responses geographically closer to the user, reducing latency.
• Break down your application into microservices to improve scalability and performance.
• Consider serverless computing to dynamically manage the allocation of machine resources. AWS is a good reference for this.

4. Code Optimization:

• Use asynchronous operations to prevent blocking I/O operations from slowing down your API.
• Design your API to handle multiple requests concurrently.
• Minimize External API Calls: External API calls can significantly impact performance; cache results where possible.
• Minimize overhead by optimizing object serialization and deserialization.
• Code Profiling: Regularly profile your code to identify and optimize bottlenecks.

5. API Design, Security and Compliance:

• Use fast, secure authentication mechanisms like OAuth 2.0 or JWT.
• Protect your API from overuse and abuse by implementing rate limiting.
• Use HTTPS, but optimize SSL/TLS for performance.
• Use of Rate Limiting Algorithms. Explore different rate limiting algorithms (token bucket, leaky bucket) for more granular control and fairness.
• Define your API using OpenAPI (Swagger) to improve developer experience and documentation.

6. Monitoring and Testing:

• Implement real-time dashboards to visualize API performance metrics and proactively identify issues.
• Set up alerts based on user metrics like perceived latency and application crashes for better user-centric monitoring.
• Conduct A/B testing of different performance optimizations to measure their impact and ensure effectiveness.

7. Client-side Optimization

• Reduce the number of API calls by batching requests together.
• Only fetch data when changes occur, rather than polling at regular intervals.
• Use WebSockets for efficient, real-time data exchange.

Conclusion

With the above listed methods, you have a wide range of possibilities to optimized your APIs and step up performance of your systems and thus improving user experience.