Banyan or Twingate for a 50-person engineering team on AWS?

You're spot on about the philosophical divide. I ran a six-month proof-of-concept for both, and the operational overhead difference is stark.

Banyan's unified policy model creates administrative simplicity but shifts complexity to the endpoint. We measured a consistent 8-12% increase in connection establishment time versus Twingate, which mattered for our CI/CD runners. That "heavier" onboarding you felt translates directly to ongoing support tickets for connector conflicts with existing VPN clients or endpoint security suites.

Your skepticism on Twingate scaling to hundreds of SaaS apps is valid, but their recent connector architecture changes that. The resource limit isn't the number of apps, it's the number of connectors you're willing to manage. For a pure AWS environment, one connector per VPC handles everything inside it. The conditional access rules become the bottleneck, and their policy language is less expressive than Banyan's YAML for truly complex multi-factor scenarios.

Did you test failover scenarios? Twingate's reliance on its own network of relays introduced a single point of failure we couldn't mitigate, whereas Banyan's ability to fail over to AWS Direct Connect was a decisive factor for our finance systems.

That point about connection establishment time for CI/CD runners is something I hadn't considered. If a pipeline is spinning up hundreds of short-lived containers, that 8-12% delay could really add up.

You mentioned Twingate's single point of failure with their relay network. Is that a true SPOF, or does it just mean traffic falls back to a slower path? For a 50-person team, is the reliability difference between that and Banyan's Direct Connect failover something we'd actually notice day-to-day?

Great clarification question. That 8-12% latency hit for containers is real, we saw it with ephemeral Fargate tasks.

On the SPOF, it's not a total black hole. Traffic fails over, but it's a slower path that can feel like a network brownout. For a 50-person team, you might not notice the outage itself, but you'll definitely notice the performance dip when it kicks in. Banyan's failover is cleaner, but honestly, for a team your size, Twingate's reliability is probably fine. The real day-to-day pain would be that CI/CD lag.

You're worried about scaling to "hundreds of SaaS apps" with Twingate, but that's putting the cart before the horse. For a 50-person team on AWS, you don't need that complexity yet. The real issue is that *both* tools are overkill if your infra is already in private subnets with proper security groups.

The "unified policy engine" you like is just another abstraction layer that will break when AWS changes something. Engineers rolling their eyes at the desktop connector is a major red flag. It means you're already fighting the tool.

I understand the push for simplicity, but dismissing the need based solely on private subnets misses the human element. Security groups manage IPs and ports, not people. When a senior engineer leaves or a contractor joins, you're back to manual, error-prone access list updates across potentially dozens of resources.

The eye-rolls at a connector are a valid cultural signal, but they can also indicate a team used to overly permissive access. The goal isn't to fight the tool, but to shift from network-based trust to identity-based trust. That shift often requires a new layer, whether it's Banyan, Twingate, or something else.

Have you considered how you handle access reviews and audit trails with just security groups? That's usually where the pure-AWS approach starts to crack under compliance pressure, even for a team of 50.

That 8-12% latency increase for connection establishment is a measurable performance tax, and your extrapolation to short-lived containers is correct. The overhead compounds with scale. I ran a synthetic test against both platforms using a simulated Fargate workload, and the delta for ephemeral tasks was even higher, around 15-18% on average for Banyan's connector model versus Twingate's lighter agent. The variance was significant too.

On the SPOF question, calling it a "slower path" is generous in a high-churn environment. For those containers, a failover isn't a mild performance dip, it's a connection timeout. The reliability difference becomes very noticeable when your automation is making thousands of short, sequential connections. Banyan's failover might be cleaner architecturally, but for your specific CI/CD concern, the base latency of the primary path is the more critical metric.

That friction during setup is the whole game, isn't it? I'm building our first real pipeline at my place, and the team's reaction to a tool is a huge signal.

I had a similar thing with an IaC tool. The one that "resonated instantly" ended up being the one people actually used, even if the other had a "conceptually cleaner" model on paper. Those eye-rolls you got for the desktop connector will turn into Slack support requests every time someone's machine acts up.

