I Reverse-Engineered the Google SRE "NALS" Interview (Here is the Flowchart)

Most candidates preparing for a Google Site Reliability Engineering (SRE) interview make a fatal mistake.

They spend 100 hours grinding LeetCode Mediums. They memorize the "Design Twitter" system design chapter. They walk into the onsite interview feeling prepared.

And then they hit the NALS round.

And they fail.

I’ve spent the last few months deconstructing the Google SRE interview loop to build a comprehensive preparation roadmap. Here is the truth about the NALS round, why it kills so many qualified candidates, and the exact framework you need to pass it.

What is NALS? (It’s Not "System Design")

NALS stands for Non-Abstract Large System Design.

In a standard Software Engineering (SWE) System Design interview, the prompt is usually: "Design Twitter from scratch." You draw boxes, add a load balancer, add a cache, and you pass.

In a Google SRE NALS interview, the prompt is usually:

"We have a photo upload service. It is currently running in production. Users in South America are reporting 500ms latency spikes, but the dashboards look green. Diagnose the issue and redesign the infrastructure to prevent it from happening again."

Do you see the difference?

• Standard Design: Architecture from scratch.
• Google SRE NALS: Diagnosis, Stabilization, and Scaling of an existing, broken system.

They are not testing your ability to draw boxes. They are testing your Operational Maturity.

The "War Room" Mental Model

To pass a Google SRE interview, you cannot think like a builder. You must think like an Incident Commander.

When presented with a NALS scenario, do not jump straight to "Let's add a Redis Cache." That is a feature request. SREs care about reliability.

Use this 4-step diagnostic flow:

1. Clarify & Isolate

Don't assume the problem. Ask questions that narrow the blast radius.

• "Is this affecting all users, or just one region?"
• "Is it a hard failure (500 errors) or a soft failure (latency)?"
• "Did a config push happen recently?"

2. Stabilize (The "Google" Signal)

This is where 90% of candidates fail. They try to find the root cause immediately. A Google SRE’s first job is to stop the bleeding.

• Good Answer: "I'll look at the logs."
• Google SRE Answer: "I will drain traffic from the South American cluster to US-East to restore service for users. Then I will look at the logs."

3. The "5-S" Design Rule

Once the system is stable, you need to re-architect it. I developed the "5-S Rule" to ensure you cover the pillars Google cares about:

• Scope: What exactly are we redesigning? (e.g., "A feature flag service for 10M users").
• Scale: What are the constraints? (e.g., "1M QPS reads, but only 100 QPS writes").
• SLIs (Service Level Indicators): How do we measure success? (e.g., "99.95% availability, <200ms latency").
• Storage: Durability vs. Speed. (e.g., "Spanner for consistency, or Bigtable for throughput?").
• Safety: What happens when it fails? (e.g., "Fail open with stale reads").

4. Observability as a Feature

In a Google interview, "Monitoring" isn't an afterthought. It is a core component. You must define specific metrics (The Four Golden Signals) that would have caught the issue.

The Missing Link: Linux Internals

NALS often bleeds into low-level troubleshooting. If you say "The server is slow," the interviewer will ask "Why?"

You need to be able to go from "High Latency" down to the kernel level:

• Is it CPU Throttling due to CFS quotas?
• Is it Memory Pressure causing excessive paging?
• Is it a File Descriptor exhaustion causing connection drops?

If you can't reason about the Linux kernel, you cannot reason about Google-scale production.

Get the Full Playbook (Open Source)

I realized that while there are thousands of coding guides, there was no single "source of truth" for the specific Operational & Architectural side of the Google SRE interview.

So, I reverse-engineered the entire loop and open-sourced the core frameworks on GitHub.

The Repository covers:

1. The Full NALS Diagnostic Flowchart (Stabilize -> Debug -> Fix).
2. The Linux Internals Cheat Sheet (The 20 commands that solve 80% of incidents).
3. The "Googleisms" Behavioral Framework (How to map your stories to Google’s culture).

It is free to use. If you are prepping for Google, Meta, or any Tier-1 SRE role, this will save you weeks of guessing.

👉 Star the Repository on GitHub Here

(P.S. If you want the complete deep-dive with practice scenarios and mock interview simulations, there is a link to the full course in the README).

Good luck with the loop. Stop guessing, start architecting.