
Mastering Dockerfile USER
Mastering Dockerfile USER: The Key to seamless Kubernetes Deployment
In this article, Jehoszafat Zimnowoda, Engineering Manager @ Red Kubes, explains some of the design decisions his team has made for implementing a zero-trust network architecture for Kubernetes.
Written by Jehoszafat Zimnowoda, Engineering Manager @ Red Kubes
Controlling network traffic plays a key role in today’s distributed and dynamically changing systems, including Kubernetes. Of course, you can live without strict control of your network traffic but it is like driving a car without wearing seatbelts – everything is fine until an accident happens. In this article, I’ll explain some of the design decisions my team has made for implementing a zero-trust network architecture for Kubernetes.
Zero Trust means: Don't trust any network, including your own. Paraphrasing it into the Kubernetes realm: By default, a Pod cannot access any public or private endpoint and a Pod cannot be accessed by a public or private actor.
Lack of “seatbelts” in a Kubernetes cluster may lead to attacks like downloading malicious software into your Container, data leakage, and DDoS attacks inside the cluster. This is why denying any network traffic by default and applying the least privilege principle is crucial.
There are many ways to implement zero trust in Kubernetes, depending on the technologies used. In Otomi, we use Kubernetes Network policies and the Istio Service Mesh as means to control ingress and egress network traffic.
In Otomi, each application in each team namespace is accompanied by two sets of rules: internal ingress filtering and external egress filtering, as shown in the picture below. Each set of rules is composed of trusted endpoints that are either given by Otomi or user-defined. When I say application I mean a group of Pods with the label app:
I would like to emphasize that leveraging Pod labels is crucial when employing network policies in a Kubernetes cluster because they allow targeting a set of Pods that dynamically are spawned and teardown by the Kubernetes scheduler.
Otomi defines a set of trusted platform applications for each Pod in the team namespace. These are:
A user can also define trusted applications that belong to a team or even another team namespace. It is also possible to trust all applications from a given team. Some practical examples are presented in the next section.
Network Policies may be limited by the underlying implementation of the CNI. For example, Calico does not allow to define egress policies for domain names, whereas Cilium does. Since all applications in all team namespaces are automatically deployed with an Istio-proxy sidecar, we decided to tackle external egress filtering by leveraging Istio constructs. First of all, we defined a strict Istio mesh outboundPolicy for each team namespace, then we employ ServiceEntries to define trusted public IP addresses and public domain names. A ServiceEntry can be bound to a namespace or entire service mesh but not to a specific workload. Therefore AuthorizationPolicy rules can be used to make external egress filtering more fine-grained (coming soon in Otomi).
Last but not least, Otomi also allows external egress policies for trusted platform public domains. For example to allow access to public OIDC URL, so applications are able to verify incoming JWT tokens (if needed).
Kubernetes Network Policies and Istio Service Mesh concepts may be difficult to understand for a user that just wants to deploy an app and whitelist trusted endpoints. We decided to let users operate on a high-level concept like Kubernetes services, public domain names, and IP addresses. Otomi translates them into manifests that represent Kubernetes resources.
The next 2 figures show how teams can use the self-service feature in Otomi to configure Ingress and Egress network filtering per service:
All network policies, ServiceEntries and Sidecar configurations are rendered based on configuration parameters stored in Git. This prevents any dangling policies in the cluster and enables you to follow the just-in-time principle. It will also ensure strict network policies for new services registered in Otomi, so only explicit rules enable ingress or egress traffic.
Note that the configuration code in the next snippets is automatically generated when configuring ingress and egress policies using the self-service feature in Otomi. It is also possible to write this configuration manually by cloning the configuration repository and using Otomi CLI to validate and apply changes.
An application disallows internal ingress traffic and external egress traffic:
A service that needs to access https://httpbin.org domain and public IP 116.203.255.68on port 443:
A service that needs to access public TCP endpoint:
If your organization is planning to employ strict network traffic policy enforcement then you need to give development teams time to adapt. Invest in automation of deploying network policies, service entries, and sidecars configuration. Hide technology details from users and let them operate on high-level concepts like trusted public endpoints and trusted cluster applications.
You may wonder about the implementation of particular pieces. For your convenience, I prepared direct links from the otomi-core Github repository.
Internal ingress filtering:
https://github.com/redkubes/otomi-core/blob/master/charts/team-ns/templates/networkpolicy.yaml
External egress filtering:
https://github.com/redkubes/otomi-core/blob/master/charts/team-ns/templates/istio-serviceentry.yaml
https://github.com/redkubes/otomi-core/blob/master/charts/team-ns/templates/istio-sidecar.yaml
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Mastering Dockerfile USER: The Key to seamless Kubernetes Deployment