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Developer & Engineering

Developer Latency Sensitivity & SLO Benchmarking Survey

Measures developer-perceived latency thresholds, tail-latency tolerance, and performance trade-off priorities by use case. Use it to benchmark acceptable response times, set data-informed SLOs and SLAs, and prioritize performance investments that align with what developers actually care about.

Sample questions

A preview of what’s in the template. Every question is editable before you launch.

24 questions · ~11 min
Q01
Message

Welcome, and thank you for your interest in this survey on developer latency experiences. This survey takes approximately 11 minutes. Your participation is entirely voluntary, and you may stop at any time. There are no right or wrong answers — we are interested in your honest opinions and real-world experiences from the last 30 days. All responses are confidential, will be anonymized, and reported only in aggregate for internal research purposes.

Q02
Multiple Choice

Have you written, reviewed, or deployed code in a professional capacity in the last 30 days?

  • Yes
  • No
Q03
Multiple Choice

Which of the following languages or platforms did you actively use in the last 30 days? (Select all that apply)

  • JavaScript/Node.js
  • TypeScript
  • Python
  • Java
  • Go
  • Rust
  • .NET/C#
  • Ruby
  • Kotlin
  • Swift
  • C/C++
  • Other (please specify)
Q04
Opinion Scale

Overall, how sensitive to latency are your primary workloads?

Scale: 17
Min:Not at all sensitiveMax:Extremely sensitive
Q05
Dropdown

Over the last 30 days, what p95 latency have you typically observed for your primary endpoint?

  • < 50 ms
  • 50–100 ms
  • 100–250 ms
  • 250–500 ms
  • 500 ms – 1 s
  • 1–2 s
  • 2–5 s
  • > 5 s
  • I don't monitor this metric
Q06
Opinion Scale

If your median latency meets its target, how acceptable are occasional latency spikes?

Scale: 17
Min:Completely unacceptableMax:Completely acceptable
Q07
Ranking

For a latency-sensitive workload, rank the following priorities from most to least important.

  1. Median latency (p50)
  2. Tail latency (p95/p99)
  3. Availability/reliability
  4. Cost efficiency
  5. Throughput
  6. Feature completeness
  7. Developer productivity
Drag to rank
Q08
AI Interview

We'd like to explore your latency trade-off decisions in a bit more depth. An AI moderator will ask you a couple of follow-up questions.

Q09
Multiple Choice

Which of the following best describes your current role?

  • Backend engineer
  • Frontend/web engineer
  • Full-stack engineer
  • Mobile engineer
  • ML/AI engineer
  • SRE/DevOps
  • Data engineer
  • Engineering manager
  • Other (please specify)
Q10
Message

Thank you for completing this survey! Your responses will be used in aggregate to help set better latency benchmarks and improve developer tooling experiences. If you have questions, please contact the research team.

Q11
Multiple Choice

Which of the following use cases are most relevant to your current work? (Select all that apply)

  • User-facing web API
  • Interactive UI actions
  • Search/query
  • Payments/auth/checkout
  • Online ML inference
  • Batch ML/offline scoring
  • Streaming/real-time feeds
  • Data pipelines/ETL
  • Background jobs
  • Build/test/dev tooling
  • Other (please specify)
Q12
Dropdown

For user-facing requests, what do you consider an acceptable median (p50) latency?

  • < 20 ms
  • 20–50 ms
  • 50–100 ms
  • 100–200 ms
  • 200–500 ms
  • 500 ms – 1 s
  • > 1 s
Q13
Dropdown

What is your typical default timeout setting for external API or service calls?

  • < 500 ms
  • 500 ms – 1 s
  • 1–3 s
  • 3–5 s
  • 5–10 s
  • 10–30 s
  • > 30 s
  • No explicit timeout set
Q14
Ranking

When latency threatens your SLA or SLO, rank your top strategies in order of priority (drag to reorder).

  1. Degrade non-critical features
  2. Cache more aggressively
  3. Precompute or batch work
  4. Parallelize or partition requests
  5. Return partial results
  6. Scale up/out resources
  7. Fail fast with retry/backoff
Drag to rank
Q15
Dropdown

In your experience, above what latency do interactive actions start to feel noticeably slow to users?

  • 100 ms
  • 200 ms
  • 300 ms
  • 500 ms
  • 800 ms
  • 1 s
  • > 1 s
Q16
Long Text

Based on your responses in this survey, please share any additional thoughts about acceptable latency, tail behavior, or how latency considerations shape your system designs.

Q17
Dropdown

How many years of professional software development experience do you have?

  • < 1
  • 1–2
  • 3–5
  • 6–9
  • 10–14
  • 15+
Q18
Dropdown

For user-facing requests, what do you consider an acceptable 95th-percentile (p95) latency?

  • < 50 ms
  • 50–100 ms
  • 100–250 ms
  • 250–500 ms
  • 500 ms – 1 s
  • 1–2 s
  • > 2 s
Q19
Dropdown

What is the maximum acceptable end-to-end latency you would set for interactive UI actions (e.g., button clicks, navigation)?

  • < 100 ms
  • 100–200 ms
  • 200–500 ms
  • 500 ms – 1 s
  • 1–2 s
  • > 2 s
Q20
Dropdown

Approximately how large is your organization?

  • 1 (just me)
  • 2–10
  • 11–50
  • 51–200
  • 201–1,000
  • 1,001–5,000
  • > 5,000
Q21
Opinion Scale

How important is reducing tail latency (p95/p99) compared to reducing average latency for your workloads?

Scale: 17
Min:Not at all importantMax:Extremely important
Q22
Dropdown

What is the maximum acceptable end-to-end latency you would set for synchronous API calls (e.g., REST/gRPC)?

  • < 100 ms
  • 100–250 ms
  • 250–500 ms
  • 500 ms – 1 s
  • 1–3 s
  • > 3 s
Q23
Dropdown

In which region are you primarily located?

  • North America
  • Latin America
  • Europe
  • Middle East
  • Africa
  • Asia
  • Oceania
  • Prefer not to say
Q24
Dropdown

What is the maximum acceptable end-to-end latency you would set for batch or background jobs?

  • < 1 s
  • 1–5 s
  • 5–30 s
  • 30 s – 2 min
  • 2–10 min
  • > 10 min

What’s included

  • AI follow-ups

    Adaptive probes on open-ended answers that pull out detail a static form would miss.

  • Attention checks

    Built-in safeguards against rushed answers and low-quality respondents.

  • AI-drafted copy

    Wording, ordering, and branching written by the AI — tuned to your research goal.

  • Auto report

    Themes, quotes, and a plain-English summary write themselves once responses come in.

Why this template

What this template is built to do — we found no directly comparable template from other survey tools to review.

What sets it apart

  • Includes multiple dropdown questions that pin down concrete acceptable p50 and p95 latency thresholds by use case (interactive, synchronous, batch/background), producing data usable for real SLO/SLA setting rather than generic satisfaction scores
  • Uses ranking questions to force explicit trade-off prioritization between latency, cost, reliability, and other engineering priorities when latency threatens an SLA/SLO
  • Includes an adaptive AI follow-up interview segment specifically to probe respondents' latency trade-off decisions in depth after they've answered the structured questions
  • Segments respondents by role, experience, org size, and tech stack so latency tolerance data can be cross-tabbed by professional context, and closes with an open-text reflection question and an auto-generated report

Ready to launch?

Open this template in the editor. Every part is yours to change before the first respondent sees it.

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