Skip to content

Jay's Cloud Architecture Blog

Designing for scalability, security, and cost-effectiveness: Mastering cloud architecture

Menu
Menu
Queue Based Load Levelling

Queue-Based Load Leveling: Smoothing out the bumps in high-traffic systems

Posted on January 23, 2023February 8, 2023 by Jay Strydom

The Queue-Based Load Leveling pattern is a technique used to manage the load on a system by buffering incoming requests in a queue and processing them as resources become available. This pattern is used to handle bursts of incoming requests that would otherwise overload the system and cause it to fail.

In this pattern, incoming requests are placed in a queue, and a set of worker threads or processes are used to process the requests from the queue. The queue acts as a buffer, allowing the system to handle short-term spikes in incoming requests without overwhelming the system. The worker threads or processes retrieve requests from the queue and process them one at a time.

The Queue-Based Load Leveling pattern has several advantages:

  1. Improved scalability: The pattern allows the system to handle bursts of incoming requests without overwhelming the system and can help to improve scalability by allowing the system to handle variable loads.
  2. Improved reliability: The pattern helps to improve the reliability of a system by queuing incoming requests and processing them as resources become available, which can help to prevent system failures caused by overload.
  3. Improved performance: The pattern can improve performance by allowing the system to process requests in parallel using worker threads or processes, which can help to improve the overall throughput of the system.
  4. Improved manageability: The pattern can improve manageability by allowing system administrators to monitor the size of the queue, which can provide insight into the system’s load and performance.
  5. Improved security: The pattern can improve security by allowing incoming requests to be validated before being added to the queue and also can be used to rate-limit the incoming requests.

It’s important to consider the size of the queue and the rate at which requests are added and removed, in order to ensure that the system can handle the load and that the queue does not grow too large. Additionally, it’s important to consider the type of requests that will be placed in the queue and the resources required to process them, in order to ensure that the system is able to handle the load.

For more information, refer to the Queue-Based Load Leveling pattern on the Microsoft website.

  • Automation (2)
  • Azure (18)
    • Azure App Service (2)
    • Azure B2B (1)
    • Azure B2C (1)
    • Azure Backup (1)
    • Azure Event Grid (1)
    • Azure Firewall (1)
    • Azure Functions (1)
    • Azure Migrate (1)
    • Azure Private Links (1)
    • Azure Service Bus (1)
    • Azure Site Recovery (2)
    • Azure SQL Managed Instance (1)
  • Cloud (17)
  • Cost Optimization (3)
  • Design Patterns (4)
    • CQRS (1)
    • Queue-Based Load Leveling (1)
    • Retry Pattern (1)
    • Throttling (1)
  • Frameworks (4)
    • Azure Landing Zone (1)
    • Azure Well-Architected Framework (1)
    • Cloud Adoption Framework (1)
    • Incident Management (1)
  • Performance (5)
  • Reliability (5)
  • Scalability (1)
  • Security (5)
    • Azure Secure Score (1)
    • MFA (1)
    • Workload Segregation (1)
    • Zero Trust Architecture (1)
  • Web Development (1)
    • SEO (1)
  • Optimize your Azure environment for cost, performance, security, and reliability with Cloudconomist
  • Take website screenshots with Add Screenshots
  • Schedule jobs with Cloudy Scheduler