The Role of Kubernetes Ingress in Container Management – Spiceworks News and Insights

Kubernetes Ingress is defined as a set of routing protocols that details the specifics of how users outside the Kubernetes cluster can access the services running within it. This article explains the fundamentals of Kubernetes ingress, ingress controllers, types of ingress, and the real-world uses of Kubernetes ingress.

Table of Contents

What Is Kubernetes Ingress?

Kubernetes Ingress refers to a set of routing protocols that details the specifics of how users outside the Kubernetes cluster can access the services running within it. This routing typically happens via HTTP/HTTPS protocols.

In Kubernetes, pods refer to the smallest instance of the computing units that operate and run within the cluster, while a load balancer lies outside the cluster. Typically, the load balancer uses internet traffic and guides it to the edge proxy that is active within the cluster. Through the edge proxy, the traffic is directed to respective services and pods depending on the requests. Here, the edge proxy functions as an ingress controller that uses ingress resources in Kubernetes to steer the requests within the cluster.

While Kubernetes Ingress exposes cluster services to the external world, it also helps administrators manage applications better and diagnose routing-related matters, if any. This enhances the cluster security as Kubernetes Ingress considerably reduces the attack surface.

Typical use cases of Kubernetes Ingress include:

  • Offering URLs that are externally reachable to access specific services lying within the cluster.
  • Managing traffic over the web by performing load-balancing tasks.
  • Providing name-based virtual hosting that allows the user to host multiple websites on a single system with one IP.
  • Decrypts encrypted traffic through secure sockets layer (SSL) or transport layer security (TLS) termination.

Key components of Kubernetes Ingress include:

  • Ingress API object: This refers to the cluster services that are exposed to external users via routing rules.
  • Ingress controller: This refers to the real-time implementation of ingress, wherein, the load balancer acts as a controller to navigate traffic from the API source to the target service operational in the Kubernetes cluster.

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What Is an Ingress Controller?

An ingress controller refers to a load balancer that is designed for the seamless management of Kubernetes and other containerized environments. Typically, the ingress controller maneuvers traffic from external sources to services or pods within the Kubernetes cluster by using the transport layer and application layer of the standard OSI model.

The transport layer (OSI – Layer 4) in the OSI model reveals the links between the network layers stacked in the model, wherein, external connections are distributed across the pods in a round-robin fashion. On the other hand, the application layer (OSI – Layer 7) is inclined toward the application end of the OSI stack, wherein, external connections are distributed across the pods based on incoming requests.

Amongst the two, L7 is the preferred choice; however, the ingress controller that fulfills your routing needs and fits the load balancing criteria should be selected, irrespective of the defined norms.

An ingress controller performs the following duties on the Kubernetes platform:

  • Allows the inflow of traffic from outside the Kubernetes environment and distributes (load balances) it onto the pods or containers operational inside the Kubernetes platform.
  • Manages egress traffic that needs to access and interact with services outside a specific cluster.
  • Keeps a check on Kubernetes pods and updates the load balancing rules in real time as and when the pods are added or removed from a service running in the Kubernetes cluster.

Simply put, Kubernetes Ingress may be treated as a computing machine, while the ingress controller may then relate to a developer who uses the computing machine to take the desired action. Continuing the analogy, ingress rules may then serve as the managing head that moderates and guides the developer to carry out the task on the computing machine.

Fundamentally, ingress rules relate to protocols that process the HTTP traffic flowing into a network or cluster. For ingress that lacks rules, all inbound traffic is sent to a default service at the backend.

Technically, an ingress controller refers to an application that uses ingress resources to configure an HTTP load balancer, which may be a software-based balancer such as one running in a cluster, or a hardware or cloud-based balancer that may run external to any cluster. Ingress controllers of various kinds are available in the market. However, choosing the appropriate one based on the load and traffic management strategy for your Kubernetes cluster is crucial.

Moreover, the Kubernetes platform offers support for ingress controllers of different varieties, including AWS, Google Compute Engine (GCE), Kong, Traefik, HAProxy, and Nginx ingress controllers, along with integration features for some third-party ingress controllers. 

More so, ingress controllers are chosen based on the following parameters:

  • Application needs
  • Type of host environment

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Types of Ingress

Ingress in Kubernetes is divided into three types:

1. Single service ingress

Single service ingress refers to the one that is backed by one service and only that service is exposed to external users. To enable single service ingress, you need to define a default backend where all the traffic may be directed in situations when hosts or paths in ingress objects do not meet the ones mentioned in the HTTP message. Hence, the backend without rules needs to be specified while working with a single service ingress.

Ingress example:

apiVersion: networking.k8s.io/v1

kind: Ingress

metadata:

  name: test-ingress

spec:

  defaultBackend:

service:

   name: test

   port:

     number: 80

2. Simple fanout ingress

In simple fanout ingress, the configuration allows the exposure of multiple services by using a single IP address. This facilitates the routing of traffic to the target location based on the request type. The simple fanout type enables easy traffic routing while reducing the total count of load balancers in the cluster.

