Examining Network Architectures: Kubernetes and Cycle

In a world of managed services, details can often be skipped, overlooked, ignored, or just plain avoided. And in many cases, that's fine. But if you're here, reading this, then I will take it for granted that these things interest you, and I welcome you to join me on this journey of exploration, looking under the hood of two prominent container orchestration platforms on the market: Cycle and Kubernetes.

As we delve deeper, we'll uncover fundamental networking differences, explore how each platform approaches security, and clarify the practical implications for your day-to-day operations. What exactly makes one model simpler or more secure than the other? How does each approach scale, and what might that mean for your organization's future? Stay tuned—answers and insights lie just around the corner.

Comparing Network Fundamentals

Kubernetes Networking

Kubernetes implements a flat, cluster-wide networking model primarily at Layer 3 (network layer). In this model, every pod is assigned a unique IP address and is directly reachable via IP routing from any other pod within the cluster, regardless of the node it resides on. The underlying implementation often relies on the Container Network Interface (CNI), with popular choices including Calico, Cilium, and Flannel. Selecting a CNI has implications for performance, security, and complexity, and it's important to choose one aligned with your specific operational needs.

Namespaces in Kubernetes provide logical groupings for resources such as pods, services, and deployments, mainly for organizational purposes, resource quotas, and access control via RBAC (Role-Based Access Control). However, namespaces do not inherently provide any network isolation; pods in different namespaces can freely communicate unless explicitly restricted.

Network isolation in Kubernetes is commonly achieved through Network Policies, which are rules defined in YAML that specify how groups of pods are allowed to communicate with each other and other network endpoints. These policies operate independently but can be combined with RBAC for administrative access controls. Additional tooling often includes service meshes (such as Istio or Linkerd), which provide advanced features like mutual TLS encryption, detailed observability, and enhanced traffic management.

Cycle Networking

Cycle uses an environment-centric networking model, where each environment is created with an isolated network by default. Unlike Kubernetes, Cycle does not implement a flat network across all worker nodes. Environment to Environment communication requires Software Defined Networks (SDNs), which are natively supported and implemented.

Within an environment, containers can communicate freely with each other. There are mechanics for separating containers into a space that might seem similar to a namespace on Kubernetes. On Cycle we call these spaces deployments. From a high level, deployments allow for many versions of the same sets of containers to live within a single environment (on a single network) without needing to worry about hostname collisions. There are several other benefits, but for the scope of what we're talking about here lets leave it at that.

If a container from a deployment or the global environment scope wants to communicate with any containers in another deployment within the same environment, a special syntax is used. This syntax provides additional information to the discovery service, ensuring precise routing, especially important when multiple deployments in a single environment might contain containers with identical hostnames.

Explicit definitions and permissions control all cross-environment communications, making the network model inherently secure and clear in its boundaries.

Pathways to Secure Networks

Kubernetes: From Open to Restricted

A NetworkPolicy in Kubernetes is applied to a specific set of pods within a namespace. It uses label selectors to identify the target pods and then defines the allowed sources and destinations for traffic. These rules can cover ingress (incoming traffic), egress (outgoing traffic), or both. Without a corresponding deny rule, traffic remains unrestricted—even if a policy is present.

Best practice involves starting with a "default deny" posture: one deny-all policy per namespace for ingress and/or egress. Once this baseline is in place, teams can define allowlist policies that permit only the desired communication patterns between workloads. This whitelist approach limits blast radius and reduces the risk of lateral movement during a compromise.

However, this model introduces fragility. A misconfigured policy—such as forgetting an egress rule for DNS or blocking a required internal service—can lead to runtime failures. In some cases, workloads might become unreachable or break silently, especially if no clear logging or visibility is in place.

For teams building from scratch, a basic progression might look like this:

• Deploy a cluster with a CNI that supports NetworkPolicy (e.g., Calico, Cilium).
• Apply a default deny ingress and egress policy to each namespace.
• Gradually layer in allowlist rules for required pod-to-pod communication.
• Add policies for DNS and egress internet traffic.
• Introduce RBAC and admission controllers to ensure only reviewed policies are deployed.
• Integrate a service mesh if mutual TLS, retries, or traffic shaping is needed.

This setup improves security but introduces technical debt. Every rule becomes a potential failure point. Policies must be versioned, validated, and audited. CI/CD pipelines may need testing gates for policy safety. Documentation and cross-team alignment become essential, especially when multiple services share a namespace or infrastructure is reused across environments.

As clusters grow, the cost of maintaining policy accuracy and visibility increases. Eventually, teams often centralize this work under a dedicated platform team to own network policy hygiene, observability, and rollout strategy.

Cycle: Secure by Default, Composable when Needed

Cycle environments begin with a secure-by-default stance. Even at the container level, containers are set to only communicate over local (no-egress) networks. Egress must be enabled, the same with public network settings.

The default Cycle environment model requires all public traffic come in over the environment load balancer which has configuration settings to be used as a firewall (WAF) if desired. Circumventing the default ingress with tools like Cloudflare Tunnels must be done explicitly.

Environments are not complicated. Creating a new environment from a cluster on Cycle is a simple GUI form or single API call. So segmenting different services into their own environment is somewhat trivial. We do expect users to want to connect environments (or services running within said environments). That can be accomplished through Cycle Networks. These are software defined networks that create a new, completely isolated network that includes all containers in the defined SDN list.