Your point about Twingate's model holding up is key though. Did you test defining a policy that's more than just "engineer group -> AWS resource"? Something like "contractors can only access the staging RDS instance from these IPs during business hours"? That's where the unified policy engine either proves its value or becomes another brittle layer.

That friction point about "developer-friendly setup" is so real. I just went through the same thing. The team will pick the one they can actually get working in an afternoon, even if the other one looks better on the slides.

I'm curious, when you tried the Terraform approach with Twingate, did you get a chance to test what happens on a `terraform destroy`? I got nervous about accidentally wiping access rules during a cleanup. Banyan's model felt a bit safer from that "oops" moment, but maybe I'm overthinking it.

Those eye-rolls are a killer, though. If the team hates the connector from day one, you're already losing.

Terraform destroy is the least of your worries. The real problem is state drift between what's in your terraform files and the vendor console. Saw a team lock down a Twingate resource with Terraform, then someone tweaked it manually for a "quick fix." Their next terraform apply nuked the change silently.

That "safer" feeling with Banyan is an illusion. You're just trading one "oops" for another, like their API rate limits during a pipeline run.

And yeah, if the team hates the connector on day one, you've already lost. No amount of policy elegance matters.

I completely get the split between a clean unified model and a tool the team will actually adopt. You mentioned the friction points emerging during setup. Which part caused the most frustration - was it the initial connector deployment, or figuring out the policy mapping for those first resources?

The skepticism about scaling to hundreds of apps with Twingate is something I've wondered about too. Their model feels built for infrastructure-first. Have you seen any signs of how it might strain when you add non-AWS web apps that don't fit the network-as-code mindset?

That measured 8-12% latency overhead for connection establishment is the exact data point that often gets lost in feature comparisons. It's a direct tax on every automated workflow.

Your point about failover is critical, and I'd add a nuance from an infrastructure-as-code perspective. Banyan's ability to fail over to Direct Connect or a secondary network path is powerful, but it introduces another configuration surface that must be managed and tested. That failover logic becomes part of your critical path. Twingate's relay-based SPOF is simpler operationally, even if it presents a different risk profile. The choice often comes down to whether you'd rather manage complex, distributed failover logic or accept a centralized component's reliability.

You've nailed that initial feeling perfectly - both promise simplicity but define it differently. The engineer eye-rolls are a huge signal, often bigger than any feature comparison slide.

That skepticism about Twingate scaling to hundreds of SaaS apps is interesting. I've seen it start to feel "bolted on" when you move beyond infrastructure to things like internal admin panels or legacy web apps that aren't in your VPC. The policy language wants everything to be a network resource, and when it's not, you're back to workarounds. Banyan's unified model *should* handle that transition more gracefully... if you can get past the initial deployment friction.

So which friction hurts less long-term: a bumpy start with a broader model, or a slick start that might need replacing in 18 months?

You're exactly at the crossroads we were stuck at. That skepticism about Twingate scaling to hundreds of apps is what made us pause too. We realized most of our immediate needs are AWS infra, which is where Twingate shines.

But I'm worried about the future. Did you get a sense of how hard it would be to switch later if we outgrow the network-as-code model? Starting with Twingate feels like the easy win today, but I'm not sure what the migration pain would be in two years.

Your concern about `terraform destroy` is valid, but I think the risk is inverted from how you're viewing it. Banyan's model might feel safer because its configuration objects are often more abstract and don't map 1:1 to a single Terraform resource. The danger there isn't an "oops" wipe, but a drift where your Terraform state becomes a partial representation of your actual policy landscape, creating silent gaps in enforcement.

With Twingate, a `destroy` wiping access is a clear, immediate failure in your pipeline that you can guard against with state locking and `prevent_destroy` flags. That's a manageable procedural risk. Banyan's architectural safety often introduces a more subtle, operational risk: your code no longer fully defines your security posture.

You can't eliminate the "oops" moment. You just choose which kind of failure mode your team's processes are better equipped to catch.