Solved: Spending €1.1M/month on Google Ads… and support can’t resolve even basic issues

#devops #programming #tutorial #cloud

🚀 Executive Summary

TL;DR: High-spending cloud customers frequently encounter inadequate support from providers like Google, leading to significant outages and financial losses. The core solution involves architecting systems for resilience through automated multi-region/multi-cloud failover, proactive engagement with Technical Account Managers, and robust observability to minimize dependency on provider support.

🎯 Key Takeaways

Implement a “No Single Point of Support” architecture using automated multi-region or multi-cloud failover with a global load balancer independent of any single provider (e.g., Cloudflare, Akamai).
Proactively engage your Technical Account Manager (TAM) for strategic architectural reviews and to leverage their internal network and social capital, rather than using them solely for reactive escalations.
Invest heavily in your observability stack (Prometheus, Grafana, OpenTelemetry) to generate undeniable data that precisely identifies provider-side issues, forcing direct escalation past Tier 1 support.

Spending €1.1M/month on Google Ads… and support can’t resolve even basic issues

When you’re a massive cloud spender but can’t get competent support for basic issues, it’s a systemic failure, not a personal one. The key isn’t to yell louder at support; it’s to architect your systems for resilience against the provider’s own bureaucracy.

I Felt That Reddit Post In My Bones

It was 3 AM. The on-call phone blared to life, and I rolled out of bed to see our primary Postgres cluster, pg-prod-us-east-1-a, in a connection-storm panic. We were a top-tier customer, spending six figures a month with our cloud provider, and our “Premium Enterprise Support” contract was supposed to be our silver bullet. An hour into the P1 outage, all we had was a ticket number and a junior agent on the other end of the line asking if we’d tried restarting the instance. We were burning thousands of dollars a minute, and our lifeline was a human-shaped knowledge base article. So when I saw that Reddit thread about a company spending over a million a month and getting the same runaround, I didn’t just sympathize. I had flashbacks.

That feeling of total helplessness, where your entire business is at the mercy of a support queue you have no control over, is something no engineer should have to experience. But we all do.

The truth is, your million-dollar bill doesn’t buy you a magic wand. It just gets you a slightly better seat in the same broken theater. Let’s talk about why this happens and how we, as engineers, can build systems that make their support queue irrelevant.

Why Your Spend is Just a Number on Their Spreadsheet

It’s simple, brutal math. To a cloud giant like Google, AWS, or Azure, even €1.1M a month is a rounding error. Their support model is built for mass-scale ticket deflection, not nuanced problem-solving. It’s a funnel designed to keep their expensive, high-level engineers away from the noise.

Tier 1 Triage: The first person you talk to is following a script. Their job is to link you to a doc and close the ticket.
The “Prove It’s Us” Game: The default assumption is that the problem is your code, your configuration, or your fault. The burden of proof is on you, even when their infrastructure is clearly misbehaving.
Firewalled Experts: The actual SREs and network engineers who can fix the problem are protected by layers of process. You only get access to them if your issue is causing a region-wide outage or you’re a named account like Netflix.

You can’t fix their business model. But you can architect your way around it. Stop trying to get better support; start building systems that don’t need it.

Stop Waiting for a Hero: 3 Ways to Architect for Resilience

If you’re waiting for a support agent to save you during an outage, you’ve already lost. The goal is to design systems where their internal failures become a non-event for you. Here are three strategies we’ve implemented at TechResolve.

1. The “No Single Point of Support” Architecture

We all know about avoiding a single point of failure in our infrastructure. It’s time to apply that same logic to our support vendors. If your entire operation grinds to a halt because Google Cloud Networking in us-central1 is having a bad day and their support is useless, that’s a design flaw.

The Fix: Implement a robust, automated multi-region or even multi-cloud failover strategy. Use a global load balancer (like Cloudflare, Akamai, or AWS Route 53) that isn’t tied to a single provider. If your GKE clusters in GCP start acting up and support is giving you the runaround, a single API call or a health check failure should automatically shift 100% of your traffic to your EKS failover environment in AWS us-east-2.


Old Way (High Risk)	Resilient Way (Low Risk)
Single Region GKE deployment.	Active-passive GKE and EKS deployments.
DNS points directly to GCP Load Balancer.	Cloudflare Global Load Balancing points to both clouds.
Outage Plan: Frantically file a P1 ticket with Google support and wait.	Outage Plan: Automated health checks detect GKE latency and fail traffic over to EKS in under 5 minutes. Open a low-priority ticket with Google later.

This isn’t just for disasters. It’s leverage. The ability to completely move off a provider’s troublesome region is more powerful than any support ticket you can write.

2. Your TAM Is Your Bat-Signal (If You Use It Right)

Your Technical Account Manager (TAM) is not an escalation monkey. If you only call them when things are on fire, you’re using them wrong. The support portal is for break-fix; your TAM is your strategic advocate inside the machine.

The Fix: Build a real relationship. Schedule regular architectural reviews. Before a major launch, bring your TAM into the planning phase. Walk them through your concerns. When we were preparing to launch a new service on Spanner, we had three sessions with our Google TAM and a Spanner specialist they brought in. We war-gamed failure scenarios. When a minor latency issue did crop up, our TAM didn’t need to be “brought up to speed”—he already had the context, knew which internal team to ping directly, and bypassed the entire Tier 1 circus for us. Your TAM’s real value is their internal org chart and the social capital they have with the engineering teams. Use it proactively.

3. Prove Them Wrong With Your Own Data

Support’s first line of defense is ambiguity. “We see no issues on our end.” Your job is to eliminate that ambiguity with overwhelming, undeniable data. Don’t give them an escape route.

The Fix: Invest heavily in your observability stack (Prometheus, Grafana, OpenTelemetry, etc.). Your goal is to pinpoint a problem so precisely that it can only have one root cause: them. Don’t open a ticket saying “Our app is slow.”

Open a ticket saying this:

## GKE Egress Latency Anomaly in us-central1-c

Description:
We are observing a sustained 150ms increase in TCP connection handshake time for all egress traffic from our GKE cluster `gke-prod-main-app` in zone `us-central1-c`.

- Start Time: 14:32 UTC
- End Time: Ongoing
- Source: Any pod on GKE nodes with kernel version 5.4.0-1045-gke
- Destination: Any external IP address (tested against 8.8.8.8 and 1.1.1.1)

This issue is NOT present in our identical cluster in `us-central1-b`.

Attached:
1. MTR trace from an affected pod vs. a healthy pod.
2. Grafana dashboard URL showing the exact moment the latency deviation began across all nodes in the zone.
3. Packet capture showing TCP SYN retransmissions.

Please escalate to the regional networking team responsible for the `us-central1-c` data plane. This is not a configuration issue on our end.

When you present a case this airtight, you give the Tier 1 agent no choice but to hit the “escalate” button. You’ve done their job for them. This is how you skip the line.