The difference here is that a broadcast ping or DNS lookup from a container with access to both the environment network and an SDN network would not result in uncovering information about containers on the SDN unless a special identifier syntax is used along with the request. A crucial difference.

The result is a network that doesn't assume trust, doesn't flatten scope without permission, and doesn't require multiple layers of tooling just to establish safe defaults. When composability is required—connecting two environments or linking internal services—Cycle's SDNs provide a native, auditable path forward.

Moving Beyond Defaults

Kubernetes: Carefully Measure and Move Slow

After you've locked down basic ingress and egress with NetworkPolicies, the next step is preparing your cluster to support safe, maintainable scale. This requires layering in governance, observability, and change management practices that evolve alongside your infrastructure.

Policy hygiene refers to the validation and consistency of network policy definitions throughout their lifecycle. It typically comes into play during the CI/CD phase—before policies are applied to live clusters. Tools like Gatekeeper (OPA) and Kyverno can enforce structure, required fields, or blocklist conditions during pull requests or policy deployment. But beware, there are vulnerabilities in even the most trusted of Kubernetes addons.

When codifying allowlist standards (e.g., what services can talk to what, and under which ports or protocols), the responsibility usually falls to a platform or security team. These groups define baseline patterns and expectations. Engineers may propose changes via internal RFCs or Git-based review workflows. This process creates a governance checkpoint—but can also introduce bottlenecks, especially when standards are unclear or review queues grow.

DNS and egress testing is a common failure mode in early-stage policy setups. For example, blocking all egress without making an explicit exception for kube-dns will prevent pods from resolving hostnames. This can cause subtle breakages that manifest as timeouts or connection errors. It's recommended to write automated policy validation tests for DNS, NTP, and other base dependencies before rolling out deny-all configurations.

Service meshes (like Istio, Linkerd, or Consul) offer additional capabilities such as mutual TLS, retry logic, traffic shaping, and telemetry. These are not officially maintained by the Kubernetes project—they're independent ecosystems, each with their own setup and lifecycle. Implementing a mesh typically involves deploying sidecar proxies alongside your pods and updating manifests to enable injection. The cost is non-trivial: it adds to the cluster footprint, increases startup time, and often introduces a new layer of operational responsibility.

Visibility tooling like Cilium with Hubble or Calico with Flow Logs helps debug and audit traffic behavior. These tools are generally straightforward to install in clusters already running compatible CNIs but do require compute resources and operational effort to configure correctly. Teams should account for CPU/memory cost from agents, data storage for logs, and time spent tuning observability dashboards. The payoff is often worth it—especially in deny-by-default clusters—but should be planned for explicitly.

As the networking footprint grows, it helps to treat secure networking as a shared product within the organization. This means investing in platform teams who can write, maintain, and evolve the network policies and surrounding tooling in step with application delivery cycles.

Cycle: Focused Scope, Predictable Interfaces

Cycle's networking model is narrower by design. It eliminates the need for many of the layers Kubernetes requires by embedding opinionated behavior directly into the platform. Environment networks are isolated. Users can compose SDNs that include multiple environments. DNS is network-aware. These defaults reduce the number of components needed to achieve a secure, functioning network.

This simplification doesn't mean Cycle environments never require attention—but it changes what kind of attention they require. Instead of maintaining policy engines or custom controllers, teams focus on intentional environment design, clear SDN boundaries, and explicit service relationships.

Because of Cycle's predictable routing and discovery mechanisms, failures tend to be easier to trace. If a container can't reach another, the failure is more often tied to a missing SDN relationship or a discovery syntax issue—not an ambiguous combination of CRDs, YAML files, and layered policies.

As a result, the operational complexity of Cycle tends to scale linearly with the number of services—not exponentially with the number of network policies, controllers, and observability systems.

Choosing a Model That Matches Your Org

Kubernetes and Cycle represent fundamentally different approaches to networking—and choosing between them often comes down to matching the platform to your team's structure, risk tolerance, and need for flexibility.

Feature	Kubernetes	Cycle
Default network behavior	Flat, open cluster network	Environment-isolated networks
Cross-scope communication	Allowed unless blocked via policy	Only allowed if explicitly defined (e.g., SDNs)
DNS behavior	Global by default	Scoped per environment or SDN
Security defaults	Open unless configured	Secure unless explicitly opened
Tooling requirements	CNI, NetworkPolicy, RBAC, Service Mesh, Gatekeeper, etc.	Native environment and SDN constructs
Operational risk	High—requires layered controls and strong governance	Lower—intention-first and bounded by default
Complexity scaling	Grows with services, namespaces, policies, and tooling	Grows with number of environments and SDN links
Best suited for	Ultra low level control and flexibility	Secure-by-default, simplified operational environments

Kubernetes provides powerful flexibility. That flexibility carries overhead: careful policy coordination, cross-team governance, and layered observability.

Cycle, by contrast, bakes opinionated defaults into the platform, limiting complexity and minimizing misconfiguration risk. It favors a deliberate, service-by-service architecture where connectivity is granted intentionally—not assumed.

There is no single right answer—but the fewer assumptions your platform makes, the more effort you'll need to put into securing and maintaining it. Choosing a model that aligns with your team's strengths will determine how sustainable and secure your networking architecture will be over time.

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