Enhancing Developer Rate Limit Experience in Istio

Enhancing Developer Rate Limit Experience in Istio

Table of Contents

1. Introduction
2. What is Rate Limiting?
3. Benefits of Rate Limiting
4. Challenges in Implementing Rate Limiting
5. The Need for a Red Limit Solution
6. Introducing the Kubernetes Operator Solution
   • 6.1 Overview of the Kubernetes Operator
   • 6.2 Red Limit Service
   • 6.3 Global Red Limit Configuration
   • 6.4 Local Red Limit Configuration
7. Implementing Global Red Limiting
   • 7.1 Creating a Red Limit Service
   • 7.2 Enabling Red Limiting in a Deployment
   • 7.3 Configuring Red Limiting
   • 7.4 Dividing Red Limiting by Domain
8. Demo: Implementing Red Limiting per Route
9. Production Readiness and Future Steps
   • 9.1 Improving Unit Tests
   • 9.2 Deploying to Production
   • 9.3 Integrating with Other Services

Improve Rate Limit Experience for Developers in Steel

Rate limiting is a crucial strategy for controlling the traffic, requests, and resource usage in applications. It allows developers to set limits on how often certain actions can be repeated within a specific time frame. For example, limiting the number of login attempts a user can make in a given period helps prevent brute force attacks and reduces resource consumption.

In the Context of Steel, an infrastructure maintained by GoTo Financial, rate limiting plays a significant role in enhancing the overall developer experience. However, implementing rate limiting in Steel has its challenges. Configuration complexities, the need to Create multiple Envoy filter objects for different Steel versions, and the potential for human errors during upgrades all arise as significant pain points.

To address these challenges, we have developed a Kubernetes operator solution that abstracts the complex configuration of rate limiting and automates the deployment process. This article will explore our solution in Detail, discussing its various components, such as the Red Limit Service, Global Red Limit Configuration, Local Red Limit Configuration, and more.

What is Rate Limiting?

Rate limiting is a strategy or pattern that sets limits on the frequency of actions within a given time period, such as the number of requests or resource usage. It provides several benefits, including:

• Protection against DoS attacks: Rate limiting helps mitigate the impact of distributed denial-of-service (DDoS) attacks by limiting the number of requests an attacker can make.
• Resource consumption control: By setting limits on resource usage, rate limiting ensures fair resource distribution and prevents one user or service from monopolizing available resources.
• Throttling: Throttling allows developers to control the speed at which requests are processed, preventing overload and ensuring the stability of the system.

Challenges in Implementing Rate Limiting

While rate limiting offers significant benefits, implementing it in complex infrastructures like Steel can be challenging. Some challenges include:

• Configuration complexity: Applying rate limiting via Envoy filters requires understanding complex Envoy configurations and can be prone to human errors.
• Version-specific configurations: Upgrading Steel versions necessitates creating multiple Envoy filter objects for each version, leading to potential errors and slowing down the upgrade process.
• Lack of abstraction: Developers need a platform or service that abstracts the complex configuration details of rate limiting, allowing them to focus on their application logic.

The Need for a Red Limit Solution

To address the challenges Mentioned above and simplify the process of implementing rate limiting in Steel, we developed a Kubernetes operator solution. This solution aims to:

1. Abstract the complexity of rate limit configurations, making it easier for developers to understand and create rate limit configurations.
2. Automatically handle the configuration and rollout of rate limit changes across different Steel versions, minimizing human errors and improving the upgrade process.
3. Support both global and local rate limiting in Istio for optimal performance and flexibility.

Introducing the Kubernetes Operator Solution

Our Kubernetes operator solution incorporates several Kubernetes objects that work together to provide an efficient and scalable rate limit setup. Let's take a closer look at these objects:

6.1 Overview of the Kubernetes Operator

The Kubernetes operator acts as the central component of our solution. It carries out the necessary operations to create and manage other Kubernetes objects Based on the specifications provided by the developer.

6.2 Red Limit Service

The Red Limit Service is a Kubernetes service that supports the rate limit interface. It allows developers to configure important parameters such as replicas, resource usage, request backend radius, and stats D.

6.3 Global Red Limit Configuration

The Global Red Limit Configuration enables rate limiting functionality in specific deployments, selected via labels. By specifying the Istio Ingress Gateway in the configuration, developers can control rate limiting on a global level.

6.4 Local Red Limit Configuration

The Local Red Limit Configuration allows developers to specify rate limiting rules for individual services. It works in tandem with the Global Red Limit Configuration and supports division by domain to limit specific domains.

Implementing Global Red Limiting

Enabling global rate limiting in Steel involves several steps. Let's walk through them:

7.1 Creating a Red Limit Service

The first step is to create a Red Limit Service that adheres to the rate limit interface. Developers can configure various parameters, such as replicas, resource usage, and request backend radius, based on the specific requirements of their application.

7.2 Enabling Red Limiting in a Deployment

To enable rate limiting, developers need to include the Global Red Limit Configuration in their deployment. By selecting the appropriate services with labels, developers can control which deployments are subject to rate limiting.

7.3 Configuring Red Limiting

Developers can customize the rate limiting behavior by configuring the Red Limit Service. This includes specifying the service to which rate limiting should be applied, defining the rate limit rules based on methods and paths, and utilizing labels for better metrics.

7.4 Dividing Red Limiting by Domain

The Global Red Limit Configuration supports dividing rate limiting by domain. This ensures that rate limiting applies to specific domains, allowing for granular control over rate limits.

Demo: Implementing Red Limiting per Route

To demonstrate the effectiveness of our solution, we have created a demo showcasing how developers can implement rate limiting per route. By setting a route name in the virtual service, developers can easily Apply rate limiting to individual routes within their service.

In the demo, we simulate a Scenario where one request per hour is allowed. When curling the route multiple times within the hour, the first request succeeds, while subsequent requests receive a 429 HTTP code, indicating they have been rate-limited.

Production Readiness and Future Steps

To make our rate limit service production-ready, there are a few steps we plan to undertake:

9.1 Improving Unit Tests

We aim to enhance the unit tests for our Kubernetes operator and ensure comprehensive test coverage. This will help identify and fix any potential issues before deployment to production.

9.2 Deploying to Production

Currently, We Are only using the Kubernetes operator in our staging environment. Our next step is to deploy it to production, ensuring its stability and reliability under real-world conditions.

9.3 Integrating with Other Services

To further streamline the development process, we plan to integrate our Kubernetes operator with other services within our infrastructure, such as Go Passage and Super App for Engineers. This will enhance the overall developer experience and enable seamless rate limit management.

In conclusion, our Kubernetes operator solution offers a Simplified and automated approach to rate limiting in Steel. By abstracting complex configurations and providing seamless deployment across different versions, it improves the developer experience and ensures optimal resource usage. With its potential for production readiness and future integrations, our solution paves the way for efficient rate limit management in complex infrastructures.