How LinkedIn Authorizes 10 Million API Calls Per Second?

LinkedIn has millions of users today, so it manages 10 million API calls per second. This is achieved through advanced authorization systems and scalable architecture and this showcases its robust technological infrastructure. The platform uses distributed caching, rate limiting, and throttling to maintain efficiency and reliability. Each component, from token management to API gateways, is tailored to ensure secure and swift data handling. In this article, we will explore the strategies used to authorizes 10 Million API Calls Per Second.

LinkedIn’s API infrastructure is a complex network designed to handle millions of data requests every day. This system is crucial for supporting the diverse needs of users and third-party applications. The infrastructure is carefully crafted to ensure efficiency, security, and scalability.

• Layered Architecture: LinkedIn employs a layered architecture to handle millions of API calls efficiently.
• Global Data Centers: At the base, multiple global data centers store and process vast amounts of data. These data centers are interconnected using high-speed networks for rapid data transfer.
• Server Clusters: Each center hosts a cluster of servers that are optimized for speed and reliability. The servers are equipped with modern hardware that ensures high-performance operations.
• Virtualization Technologies: Above the hardware layer, virtualization technologies maximize resource utilization and scalability.
• Load Balancing: Load balancers distribute incoming API requests evenly across server clusters. This distribution helps prevent any single server from becoming a bottleneck.
• Redundancy: Redundancy is built into every layer to ensure continuous service during hardware failures.
• Advanced Monitoring Systems: Advanced monitoring systems track the health and performance of the entire infrastructure.These systems provide real-time alerts to prevent and quickly resolve potential issues.

Efficient authorization forms the backbone of secure, stable, and reliable API management, especially when handling millions of interactions typical for platforms like LinkedIn. Here is why efficient authorization is important or high-volume API calls:

• Ensuring Valid User Access:
  • Efficient authorization ensures that only valid users access LinkedIn’s API resources.
  • It protects the system against unauthorized access and potential security breaches.
  • By verifying user credentials quickly, it maintains a seamless user experience.
  • This speed is crucial for maintaining performance during peak usage times.
• Resource Management:
  • Efficient authorization helps manage and allocate system resources effectively.
  • It prevents system overloads by blocking excessive requests from unauthorized users.
  • This is essential for sustaining system stability and availability.
• Data Protection:
  • Efficient authorization protects user data from being accessed by unauthorized parties.
• Legal and Regulatory Compliance:
  • Compliance with legal and regulatory requirements is ensured through efficient authorization.
• Trust and Security Standards:
  • Efficient authorization builds trust among users and developers by upholding high security standards.

By implementing these practices, LinkedIn maintains a secure, stable, and user-friendly API infrastructure that meets legal requirements and fosters user trust.

Here is an overview of the evolution of LinkedIn’s infrastructure to meet growing demands:

• Initial Setup
  • Simple Server Setup: Managed limited traffic with a basic server configuration.
• Transition to Scalable Architecture
  • Adoption of Cloud Technologies: Enhanced flexibility and scalability through cloud solutions.
  • Advanced Data Storage Solutions: Implemented to handle the surge in data volume.
• Integration of Data Centers:
  • Regional Data Centers: Integrated data centers across different regions to reduce latency and improve response times for global users.
• Traffic Management Solutions:
  • Smart Load Balancers: Developed traffic management solutions including load balancers that dynamically adjust to traffic changes.
  • Machine Learning Models: Introduced machine learning models to predict and manage load spikes.
• Architectural Enhancements:
  • Microservices Architecture: Improved deployment speeds and scalability, allowing updates without disrupting the entire system.
  • Continuous Integration and Continuous Deployment (CI/CD): Adopted CI/CD practices to streamline updates.
• Data Security and Compliance:
  • Increased Focus on Security: Enhanced data security and compliance measures to maintain user trust and meet regulatory requirements.
• Outcome of Infrastructure Evolution:
  • Support for Growing User Base: Successfully scaled infrastructure to support millions of active users and billions of data interactions daily.

These are the considerations that are important for designing a scalable authorization systems-

• Design for concurrent requests: Systems must handle multiple requests simultaneously without delays. This involves structuring the authorization system to efficiently manage thousands of concurrent API calls. It ensures that the system remains responsive even under heavy user load.
• Use of scalable databases: Opt for databases that can expand as demand increases. Scalable databases allow for adding more storage and processing power as needed. This is crucial for maintaining performance during peak periods and as user numbers grow.
• Implement caching mechanisms: Cache frequently accessed data to reduce load times. Caching saves results of common queries, reducing the need to access the database repeatedly. This significantly speeds up response times for common requests and reduces system load.
• Employ load balancers: Distribute incoming API requests across multiple servers. Load balancers help prevent any single server from becoming overwhelmed. They ensure all server resources are utilized efficiently, improving overall system performance.
• Microservices architecture: Break down the system into smaller, independent components. Microservices allow different parts of the authorization system to scale independently. This flexibility helps manage resources more effectively and simplifies updates and maintenance.
• Auto-scaling capabilities: Automatically adjust resources based on current demand. Auto-scaling adds or removes resources based on real-time usage statistics. This ensures that the system scales up during high demand and conserves resources when demand is low.
• Robust session management: Efficiently handle user sessions at scale. Managing sessions properly ensures that user data remains secure while minimizing memory and resource usage. This is critical for maintaining both security and performance in high-load scenarios.

