Hey folks! 👋
I've been knee-deep in securing our dev team's sprawling infrastructure—we've got clusters running on AWS EKS, GKE over on Google Cloud, and even some experimental stuff on Azure AKS. Managing access and network policies across all of them was becoming a real headache with our old VPN-based approach.
I just rolled out Banyan Security's Zero Trust platform last week to tackle this, and I'm already seeing some interesting results. The promise of unified access for our Kubernetes APIs and internal tools, without opening up the entire network, was exactly what we needed.
Has anyone else here used Banyan specifically for a multi-cloud K8s environment? I'm particularly curious about:
* **Service Account & RBAC Integration:** How smoothly did you tie Banyan's access policies into your existing Kubernetes RBAC? We're syncing OIDC groups, which is working, but I'd love to hear best practices.
* **Performance Overhead:** We haven't noticed any latency hit on `kubectl` commands, but I'm wondering about the impact on high-throughput service-to-service traffic within clusters if we start gating more of that.
* **The "TrustScore" Feature:** We're toying with using device trust posture checks (like requiring a managed laptop) before allowing access to our production namespaces. Any real-world experience with this being too strict for developers?
So far, the shift from a network perimeter model to a device-and-identity-centric one feels right for our cloud-native setup. The admin portal is pretty clean for defining access policies, though I'm still getting my head around all the advanced policy conditions.
Would love to compare notes and hear if it's solved similar problems for you, or if you ran into any tricky pitfalls during deployment!
Beta tester at heart
Interesting timing! We're also juggling EKS and GKE. Your point about tying Banyan's policies into RBAC is exactly where my question is. We're also syncing OIDC groups, but I'm a bit fuzzy on how Banyan's access tags map to specific cluster roles in practice. Did you have to create a bunch of new ClusterRoleBindings, or did the existing ones work?
Your question about mapping Banyan's access tags to cluster roles is the crux of it. The tags don't directly become K8s roles; they act as the *selector* for the subjects in your ClusterRoleBindings. So, you'll likely end up creating new bindings, but they can reuse your existing ClusterRoles.
For example, if you have an access tag like `team:platform-eng`, your binding's `subjects` section would specify a user or group where the `name` is that tag. It looks like this in practice:
```yaml
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:
name: platform-eng-view
roleRef:
apiGroup: rbac.authorization.k8s.io
kind: ClusterRole
name: view
subjects:
- apiGroup: rbac.authorization.k8s.io
kind: User
name: team:platform-eng
```
This is where your OIDC integration comes in, as the authenticated principal's "team" claim must match that tag structure. The main caveat is ensuring your tag naming convention aligns cleanly with your existing RBAC matrix; you might need a few new bindings to cover the tag permutations, but the roles themselves can stay put.
Measure twice, cut once.
Excellent question, and your initial findings about the lack of latency on `kubectl` commands align with my experience. The control plane traffic for command-line interaction is minimal and usually not the bottleneck.
Regarding your specific query on **Performance Overhead for service-to-service traffic**, that's a more complex consideration. The impact depends entirely on your architecture choice. If you're using Banyan's Secure Access Tunnels just for *initial human-to-cluster* access, the intra-cluster Pod-to-Pod traffic remains native and unaffected. However, if you implement their "Zero Trust Everywhere" model and start routing *all* service mesh traffic through their sidecar proxies for intra-cluster segmentation, you will introduce latency. In our tests, this was in the range of 2-8ms additional hop-to-hop latency, which is negligible for most CRUD apps but can become problematic for high-frequency, low-latency trading or real-time inference workloads. The key is to scope the segmentation precisely.
On **the "TrustScore" feature**, we found it most useful as a conditional in access policies for particularly sensitive clusters or namespaces, not as a blanket rule. For instance, you could write a policy that grants `kubectl exec` permissions only if the user's device TrustScore exceeds a certain threshold, while `kubectl get` might be allowed with a lower score. It adds a useful layer of context, but it shouldn't replace core RBAC design.
Yeah, user816's example is spot on. The key is that Banyan's tags become the *subject name* in your RBAC bindings. You're not modifying your existing ClusterRoles, you're just creating new bindings that point to them.
One caveat from our rollout: watch out for tag naming conventions. If your OIDC group is `[email protected]`, but your Banyan access tag is `team:platform-eng`, they won't match unless you normalize them. We had to adjust our OIDC connector's claim mapping to output the tag format directly.
How are you handling tag inheritance for different environments? We found creating a parent tag like `env:prod` and combining it with team tags kept the binding count manageable.
Sleep is for the weak
Totally agree on the importance of normalizing the OIDC claim format - that was a real "aha" moment for us too. We ran into the same issue when our Azure AD groups didn't match the tag structure.
> How are you handling tag inheritance for different environments?
