San Francisco — FluxNinja is thrilled to announce the General Availability of its innovative open source tool, Aperture. This cutting-edge solution is designed to enable prioritized load shedding driven by observability and graceful degradation of non-critical services, effectively preventing total system collapse. Furthermore, Aperture intelligently auto-scales essential resources only when necessary, resulting in significant infrastructure cost savings.

In today's world, the internet is the most widely used technology. Everyone, from individuals to products, seeks to establish a strong online presence. This has led to a significant increase in users accessing various online services, resulting in a surge of traffic to websites and web applications.

Because of this surge in user traffic, companies now prioritize estimating the number of potential users when launching new products or websites, due to capacity constraints which lead to website downtime, for example, after the announcement of ChatGPT 3.5, there was a massive influx of traffic and interest from people all around the world. In such situations, it is essential to have load management in place to avoid possible business loss.

Graceful degradation and managing failures in complex microservices are critical topics in modern application architecture. Failures are inevitable and can cause chaos and disruption. However, prioritized load shedding can help preserve critical user experiences and keep services healthy and responsive. This approach can prevent cascading failures and allow for critical services to remain functional, even when resources are scarce.

To help navigate this complex topic, Tanveer Gill, the CTO of FluxNinja, got the opportunity to present at Chaos Carnival 2023 (March 15-16), which happened virtually, the sessions were pre-recorded. Though, attendees could interact with speakers since they were present all the time during the session.

Service meshes are becoming increasingly popular in cloud-native applications, as they provide a way to manage network traffic between microservices. Istio, one of the most popular service meshes, uses Envoy as its data plane. However, to maintain the stability and reliability of modern web-scale applications, organizations need more advanced load management capabilities. This is where Aperture comes in, offering several features, including:

In today's world of rapidly evolving technology, it is more important than ever for businesses to have systems that are reliable, scalable, and capable of handling increasing levels of traffic and demand. Sometimes, even the most well-designed microservices systems can experience failures or outages. There are several examples in the past where companies like Uber, Amazon, Netflix, and Zalando faced massive traffic surges and outages. In the case of Zalando (Shoes & Fashion Company), the whole cluster went down; one of the attributes was high latency, causing critical payment methods to stop working and impacting both parties, customers, and the company. This outage caused them a monetary loss. Later on, companies started adopting the graceful degradation paradigm.

A robust reliability automation strategy is essential for the successful management of cloud applications. It not only sets top-performing apps apart from the rest, but also establishes trust with end customers and drives business success. Whether you are a small or large organization, investing in reliability management is crucial for ensuring the availability, performance, and consistency of your services.

In this blog, we will introduce you to the fundamental principles of reliability automation, known as the Reliability Spectrum. Consist of three key pillars - prevention, protection, and escalation & recovery - the Reliability Spectrum provides a comprehensive framework for maintaining a reliable cloud application. Join us as we delve into the details of each pillar and explore the essential components of a successful reliability automation strategy.

Rate Limiting is a common requirement for any API service to protect itself from malicious or accidental abuse. Aperture provides a powerful policy engine that can be used to implement rate limiting using the Rate Limiter Component and Flow Classifier.

In this blog post, we will specifically examine how to implement rate limiting for GraphQL queries. Let us begin by discussing what GraphQL is and why rate limiting on GraphQL queries is required.

The FluxNinja team had the opportunity to demo Aperture open source at the November 2022 edition of the Kubernetes Pune meetup, organized at Slack (Salesforce) India’s office.

Kubernetes Pune is a group for all who want to learn and share experiences about Kubernetes. This meetup group is for all skill levels, from beginners to experienced professionals. Every month, we meet and discuss various aspects of the Kubernetes ecosystem, such as service discovery, load balancing, networking, storage, and more.

Highly available and reliable Services are a hallmark of any thriving business in today’s digital economy. As a Service owner, it is important to ensure that your Services stay within SLAs. But when bugs make it into production or user traffic surges unexpectedly, services can slow down under a large volume of requests and fail. If not addressed in time, such failures tend to cascade across your infrastructure, sometimes resulting in a complete outage.

At FluxNinja, we believe that adaptive concurrency limits are the most effective way to ensure services are protected and continue to perform within SLAs.

FluxNinja announces Aperture, bringing reliability to your web-scale apps with flow control​

Today, FluxNinja is emerging from stealth mode to announce Aperture - the first open source flow control and reliability management platform for modern web applications.