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Version: 2.15.1


Aperture is an open source load management platform designed for classifying, prioritizing, scheduling, and rate-limiting API traffic in cloud applications. Built upon a foundation of observability and a global control plane, it offers a comprehensive suite of load management capabilities. These capabilities enhance the reliability and performance of cloud applications while also optimizing resource utilization.

Aperture can seamlessly integrate with existing control points such as gateways, service meshes, and application middlewares. Moreover, it offers SDKs for developers who need to establish control points around specific features or code sections inside applications.

Aperture's control plane is available as a managed service, Aperture Cloud, or can be self-hosted within your infrastructure.

Here's a simplified diagram of how Aperture Cloud (managed by FluxNinja) interacts with your infrastructure. Visit the Architecture page for more details.

Aperture Architecture (dark) Aperture Architecture (light)


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⚙️ Load management capabilities

Aperture provides a variety of advanced load management features:

  • 🛡️ Adaptive Service Protection: Enhance resource utilization and safeguard against abrupt service overloads with an intelligent queue at the entry point of services. This queue dynamically adjusts the rate of requests based on live service health, thereby mitigating potential service disruptions and ensuring optimal performance under all load conditions.
  • 📊 Global Quota Management: Maintain compliance with external API quotas with a global token bucket and smart request queuing. This feature regulates requests aimed at external services, ensuring that the usage remains within prescribed rate limits and avoids penalties or additional costs.
  • 🎯 Workload Prioritization: Safeguard crucial user experience pathways and ensure prioritized access to external APIs even during high-load conditions by strategically prioritizing workloads. This is achieved through the use of declarative policies that label and prioritize workload requests, such as API calls. By employing weighted fair queuing for scheduling, Aperture ensures a fair distribution of resources that aligns with the business value and urgency of requests.
  • 🔀 Load-based Auto Scaling: Eliminate the need for costly over-provisioning and enhance efficiency with Aperture's load-based auto-scaling. Aperture's policies are expressed as circuit graphs that continuously track deviations from service-level objectives and calculate recovery or escalation actions. Auto-scaling can be implemented as an escalation that triggers based on load throttling signal.
  • ⏱️ Distributed Rate-Limiting: Safeguard APIs from potential abuse with Aperture's high-performance, distributed rate limiter. This feature enforces per-key limits based on fine-grained labels, ensuring precise control and prevention of excessive usage.
  • 🚀 Percentage Rollouts: Enable teams to gradually release new features to a subset of users, without impacting the rest of the system. Aperture provides automated load ramping functionality, allowing for a safe and controlled increment of load to new features or API endpoints. This feature continuously monitors for potential performance issues and includes an automatic response mechanism to dial back load in case of a performance regression. This proactive approach minimizes service disruptions and maintains consistent performance, even when rolling out new features.

🛠️ How it works

Load management, at its core, consists of a control loop that observes, analyzes, and actuates workloads to ensure the stability and reliability of cloud-native applications.

This control loop is pivotal in both flow control and auto-scaling use cases. In flow control, the loop manages workloads to maintain the system within its capacity. In auto-scaling scenarios, the control loop adjusts resource allocation in response to demand and performance fluctuations.

During the observation phase, an in-built telemetry system continuously monitors service performance and request attributes, allowing the Agent and Controller to make informed decisions about request handling and workload prioritization.

The analysis and actuation phases use Declarative policies that facilitate teams in defining responses to different situations, such as deviations from service-level objectives.

Aperture Control Loop Aperture Control Loop

✨ Get started

For an in-depth understanding of how Aperture interacts with applications and its various integral components, explore the Architecture section.

📖 Learn

The Concepts section provides detailed insights into essential elements of Aperture's system and policies, offering a comprehensive understanding of their key components.

Additional Support

Don't hesitate to engage with us for any queries or clarifications. Our team is here to assist and ensure that your experience with Aperture is smooth and beneficial.

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