Our phased rollout of NordLayer to our engineering and support teams has concluded, and the operational data is now significant enough to be worth documenting. The primary driver was replacing a patchwork of individual VPN solutions with a unified, centrally-managed Zero Trust Network Access (ZTNA) layer for our cloud resources (AWS, GCP) and internal tooling. The scale was approximately 250 users across three geographic regions.
The initial "big bang" deployment plan failed within the first 48 hours. Our monitoring stack (Prometheus, Grafana, along with detailed AWS VPC Flow Logs) immediately highlighted several critical path issues:
* **Latency Spikes and TCP Connection Resets:** Users in our APAC region connecting to EU-based development clusters experienced a 220-300% increase in application latency, accompanied by persistent `connection reset by peer` errors in their terminals and IDEs.
* **CI/CD Pipeline Failures:** Automated jobs running in GitLab CI, which were configured to use the NordLayer gateway for accessing internal artifact repositories, began failing at a 40% rate. Timeouts were the primary failure mode.
* **Excessive Agent CPU/Memory Consumption:** On a subset of developer macOS machines (M1/M2 MacBooks), the NordLayer agent was consistently utilizing >15% CPU and ~800MB RAM while idle, triggering thermal throttling and battery drain complaints.
### Root Cause Analysis & Remediation
We conducted a week-long deep dive, correlating client logs with our infrastructure metrics. The findings were instructive:
1. **Suboptimal Gateway Selection:** The default "auto" gateway selection was routing APAC traffic through EU servers due to perceived (but incorrect) latency metrics. The fix was to enforce geographic affinity via a custom configuration template pushed through our MDM (Jamf).
```json
// Example of the configuration snippet we deployed
{
"auto_connect": true,
"technology": "openvpn",
"protocol": "tcp",
"gateway_id": "ap_singapore_001" // Explicitly pinned gateway
}
```
2. **MTU/MSS Clamping Issues:** The CI/CD failures were traced to path MTU discovery failures. NordLayer's encrypted tunnel has a smaller MTU, and large TCP packets from our build jobs were being dropped. We resolved this by implementing MSS clamping on our internal load balancers and also adjusting the MTU on the NordLayer client configuration for Linux runners.
```bash
# Applied to our GitLab runner pods
ip link set dev eth0 mtu 1300
```
3. **Agent Resource Leak:** The macOS resource issue was a confirmed bug in a specific agent version related to its telemetry collection loop. NordLayer support provided a pre-release build that addressed the leak. We have since standardized agent versioning and update cycles as part of our desktop base image.
### Current Architecture & Cost Implications
Our stable deployment now uses a hybrid model:
* **Split Tunneling:** Enabled to exclude high-bandwidth, non-sensitive traffic (like video conferencing) from the tunnel, reducing load on the gateways.
* **Dedicated Gateways:** We provisioned dedicated servers in each primary region, moving away from shared infrastructure. This increased cost by ~30% but provided the necessary performance stability and logging isolation.
* **Observability Integration:** We now feed NordLayer's team-specific usage data into our central data warehouse, allowing us to attribute costs and perform capacity planning. The per-user pricing model became predictable only after we implemented automated offboarding scripts to deprovision licenses immediately upon HR system flags.
The transition was materially more complex than anticipated, primarily due to the interaction between the VPN layer and pre-existing network assumptions in our applications. The key takeaway is that deploying a ZTNA solution at scale is less about the client installation and more about the subsequent network performance tuning and integration into your existing observability and identity management frameworks. For teams considering a similar rollout, I would strongly advise a pilot that includes not just human users but also automated systems and a defined set of performance benchmarks against your critical internal endpoints.
Data over dogma
Latency and resets across regions doesn't surprise me. Geo routing with these tools is often naive. Did you check if their APAC traffic was still being hairpinned through a central EU gateway?
Agent CPU is a silent killer. On resource constrained dev machines it becomes a real productivity drain, not just a monitoring stat. What was your baseline comparison, the individual VPNs?
Trust, but audit.
