Client-side Global Server Load Balancing (CS-GSLB) is a method of distributing network traffic across multiple geographically dispersed servers using logic executed on the client side, rather than relying solely on server-side or DNS-based mechanisms. It is used to improve performance, availability, fault tolerance, and scalability of web-based services, particularly in multicloud or hybrid-cloud environments.

Unlike traditional Global Server Load Balancing (GSLB), which depends on DNS-based redirection or dedicated load balancing appliances, CS-GSLB delegates the decision-making process to the client application, browser, or embedded script. This technique enables real-time evaluation of server health, performance, and proximity directly from the user's device.

CS-GSLB enables end-user devices or client applications to intelligently choose the most appropriate server or data center to connect to based on dynamic criteria. These criteria may include:

• Latency or round-trip time (RTT)
• Geolocation
• Server load or availability
• Cost or reliability of the cloud provider
• Data residency or compliance requirements

Clients typically retrieve metadata about available servers using lightweight mechanisms such as DNS TXT records, HTTP endpoints, or embedded configuration files. Based on this information, the client then initiates a direct connection to the optimal server without requiring intermediary redirection.

Client-side GSLB generally follows a pattern that includes:

1. Data distribution: A configuration file or DNS TXT record contains information about available backend servers, including addresses, health indicators, priorities, and weights.
2. Client logic: JavaScript in a web app, native mobile code, or SDK libraries evaluate the server list and select one based on programmable logic.
3. Connection initiation: The client establishes a connection directly with the chosen server, typically using HTTP(S), WebSocket, or another application-layer protocol.
4. Failover: If the selected server is unreachable, the client can retry other candidates without consulting external infrastructure.

In client-side global server load balancing, dynamic server selection refers to the real-time evaluation process through which the client chooses the most suitable backend server from a list of available endpoints. This selection is based on dynamic parameters such as measured network distance, server load, service response time and energy efficiency. By performing this logic on the client, applications can respond immediately to changing network conditions and improve user experience without relying on external redirection services.

• Low latency: By evaluating options in real-time, clients can select the nearest or fastest server.
• Greater control: Developers can fine-tune selection logic without being constrained by DNS TTLs or third-party services.
• Bypasses DNS limitations: Works well in scenarios where DNS-based load balancing is unreliable due to caching or propagation delays.
• Resiliency: Enables fast failover between regions or clouds without relying on central infrastructure.

• Increased client complexity: Logic must be implemented on every client platform.
• Security considerations: Information about server infrastructure must be exposed to the client, which may raise security concerns.
• Dependency on client execution: If client logic fails or is blocked (e.g., by browser extensions), load balancing may degrade.

• Multicloud deployments where traffic must be distributed across providers like AWS, Azure, and Google Cloud.
• Edge computing and CDNs where clients dynamically choose the best edge node.
• SaaS platforms needing fine-grained control over where users connect.
• Disaster recovery setups that rely on client failover to alternate regions or availability zones.

There are no formalized industry standards for CS-GSLB, but implementations often use:

• DNS TXT records for metadata distribution
• Custom SDKs or JavaScript logic for selection
• JSON-based configuration formats

Several companies and open-source projects have incorporated client-side load balancing techniques, including:

• DynConD

• Akamai EdgeWorkers
• Cloudflare Workers

• Global Server Load Balancing (GSLB)
• Multicloud architecture
• Edge computing
• Content Delivery Network (CDN)
• GeoDNS

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