Below are the key components that work together to form a robust authorization flow:

• Authentication Server: It validates user credentials and issues tokens. This server checks the identity of a user or system trying to access resources. Upon successful validation, it grants a token that can be used for authorization.
• Authorization Server: It decides access levels and permissions for authenticated users. It evaluates the token provided by the user against access control policies. Based on this evaluation, it allows or denies access to requested resources.
• API Gateway: It serves as the entry point for all incoming API requests. It routes requests to appropriate services after initial authentication checks. It acts as a firewall to prevent unauthorized access before reaching backend services.
• Resource Server: It hosts the actual resources that users want to access. It responds to requests from users who have been granted access by the Authorization Server. It ensures that data requested is only sent back if the user has the necessary permissions.
• Database: It stores user credentials, access permissions, and tokens. It is critical for retrieving and verifying information during the authentication and authorization process. It helps maintain a record of all issued tokens and their associated access rights.
• OAuth Clients: These are the applications requesting access on behalf of the user. They interact with the Authentication and Authorization servers to obtain tokens. Use these tokens to request resources from the Resource Server on behalf of the user.
• Encryption Components: They secure data transmission in the authorization process. They encrypt tokens and sensitive data to prevent interception and unauthorized access. They ensure that communication between different components remains confidential and tamper-proof.

Token management is a crucial aspect of securing an API and ensuring that only authorized users can access certain resources. It involves issuing, storing, and validating tokens that represent a user’s permissions and authentication state. Proper token management can protect against common security threats such as token theft or misuse. It also ensures that users have a seamless experience without needing to re-authenticate frequently.

Here is how it works:

• Token Issuance: Assigns a token to a user upon successful authentication. This token acts as a digital key, allowing access to specified resources. It is generated by the Authentication Server once the user’s credentials are verified.
• Token Storage: Safely stores tokens on both the client and server side. On the client side, tokens can be stored in secure storage areas such as HTTPS cookies. Server-side storage involves maintaining a database of active tokens and their expiry details.
• Token Expiry and Renewal: Sets a validity period for each token to enhance security. Tokens are programmed to expire after a certain period to prevent long-term misuse. Upon expiry, users must re-authenticate or refresh the token to continue access.
• Token Validation: Checks the integrity and validity of the token with each request. Every API request includes token validation to ensure it’s still valid and hasn’t been tampered with. This is crucial for maintaining secure access and data integrity.
• Token Revocation: Allows tokens to be manually or automatically revoked. This feature is essential when a security breach is suspected or if the user logs out. Revocation helps prevent unauthorized access even if a token is stolen.
• Secure Token Handling: Implements best practices for token security. Techniques include using HTTPS for all communications, hashing where appropriate, and avoiding token exposure in URLs. These practices help protect tokens from being intercepted or misused by malicious actors.

Rate limiting and throttling are essential techniques used in API management to control the amount of traffic an API can handle within a certain period. By implementing these controls, LinkedIn ensures that the system remains stable and responsive, even under high demand. These practices prevent abuse and ensure equitable access to resources among all users, which is very important for a platform with millions of users like LinkedIn.

Here is how rate limiting and throttling function:

• Prevention of System Overload:
  • Ensures the API does not receive more requests than it can handle.
  • This helps maintain the service’s reliability and availability by preventing potential crashes due to overload.
  • It protects the system during unexpected surges in traffic, maintaining performance for all users.
• Fair Usage Policy Enforcement:
  • Distributes system resources fairly among users.
  • By limiting the number of requests a single user or client can make, LinkedIn ensures no single user monopolizes the resource availability.
  • This promotes a fair usage environment where all users have equal opportunity to access services.
• Enhanced Security:
  • Guards against denial-of-service attacks and other malicious activities.
  • Rate limiting can mitigate the effects of attackers or malfunctioning scripts bombarding the system with high volumes of requests.
  • This is crucial for safeguarding user data and service functionality.
• Cost Management:
  • Helps in managing operational costs by controlling the load on infrastructure.
  • By keeping traffic within expected and manageable limits, LinkedIn can optimize resource utilization and operational costs.
  • This is important for scaling the service economically as user base and data demand grow.
• Improved User Experience:
  • Prevents slowdowns by managing congestion.
  • Ensuring that no single user’s actions can slow down the system for others leads to a more consistent and reliable user experience.
  • This is essential for user satisfaction and retention.