Home

/

Glossary

/

Infrastructure

/

Load Balancing

Infrastructure

3 min read

What is Load Balancing?

Load balancing is the process of distributing incoming network traffic or workloads across multiple servers or resources to ensure no single server is overwhelmed, improving reliability, performance, and availability.

What is Load Balancing?

Load balancing distributes incoming requests or computational workloads across multiple servers, preventing any single server from becoming a bottleneck. A load balancer sits between clients and servers, routing each request to the most appropriate backend based on configured rules.

Load Balancing Algorithms

Common algorithms determine how traffic is distributed:

  • Round-robin — Requests are distributed sequentially across servers. Simple and effective when servers have equal capacity.
  • Least connections — Routes to the server with the fewest active connections, ideal when request processing times vary.
  • Weighted round-robin — Assigns more traffic to more powerful servers based on configured weights.
  • IP hash — Routes requests from the same client IP to the same server, useful for session persistence.
  • Least response time — Routes to the server with the fastest recent response time.

    • Types of Load Balancers

  • Layer 4 (Transport) — Operates at the TCP/UDP level, routing based on IP and port. Fast but cannot inspect request content.
  • Layer 7 (Application) — Operates at the HTTP level, routing based on URL paths, headers, cookies, or request content. More flexible but adds processing overhead.
  • DNS load balancing — Distributes traffic at the DNS level by returning different IP addresses for the same domain name.
  • Global server load balancing (GSLB) — Routes traffic across geographically distributed data centers based on user proximity.

    • Load Balancing in Automation

    For automation platforms, load balancing ensures that workflow execution requests are distributed across available worker nodes. This prevents any single worker from being overwhelmed during peak usage, maintains consistent execution times, and provides fault tolerance — if one worker fails, the load balancer routes to healthy ones.

    Load balancing distributes work across multiple resources for reliability and scale, a pattern documented by Google Cloud. Autonoly scales execution horizontally so large scheduled execution workloads run smoothly.

    Why It Matters

    Load balancing is essential for any automation platform that needs to handle concurrent workflows reliably. Without it, a surge in workflow executions would overwhelm a single server, causing timeouts, failures, and degraded performance for all users.

    How Autonoly Solves It

    Autonoly's execution infrastructure uses load balancing to distribute workflow executions across multiple containerized workers. When you schedule concurrent automations or multiple users trigger workflows simultaneously, the platform automatically routes each execution to an available worker with sufficient resources.

    Learn more

    Examples

    • An automation platform distributing 100 concurrent web scraping jobs across 10 worker servers using least-connections routing.

    • A reverse proxy (Nginx) distributing API requests across three application servers with health checks that remove unresponsive servers from the pool.

    • A global load balancer routing workflow executions to the nearest data center based on the user's geographic location to minimize latency.

    Frequently Asked Questions

    A reverse proxy sits in front of servers and handles all incoming requests, providing functions like SSL termination, caching, and compression. A load balancer is a specific function that distributes traffic across multiple servers. Many tools (like Nginx and HAProxy) serve as both reverse proxies and load balancers simultaneously.

    Load balancers perform health checks — periodic probes to each backend server. When a server fails to respond, the load balancer marks it as unhealthy and stops routing traffic to it. Once the server recovers and passes health checks again, it is returned to the active pool. This provides automatic fault tolerance.

    You might also like

    Blog Posts
    Use Cases
    ← LatencyLow-Code Automation →

    Related terms, automations and guides

    Where this concept shows up in practice.

    DefinitionLatencyLatency is the time delay between initiating a request and receiving a response, measured in milliseconds. In automation, lower latency means faster workflow execution and more responsive interactions with websites and APIs.DefinitionThroughputThroughput is the amount of work or data processed by a system within a given time period. In automation, it measures how many tasks, requests, or workflow executions a platform can complete per unit of time.DefinitionContainerizationContainerization is a technology that packages an application and all its dependencies into a lightweight, isolated unit called a container, ensuring it runs consistently across any environment without conflicts.DefinitionProxy ServerA proxy server is an intermediary server that routes network requests between a client and a destination server, masking the client's identity and enabling access control, caching, and geographic distribution of traffic.DefinitionRate LimitingRate limiting is a technique that controls the number of requests a client can make to a server within a given time window, preventing abuse and ensuring fair resource distribution.DefinitionCookiesCookies are small data files that websites store in a user's browser to maintain session state, track preferences, and manage authentication across page loads and visits.DefinitionHTTPHTTP (Hypertext Transfer Protocol) is the foundational protocol of the web that defines how clients and servers communicate. Every API call, web page load, and webhook delivery travels over HTTP.GuideWeb Scraping Best Practices: Avoiding Blocks, Bans, and Legal IssuesA comprehensive guide to web scraping best practices. Learn how to avoid IP blocks, bypass CAPTCHAs, handle anti-bot detection systems, respect legal boundaries, and use AI agents to automate compliant data extraction at scale.

    Stop reading about automation.

    Start automating.

    Describe what you need in plain English. Autonoly's AI agent builds and runs the automation for you — no code required.

    See Features