针对现代工作负载的速率限制、缓存和请求优先级
Aperture is a distributed load management platform designed for rate limiting, caching, and prioritizing requests in cloud applications. Built upon a foundation of distributed counters, observability, and a global control plane, it provides a comprehensive suite of load management capabilities. These capabilities enhance the reliability and performance of cloud applications, while also optimizing cost and resource utilization.
Integrating Aperture in your application through SDKs is a simple 3-step process:
Define labels: Define labels to identify users, entities, or features within your application. For example, you can define labels to identify individual users, features, or API endpoints.
Example
…
Wrap your workload: Wrap your workload with startFlow and endFlow
calls to establish control points around specific features or code sections
inside your application. For example, you can wrap your API endpoints with
Aperture SDKs to limit the number of requests per user or feature.
Example
…
Configure & monitor policies: Configure policies to control the rate, concurrency, and priority of requests.
Policy YAML
blueprint: rate-limiting/base
uri: github.com/fluxninja/aperture/blueprints@latest
policy:
policy_name: rate_limit
rate_limiter:
bucket_capacity: 60
fill_amount: 60
parameters:
interval: 3600s
limit_by_label_key: user
selectors:
- control_point: your_workload
label_matcher:
match_list:
- key: tier
operator: In
values:
- premium
In addition to language SDKs, Aperture also integrates with existing control points such as API gateways, service meshes, and application middlewares.
[!NOTE]
FluxNinja has been acquired by CodeRabbit. New sign-ups are temporarily disabled. Existing users can continue to use Aperture Cloud by signing in to their accounts.
The easiest way to try Aperture is to sign up for a free Aperture Cloud account. Aperture Cloud is a fully managed service by FluxNinja. With Aperture Cloud, there's no need to manage any infrastructure, and you can integrate your application with Aperture using SDKs. For more information, refer to the get started guide.
Prioritization Metrics for gpt-4
Performance Metrics for OpenAI Models
To try Aperture in a local Kubernetes environment, refer to Playground docs.
Reporting bugs helps us improve Aperture to be more reliable and user-friendly. Include all the required information to reproduce and understand the bug you are reporting. Follow helper questions in the bug report template to make it easier. If you see a way to improve Aperture, use the feature request template to create an issue.
To contribute code, read the Contribution guide.
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