The Problem: Inefficient Scaling in Kubernetes
In today’s cloud-native environments, applications experience fluctuating workloads, requiring efficient scaling mechanisms to optimize resource utilization and cost. Kubernetes provides Horizontal Pod Autoscaler (HPA) as a built-in solution for scaling applications, but it primarily relies on CPU and memory usage as the key metrics. However, real-world applications often require scaling based on external event-driven metrics such as the length of a message queue, database load, or HTTP request rates.
For example, consider an e-commerce platform that experiences significant traffic spikes during seasonal sales. Relying solely on CPU or memory-based scaling might not be sufficient, leading to delays in processing orders or an unnecessary surge in resource allocation, which increases operational costs. This gap necessitates a more intelligent and event-driven scaling mechanism that can dynamically respond to business-critical events beyond just resource utilization.
The Solution: Introducing KEDA
Kubernetes Event-Driven Autoscaling (KEDA) is an open-source project that extends Kubernetes’ native scaling capabilities. KEDA allows applications to scale based on external metrics, enabling event-driven architecture at scale. It supports a wide range of triggers, including message queues (Kafka, RabbitMQ, AWS SQS), databases, cloud services, and HTTP endpoints.
With KEDA, workloads can automatically scale up when an influx of events occurs and scale down to zero when no events are present. This not only improves application responsiveness but also significantly reduces cloud costs by ensuring resources are provisioned only when needed.
Key Features of KEDA:
- Event-driven scaling: Trigger scaling based on external event sources.
- Scale to zero: Efficiently manage workloads by shutting down idle applications.
- Seamless integration with Kubernetes HPA: Extend existing autoscaling capabilities beyond CPU and memory.
- Multi-cloud and on-premises support: Works with various cloud providers and on-prem environments.
- Extensive trigger support: Includes Kafka, Redis, PostgreSQL, AWS SQS, Azure Service Bus, and more.
Real-World Application: How We Helped a Cybersecurity Company Optimize Scaling with KEDA
One of our clients, a leading cybersecurity company specializing in real-time threat detection and response, faced significant challenges in scaling their applications effectively. Their security event processing system heavily relied on RabbitMQ message queues, where logs and threat alerts would accumulate unpredictably. Traditional Kubernetes HPA did not provide an optimal solution, as scaling based on CPU and memory led to inefficient resource utilization, delayed response times, and unnecessary infrastructure costs.
The Challenge
The cybersecurity company struggled with:
- Inconsistent application scaling, causing delays in processing security alerts during peak threat detection times.
- Over-provisioned infrastructure, leading to increased operational costs without proportional performance gains.
- Manual intervention, requiring DevOps teams to constantly adjust scaling policies to keep up with fluctuating queue sizes in RabbitMQ.
The Solution with KEDA
After assessing their architecture, we introduced KEDA to optimize their event-driven workload scaling. By configuring KEDA to scale based on the number of messages in their RabbitMQ queues, the system could now:
- Dynamically adjust pod replicas based on real-time message queue depth.
- Automatically scale down to zero during low-traffic hours, reducing costs.
- Ensure rapid scaling during peak transaction periods, improving customer satisfaction.
The Results
- 40% reduction in cloud costs due to intelligent resource allocation.
- 80% faster response times for transaction processing.
- Improved reliability and resilience with a fully automated and event-driven scaling approach.
Why Choose KEDA?
KEDA is an essential tool for any organization looking to optimize Kubernetes scaling beyond traditional CPU and memory metrics. By leveraging event-driven scaling, businesses can achieve enhanced performance, cost efficiency, and operational simplicity.
If your organization is struggling with unpredictable workloads, inefficient scaling, or high operational costs, KEDA provides a seamless and effective solution. Contact us today to learn how we can help implement KEDA to transform your Kubernetes scaling strategy!
The article was written by Majd Rezik, DevOps engineer at Galil Software