Ingress example:

apiVersion: networking.k8s.io/v1

kind: Ingress

metadata:

  name: simple-fanout-example

spec:

  rules:

  – host: too.car.com

http:

   paths:

   – path: /too

     pathType: Prefix

     backend:

       service:

         name: service x1

         port:

           number: 4200

   – path: /car

     pathType: Prefix

     backend:

       service:

         name: service x2

         port:

           number: 8080

3. Name-based virtual hosting

Name-based virtual hosting supports directing HTTP traffic from one IP address to various different hosts operating in a cluster. Typically, in this ingress type, traffic is steered toward a specific host before diving into the routing aspects.

Ingress example:

apiVersion: networking.k8s.io/v1

kind: Ingress

metadata:

  name: name-virtual-host-ingress

spec:

  rules:

  – host: too.car.com

http:

   paths:

   – pathType: Prefix

     path: “/”

     backend:

       service:

         name: service x1

         port:

           number: 80

  – host: car.too.com

http:

   paths:

   – pathType: Prefix

     path: “/”

     backend:

       service:

         name: service x2

         port:

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What Is Kubernetes Ingress Used For?

Today, Kubernetes has become an integral part of container management as API objects are deployable and scalable across diverse settings, including on-premise and hybrid and multi-cloud environments. Considering the wide-scale implications of Kubernetes, several organizations are implementing it to automate deployment workflows and expand their networking and security capabilities.

Let’s understand the pockets where Kubernetes Ingress is used as enterprises continue its adoption.

1. DevSecOps strategies to secure containerized environments

Fundamentally, containers refer to software packages that contain all the necessary ingredients essential for them to run in any runtime environment. However, containers face security challenges on various levels. Considering this fact, companies are trying to add more and more security layers into every software lifecycle development (SDLC) stage.

According to a May 2022 report by Red Hat titled ‘2022 State of Kubernetes Security Report’, around 94% of DevOps teams identified that they faced a security incident in their Kubernetes cluster in the last 12 months.

As a consequence, organizations are practicing DevSecOps strategies to enhance security for containerized environments. This is where Kubernetes-based DevSecOps policies come to the fore. With the growing popularity of container-based application deployment, app security has become crucial, thereby shifting the focus onto Kubernetes-based DevSecOps practices that orchestrate containers and automate application deployment processes while ensuring their security.

2. Supports multi-cluster deployments through GitOps

Several modern applications are developed, deployed, maintained, and scaled at high speeds. This includes practices such as app version control, app code review, or even automating app testing & deployment. GitOps facilitates this entire app development process as it automates the infrastructure provisioning process.

GitOps allows multi-cluster and multi-tenant deployments, wherein, several Kubernetes clusters that run in any hybrid environment can be easily managed. This enables continuous application deployment. As a result, Kubernetes, along with GitOps (Google Anthos Config Management, Codefresh, and Weaveworks), is becoming a benchmark for the rapid and fast-paced deployment of parallel applications.

3. Manages container-native environments in the cloud

Cloud migration has become quite essential for most enterprises today. Several organizations are already a part of a hybrid, multi-cloud, public, or private cloud infrastructure setting. More so, in this digital era, companies are increasingly employing containerized environments managed by platforms such as Kubernetes to speed up software deployment and delivery. This further eases the flexibility for cloud migration.

Post-pandemic, as most of the task force continues to work remotely, cloud adoption and wide-scale deployment of containerized environments is likely to witness an upward trend. According to a Feb 2022 report by Gartner, enterprises are expected to spend around $1.3 trillion on cloud migration in 2022.

Thus, as organizations continue their cloud migration strategies, top tech companies such as Google, Microsoft, and Amazon are providing advanced tools where platforms such as Kubernetes are used to simplify the management of container-native environments.

4. Focuses on stateful applications

With increased sophistication in handling containers and microservices, the development of cloud-based applications has become easier than before. However, this has also made the management of stateful applications highly complex.

Stateful applications run in containers operating in varied environments, including edge, public cloud, or hybrid cloud. Moreover, such applications require continuous integration and delivery (CI/CD) to ensure smooth execution, right from the development to the production stage, while maintaining the application state all along.

Thus, Kubernetes is typically used for implementing stateful applications across industries.

5. Better manages AI and ML workloads

Kubernetes is typically used for handling and managing AI and machine learning workloads. As AI and ML algorithms require high processing power, enterprises have tried and tested options such as using public cloud infrastructure or high-performance computing (HPC) systems to better manage their workloads.

However, the most optimal way of handling the workflow is through Kubernetes, wherein, AI and ML programs are packaged in containers and run on Kubernetes clusters. This provides flexibility in AI project management with a pinch of self-service experience for professionals handling the workflows.

Containerized environments enable teams to replicate the tested environment without the need to reconfigure the GPU while running the workload every single time. The most recent version of Kubernetes offers GPU support from AMD and NVIDIA. Moreover, NVIDIA goes further by providing a complete library of containerized ML applications that are packed as containers and are designed to run on NVIDIA GPUs.

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Takeaway

Kubernetes Ingress provides a single platform for the easy routing and management of traffic to applications in a Kubernetes cluster without the need for manual load balancing or service management within the cluster.

Moreover, the development of Kubernetes runs parallel with the evolution of DevOps. A decade earlier, DevOps was compared to the likes of Linux; however, today, it draws commonalities with Kubernetes. Right from DevSecOps to GitOps, Kubernetes plays a critical role in today’s software development process. As such, it is safe enough to say that Kubernetes is here to stay.

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