Lakshya

Platform & Developer Experience

Operating track 2nd largest · clearest loop

Site Reliability Engineer

The most standardised interview in this family, which makes it the most preparable.

What the job actually is

You own whether the service is up, measured against a number you agreed in advance. SLOs and error budgets, incident command, capacity planning, and the automation that removes the toil you just discovered. The distinction that matters: SRE serves end users; platform engineering serves internal developers. Teams blur it constantly, so ask who your customer is.

Titles this hides behind

Site Reliability EngineerStaff SRE Production EngineerDatabase Reliability Engineer SRE — Storage Layer ServicesReliability Engineer

The loop

Coding with an operations flavour Log parsing, time-series processing, retry logic. Not abstract algorithms — practical scripting under time pressure.
Non-abstract large system design — the decisive round Google's NALSD format, now widely copied. Design a system at scale with concrete numbers: requests per second, disks, bandwidth, machine counts. Hand-waving fails here in a way it does not in ordinary system design.
Incident simulation A live outage scenario. Interviewers check whether you consult dashboards, page the on-call, and record postmortem actions — process, not just diagnosis.
Linux and troubleshooting depth What actually happens when a process hangs, a disk fills, or DNS goes slow.
Blameless postmortem behavioural Now standard: run a postmortem where the person who caused the outage is in the room.

Prepare like this

  • Practise NALSD with real arithmetic. Take "design a service serving 50k QPS at 99.9%" and produce machine counts, disk throughput and failure-domain layout. Say the numbers out loud; the round rewards estimation fluency.
  • Have an error-budget policy opinion. The hardest rounds centre on what you do when the budget is exhausted and product wants to ship anyway.
  • Rehearse one incident end to end — detection, mitigation, root cause, and the action item that actually got done. Incident-response storytelling now outweighs traditional coding in these loops.
  • Refresh Linux internals. It is 19% of the corpus and close to 100% of the troubleshooting round.

Be ready for

  • "Your error budget is gone in week two of the quarter. Product wants to ship. What happens?" The signature question. There is no clean answer — they want your reasoning and your escalation path.
  • "Latency doubled ten minutes ago. Talk me through what you check, in order."
  • "What is an SLO you have set that turned out to be wrong?" Testing whether you have actually operated one rather than read about them.

Red flags in the posting

SRE that is ops with a pager. If the JD names no engineering time, no error budget and no automation ownership, you are being hired to absorb toil rather than remove it. Ask directly what fraction of time is project work — the Google-derived norm is 50%, and a team that cannot answer has not thought about it.

On-call with no rotation size. Ask how many people are in the rotation. Fewer than six is a burnout signal.

Compensation

United States — base$160k – $270kOn-call compensation varies enormously; ask whether it is paid.
India — total₹25L – ₹60LEstimated. Staff SRE roles in Bengaluru sit at the top of this range.

A day that is actually representative

TimeWhat you are actually doing
08:00Handover, then error-budget check.
10:00Write an SLO with a product owner who wants one that is easy to meet.
13:00Toil removal — automating the thing you did three times last week.
15:00A capacity model for a launch.
16:30Postmortem action item that has been open six weeks.

Real cases worth being able to discuss

Google's SRE practice

The published error-budget model and NALSD interview format have been widely adopted; the error-budget policy is the mechanism that makes reliability a shared decision rather than a veto.

Use it to say: “I use the error budget to turn a reliability argument into a pre-agreed policy, which is the only version that survives release pressure.”

Knight Capital — 2012

A deployment reaching only some servers, combined with a repurposed flag, produced roughly $440m of losses in 45 minutes.

Use it to say: “It is my standard example that deployment consistency and a kill switch are reliability controls, not release conveniences.”

A three-week plan

Week 1 — NALSD

Days 1–5: Five capacity questions, one a day, fifteen minutes each, ending with a machine count and stated assumptions.

Week 2 — operating

Days 1–2: Write an error-budget policy you would defend.

Days 3–5: Rehearse one incident end to end with the four decision points.

Week 3 — depth

Days 1–3: Linux internals and troubleshooting drills.

Days 4–5: The blameless postmortem answer, out loud.

The book for this field

Infrastructure & Reliability

Reliability and error budgets, capacity arithmetic, networks, storage and the restore you have not tested, the physical layer, a debugging method that transfers, running production, and an honest look at Kubernetes. Plus a Middleware section — web and application servers, messaging (IBM MQ, Kafka) and managed file transfer, from basics to licensing and cost.

CHAPTER 1What actually makes a system reliableNot uptime. A shared, written definition of acceptable, and a budget for spending the rest.READ THE CHAPTER →CHAPTER 16AI in observability, honestlyWhat works and why, the benchmark that bounds root-cause claims, and the longitudinal number that went the wrong way.READ THE CHAPTER →CHAPTER 7Running productionChange, incidents and toil. The three things that consume an operations team, and what to do about each.READ THE CHAPTER →

All 33 chapters in Infrastructure & Reliability →

Also read for this role

Networks, Automation, Connectivity & Data Centres

Twelve chapters from a single packet to a submarine cable. Subnetting worked by hand, BGP and why hijacks succeed, DNS and the two outages worth knowing by name, TLS and the expiry that still takes down companies, cloud networking with the arithmetic, transit and peering, colocation and what an AI rack did to the industry, and four debugging scenarios worked end to end.

CHAPTER 12Diagnosing a network problem, with four worked scenariosA ladder that bisects the stack, the eight commands that settle each rung, and four real problems worked end to end.READ THE CHAPTER →CHAPTER 7Load balancing, proxies and the edgeWhere traffic gets shaped, and where a bad health check turns a small problem into a total outage.READ THE CHAPTER →CHAPTER 5DNS, properlyA distributed cache with no invalidation, holding up the entire internet. Two of the largest outages in history were DNS.READ THE CHAPTER →

All 18 chapters in Networks, Automation, Connectivity & Data Centres →

Cross-cutting

Skills every archetype tests

These are shared across every field on this site — the same question asked in different vocabulary — so preparation here compounds rather than being spent once. The book above is specific to your field.

Design under constraintThe decisive round for SRE, AI Platform, Infrastructure — and the reason strong engineers fail it.READ THE CHAPTER →Failure and incident narrativeEvery archetype asks for this story. The outage is the setting; the decisions are the content.READ THE CHAPTER →Measuring what resists measurementTested in every field on this site under a different name — evals, SLOs, DORA, ablations. Named in 59% of AI and 42% of platform postings, and almost nobody studies it deliberately.READ THE CHAPTER →

Practice the 35 Platform questions →  ·  Back to Platform & Developer Experience →