SRE Study Guide 2026

Everything you need to pass the SRE exam in one place: the exam format, every topic to study, real practice questions with explanations, flashcards, and full-length practice tests. Free, no sign-up needed.

📋 SRE Exam Format at a Glance

40
Questions
60 min
Time Limit
65%
Passing Score

📚 SRE Topics to Study (43)

✍️ Sample SRE Questions & Answers

1. In a service mesh, what is 'traffic mirroring' (shadow traffic), and how is it used to improve reliability?
Traffic mirroring sends a copy of live production requests to a shadow service version, allowing testing of new versions with real traffic patterns without affecting production users

Traffic mirroring (also called shadow deployments or dark launches) sends an asynchronous copy of production traffic to a shadow instance, allowing performance testing and behavior validation under real load without any risk to production users.

2. What is 'throughput' vs. 'latency' in performance testing, and what is their typical trade-off relationship?
Throughput is the number of requests processed per second; latency is the time to process a single request. At low load, both can be optimized simultaneously, but at high load, higher throughput often comes with increased latency as queuing occurs

At low utilization, adding more requests doesn't significantly increase individual request latency. As utilization approaches capacity, queueing theory (Little's Law) predicts latency increases sharply — this is the hockey-stick latency curve observed in most systems.

3. What is 'synthetic monitoring' and how does it complement real user monitoring (RUM)?
Synthetic monitoring runs scripted probe transactions against the production service continuously; combined with RUM (which captures real user experience), it provides complete observability: synthetics detect issues when real user traffic is absent, RUM captures the actual diversity of user experiences

Synthetic monitoring provides 24/7 baseline measurements and immediate alerts even at zero user traffic. RUM captures the true diversity of user environments, devices, and geographies that synthetics cannot replicate — together they cover different monitoring blind spots.

4. What is 'horizontal vs. vertical scaling,' and when is each approach MOST appropriate?
Horizontal scaling adds more instances of a service; vertical scaling increases the resources (CPU, memory) of existing instances. Horizontal scaling is preferred for stateless services and enables near-infinite capacity; vertical scaling is simpler but has hardware limits and causes downtime during upgrades

Horizontal scaling (scale out) adds instances and distributes load — works well for stateless services but requires load balancing and may introduce distributed system complexity. Vertical scaling (scale up) is simpler but hits hardware ceilings and typically requires a restart.

5. A team defines a latency SLI as 'the proportion of homepage requests served in under 200 ms.' Which SLO statement is BEST aligned with this SLI?
99% of homepage requests will be served in under 200 ms over a rolling 28-day window

An SLO must reference the same SLI metric and unit. The SLI is the proportion of requests under 200 ms, so the SLO should set a target percentage for that same proportion over a defined time window.

6. What is 'data sovereignty' in the context of disaster recovery, and how does it constrain DR architecture for regulated industries?
Data sovereignty laws require that certain data remain within specific geographic jurisdictions; DR backups and replicas must be stored in compliant locations, potentially preventing the use of the geographically distant DR sites that would otherwise provide the best resilience

Laws like GDPR (EU), data localization laws (Russia, China, India), and industry regulations (healthcare, finance) restrict where certain data can be stored — this can force DR to use in-country or in-region backup sites rather than the most geographically distant, resilient locations.

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