Practical Tips for Advanced Use of Kubernetes Gateway API
The Kubernetes Gateway API is a significant evolution in Kubernetes service networking, offering a robust and flexible framework designed to overcome the limitations of its predecessor, the Ingress API. Because of this, Kubernetes teams everywhere are moving from traditional Ingress to the new Kubernetes Gateway API. The Gateway API offers enhanced traffic routing, cross-namespace support, and a role-based architecture that improves collaboration between platform engineers, developers and ops teams.
In this article, I’ll share practical guidelines for organizations adopting and using Kubernetes Gateway API that can help teams go beyond basic routing configurations and discover advanced strategies to maximize the Gateway API’s full potential.
What’s so Special About the Gateway API?
The Gateway API’s role-oriented architecture allows different personas to manage their specific aspects of traffic without stepping on each other’s toes, fostering efficient and secure operations. Furthermore, the API prioritizes portability, ensuring consistent functionality across various implementations and preventing vendor lock-in. With features like extensibility for custom resources, expressiveness for precise traffic routing (e.g., header-based routing and traffic splitting), and native cross-namespace support, the Gateway API empowers organizations to implement complex traffic management strategies.
The API’s capability extends to east-west traffic routing through initiatives like GAMMA, unifying traffic management for service meshes. These foundational strengths provide the perfect groundwork for leveraging the advanced strategies I’ll discuss in the next section of this article.
Making the Most of Kubernetes Gateway API: 4 Practical Tips
Let’s look at 4 tips that will help you make the most of the Kubernetes Gateway API.
- Leverage Custom Gateway Classes for Fine-Grained Control
Organizations can configure custom GatewayClasses to define standardized policies for traffic management across clusters. This allows infrastructure teams to enforce security, rate limiting, and load balancing strategies while enabling developers to configure application-specific routing without worrying about infrastructure details.
Example use case: A custom GatewayClass can specify different types of load balancing (e.g., least connections vs. round-robin) and attach policies like mTLS authentication, connection limits, and retries, ensuring consistency across teams.
For example, this YAML configures a GatewayClass with an internet-facing AWS load balancer:
apiVersion: operator.tigera.io/v1
kind: GatewayAPI
metadata:
name: default
spec:
gatewayClasses:
– name: class-with-aws-load-balancer
gatewayService:
metadata:
annotations:
service.beta.kubernetes.io/aws-load-balancer-scheme: internet-facing
- Use Traffic Mirroring and Traffic Splitting for Safer Deployments
In traditional Kubernetes rollouts, canary deployments require manual Istio or Linkerd configurations. With Gateway API, teams can mirror live production traffic to a new service version while still routing the main traffic flow to the stable version, or use traffic splitting to gradually shift traffic from the stable version to a new release.
Example use case: A company deploying a new version of a checkout service can safely mirror live requests, ensuring proper handling before sending real users to the updated service.
- Route Across Multiple Clusters
Kubernetes is standardizing APIs for federating Services across multiple clusters, and Calico Enterprise has mature support for cluster mesh Service federation. The concept allows targeting Services and backends in remote clusters as easily as those in the local cluster; cross-cluster service discovery allows applications in one cluster to communicate with services in another, enhancing scalability and high availability. The Gateway API natively supports routing to federated Services as well as to local Services-cluster networking, enabling rich cluster mesh routing without additional provisioning.
Example use case: A multi-region microservices architecture can use Gateway API to direct traffic between U.S. and EU clusters for localized latency improvements.
- Monitor and Enforce SLOs with Kubernetes-Native Observability Integrations
One of the biggest challenges in Kubernetes networking is tracking performance degradation before it impacts users. Gateway API plans to integrate Prometheus, Grafana, and OpenTelemetry, allowing teams to monitor request rates, response times, and errors. With automated SLO enforcement, teams will be able to set alerts based on response latency, ensuring that Gateway API dynamically adjusts routing based on real-time conditions.
Example use case: If checkout service latency exceeds 500ms, which exceeds the SLO for this mission critical service, traffic can be rerouted to a backup service.
Embracing the Full Potential of Kubernetes Gateway API
By embracing the Kubernetes Gateway API and implementing these advanced strategies, organizations can unlock unprecedented levels of control, flexibility, and resilience in their Kubernetes networking. From leveraging custom GatewayClasses for consistent policy enforcement and utilizing traffic mirroring for safer deployments, to simplifying multi-cluster routing and integrating native observability for robust SLO enforcement, the Gateway API empowers teams to optimize performance, enhance security, and streamline operations.
As Kubernetes continues to evolve as the de facto standard for container orchestration, mastering these advanced capabilities of the Gateway API will be crucial for building scalable, highly available, and performant applications in modern cloud-native environments.