Ah, the obligatory "big bang" deployment failure. I'm shocked, shocked I tell you. What always gets me is the phrase "unified, centrally-managed Zero Trust Network Access layer." That's pure vendor deck language. In reality, you swapped a patchwork of individual VPNs for a patchwork of new problems, just with a single vendor logo on it.
> CI/CD Pipeline Failures... began failing at a 40% rate.
This is the real story, not the user latency. When your automation starts hemorrhaging, that's a direct hit to velocity. A 40% failure rate on timeouts suggests their gateway model for non-interactive traffic is... optimistic at best. Did your team ever run a parallel PoC comparing the old individual VPN throughput to NordLayer's for automated systems, or was the decision based on the promised "unified" management pane?
cg
"Zero Trust Network Access layer." That's a lot of syllables for "yet another VPN."
Your latency and pipeline numbers are brutal, but predictable. The core problem is swapping a decentralized tool (individual VPNs) for a centralized bottleneck. You went from many points of failure to a single, complicated one. Every packet for 250 users now depends on their gateway mesh.
Did you ever consider just fixing the "patchwork of individual VPN solutions"? Standardize on WireGuard with Ansible for config management. Would have taken a fraction of the time, cost, and CPU.
Keep it simple
This is a really tough situation to be in, but thanks for documenting it. That 40% pipeline failure rate must have been a real emergency.
Just curious, did the latency and resets also affect the CI runners themselves, or was it purely an issue with jobs accessing internal resources through the gateway?
Good question, I was wondering the same. The post mentions CI/CD jobs failing when they tried to access internal resources, like artifact repositories. So it sounds like the runners were fine on their own network, but any step needing to connect *through* the ZTNA layer would time out.
That makes me think the real problem was the gateway capacity for automated traffic, not the user connections. Maybe their model is tuned for interactive SSH or web sessions, not a pipeline spawning dozens of parallel connections at once.
Yeah, the CI/CD pain is real. We had a similar but smaller scale issue last year, not with NordLayer but when we tried to route all runner traffic through a new security proxy. The pipelines looked fine until they hit a certain concurrency threshold, then everything would just hang.
The key was distinguishing interactive user traffic from automated batch traffic in the gateway config. For us, it meant setting up dedicated gateway endpoints just for CI systems, with way higher connection and rate limits. Your 40% failure rate screams that the default gateway profile couldn't handle the burst from parallel jobs.
Did you manage to get separate capacity for your CI traffic, or did you have to scale the entire gateway cluster?
You're absolutely zeroing in on the critical distinction. The gateway capacity model for automated traffic is almost always an afterthought in these platforms. They're built and benchmarked for steady-state interactive user sessions: a developer with an SSH connection, a few HTTP tabs open.
The burst from a CI/CD pipeline is a completely different beast. One pipeline trigger can spawn fifty containers simultaneously, each making multiple concurrent TLS handshakes to pull dependencies and push artifacts. That's not a steady stream, it's a tidal wave of connections hitting the gateway's state tables and CPU.
In our case, the 40% failure rate was directly tied to the gateway's maximum concurrent connection limit per instance. The interactive users barely scratched it. The CI system blew past it in seconds, causing new connections to be dropped. The vendor's solution was to just scale the entire gateway cluster horizontally, which is financially and operationally naive. We had to fight for, and finally implement, a dedicated gateway pool with a separate configuration profile tuned for high-connection churn and burst throughput, not latency.
Thanks for getting this documented, and I appreciate the honesty about the big bang failure. That kind of transparency helps everyone.
The 40% pipeline failure rate must have been a major fire drill. It's interesting that the initial monitoring flagged user latency first, but as others have pointed out, the silent killer for business impact is always the automated systems. Once your CI/CD starts hemorrhaging, the entire engineering feedback loop grinds to a halt.
I'm keen to hear what your next steps were after those first 48 hours. Did you engage with NordLayer support on the gateway capacity issue specifically, or was the fix handled internally by scaling and re-architecting?
Keep it constructive.