We took a similar approach but added a layer for service-tier access. So we have composite tags like `env:prod,team:data,service:api`. This let us create very specific bindings for, say, just the monitoring service account to talk to the prod API pods, without opening up broader team access. It does mean more bindings, but the granularity has been worth it for audit trails.
Has managing that number of bindings caused any operational slowdown for you, or are you automating the creation?
Data nerd out
The composite tag strategy makes sense, especially for audit trails. We ended up automating the binding creation to handle the scale. A simple GitOps pipeline watches for changes to a central manifest of approved tag combinations and reconciles the ClusterRoleBindings. It prevents drift and turns what could be an ops headache into a declarative process.
The operational cost shifted from managing many bindings to governing the tag combinations themselves. We had to establish a clear schema upfront - deciding which tags are allowed to be combined and who can request new ones. Without that, you risk tag sprawl, which is just as problematic as binding sprawl.
Every dollar counts.
That's a really smart way to manage it. I'm just starting to think about scale, so hearing you automated the binding creation is a huge relief.
How did you decide on the governance for the tag combinations? I'm worried about setting up a process that's too restrictive for developers, but I can already see the risk of sprawl you mentioned. Did you have a central team approving everything, or was it more of a self-service request?
Governance always sounds good on paper until it creates a bottleneck. A central approval team just slows development to a crawl, and self-service often leads to the sprawl you're worried about.
The middle ground that sometimes works is a **veto** model. Developers can create any tag combination they want, but a central security policy automatically flags and blocks combinations that violate core rules - like mixing `env:prod` with a wildcard team tag. This puts the burden on the tooling, not a committee.
But honestly, maybe the sprawl is a symptom. Why do you need so many granular tags? It often points to overly complex RBAC roles that should be simplified at the source, not managed with another layer of tags.
Trust but verify.
Hey, welcome! It's great to see someone else exploring this space. I've been using Banyan for a similar multi-cloud setup for about a year now.
On the RBAC front, you're on the right track with OIDC. The smoothest path we found was to map your IdP groups directly to Banyan's access tags, and then use those tags as subjects in RoleBindings, just like the examples others have given. The integration itself is pretty straightforward once you get the naming aligned.
Your curiosity about the TrustScore is interesting. We've been using it in a limited capacity for conditional access to our staging clusters. It's useful as one signal among many, but I wouldn't base critical production access solely on it yet. The device posture checks are solid, but the behavioral scoring still feels like it's finding its feet. Have you looked at what specific signals you want to weight most heavily?
Let's keep it real.
That's good to know about the TrustScore. We're still setting up our staging environment, so using it there as a signal first makes a lot of sense. The device posture part is what drew me in, especially for contractor access.
> behavioral scoring still feels like it's finding its feet
Yeah, that's my impression too. What kind of behavioral signals are you even looking at for kubectl access? Login time and command frequency seem pretty basic.
We ditched the VPN approach for exactly that reason. It was a mess across three clouds.
On your service account question, we didn't try to directly integrate Banyan with Kubernetes service accounts. We kept them separate. Banyan handles human and external service access (like CI/CD pipelines hitting the API), while in-cluster service-to-service auth stays with the native service accounts and network policies. Trying to unify both under one tool felt like overcomplicating things.
Build once, deploy everywhere
VPNs for K8s access are a disaster, so good riddance there.
But layering Banyan's tags on top of your existing RBAC? You're just adding another abstraction to manage. The complexity doesn't disappear, it just moves. Now you're debugging OIDC claim mappings and tag schemas instead of a straightforward `kubeconfig`.
On performance, if you start routing internal service traffic through it for "zero trust", you *will* see latency. It's another hop. Keep it for human access to the API and leave the service accounts alone.
SQL is enough
I hear your point about added abstraction, and I think you're right if you just slap Banyan's tags on top of a messy RBAC structure. The key is they shouldn't be "on top," they should *replace* a layer.
For us, moving from a forest of individual user bindings to a tag-based schema actually simplified debugging. Instead of tracing which of 50 bindings a user matched, we now trace one OIDC claim -> one access tag -> one role. It consolidated our logic. The upfront cost is designing that tag schema, like others mentioned.
On latency, absolutely agree. We treat it strictly as a control plane guardrail for human and pipeline access. Internal service traffic stays inside the cluster mesh. Routing that through an external gateway defeats the purpose of a low-latency service mesh.
Replacing a layer sounds great until you have to migrate all your existing bindings and hope your tag schema holds up for more than a year. That upfront cost you mentioned? It's a one-way trip.
I've seen teams design a "perfect" schema, only to have a new project or acquisition break all their assumptions six months later. Now you're back to debugging, but with the added joy of figuring out which tag inheritance rule failed.
And yeah, keeping it for the control plane is the only sane move. The second someone suggests using it for east-west traffic, run.
been there, migrated that