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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.

設問の例

テンプレートの内容をプレビューできます。すべての設問は公開前に自由に編集できます。

全24問・約11分
Q01
メッセージ

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
選択式

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

  • Yes
  • No
Q03
選択式

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
オピニオンスケール

Overall, how sensitive to latency are your primary workloads?

スケール: 1 – 7
最小:Not at all sensitive最大:Extremely sensitive
Q05
プルダウン

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
オピニオンスケール

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

スケール: 1 – 7
最小:Completely unacceptable最大:Completely acceptable
Q07
ランク付け

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
ドラッグして順位を付ける
Q08
AIインタビュー

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
選択式

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
メッセージ

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
選択式

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
プルダウン

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
プルダウン

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
ランク付け

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
ドラッグして順位を付ける
Q15
プルダウン

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
自由回答(長文)

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
プルダウン

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

  • < 1
  • 1–2
  • 3–5
  • 6–9
  • 10–14
  • 15+
Q18
プルダウン

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
プルダウン

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
プルダウン

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
オピニオンスケール

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

スケール: 1 – 7
最小:Not at all important最大:Extremely important
Q22
プルダウン

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
プルダウン

In which region are you primarily located?

  • North America
  • Latin America
  • Europe
  • Middle East
  • Africa
  • Asia
  • Oceania
  • Prefer not to say
Q24
プルダウン

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

含まれる機能

  • AIによる深掘り

    自由回答に合わせてAIが追加で質問し、固定のフォームでは拾えない具体的な内容を引き出します。

  • 注意確認設問

    急いだ回答や質の低い回答者を除外する仕組みを標準で備えています。

  • AIが作成する設問文

    文言、設問の順序、条件分岐をAIが調査の目的に合わせて作成します。

  • 自動レポート

    回答が集まると、テーマ、引用、わかりやすい要約が自動で作成されます。

このテンプレートを選ぶ理由

このテンプレートの設計意図をご紹介します。ほかのアンケートツールには、直接比較できるテンプレートが見つかりませんでした。

ここが違う

  • 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

よくあるご質問

「Developer Latency Sensitivity & SLO Benchmarking Survey」テンプレートにはどのような設問が含まれていますか?

すぐに使える設問が24問含まれており、最初の設問は次のとおりです:「Welcome, and thank you for your interest in this survey on developer latency experiences. This survey takes approximatel…」・「Have you written, reviewed, or deployed code in a professional capacity in the last 30 days?」・「Which of the following languages or platforms did you actively use in the last 30 days? (Select all that apply)」。すべての設問は上でプレビューでき、自由に編集できます。

このアンケートの回答にはどのくらい時間がかかりますか?

回答者は通常、24問を約11分で回答し終えます。

テンプレートは編集できますか?

はい。公開前であれば、すべての設問、選択肢、順序を編集できます。設問の追加や削除のほか、調査の目的に合わせた作り直しをAIエディターに依頼することもできます。

このテンプレートは無料で使えますか?

はい。エディターで開けば、すぐに編集を始められます。お試しにアカウントは不要で、無料プランでアンケートを公開できます。

公開の準備はできましたか?

このテンプレートをエディターで開いてみてください。最初の回答者が目にする前に、すべてを自由に変更できます。

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