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Developer & Engineering

OpenTelemetry Adoption & Readiness Assessment

Measures developer familiarity, adoption stage, blockers, and rollout priorities for OpenTelemetry across engineering teams to inform instrumentation strategy and resource planning.

Sample questions

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

20 questions · ~9 min
Q01
Message

Welcome to the OpenTelemetry Adoption & Readiness Survey. This survey takes approximately 6–8 minutes and covers your experience with observability tooling and OpenTelemetry. Your responses are completely anonymous and will be reported only in aggregate to inform tooling and adoption strategy. There are no right or wrong answers — we are interested in your honest experience. Participation is voluntary, and you may stop at any time.

Q02
Multiple Choice

Which best describes your primary role?

  • Backend developer
  • Frontend developer
  • Full-stack developer
  • Site Reliability Engineer / DevOps
  • Data/ML engineer
  • QA/Testing engineer
  • Software architect / Tech lead
  • Platform engineer
  • Other (please specify)
Q03
Multiple Choice

Which observability tools have you used in the last 6 months? (Select all that apply.)

  • Prometheus
  • Grafana
  • Jaeger
  • OpenTelemetry SDK
  • OpenTelemetry Collector
  • Elastic APM
  • Datadog
  • New Relic
  • Splunk Observability
  • AWS X-Ray
  • Azure Monitor
  • Google Cloud Operations Suite
  • None of the above
  • Other (please specify)
Q04
Multiple Choice

Which best describes your organization's current OpenTelemetry adoption stage?

  • Not considering
  • Evaluating
  • Piloting in one or a few services
  • In limited production
  • Broad production across services
Q05
Multiple Choice

What are the biggest blockers to adopting or expanding OpenTelemetry in your organization? (Select up to 5.)

  • Limited time or competing priorities
  • Unclear ROI / benefits
  • Learning curve or lack of expertise
  • Language or framework gaps
  • Lack of organizational buy-in
  • Tooling or integration maturity
  • Data volume or storage cost concerns
  • Performance overhead concerns
  • Security/PII/governance concerns
  • We're satisfied with current vendor tooling
  • No need identified yet
  • Other (please specify)
Q06
Multiple Choice

Which areas are your next targets for OpenTelemetry instrumentation in the next 6 months? (Select all that apply.)

  • Java services
  • Node.js services
  • Python services
  • Go services
  • .NET services
  • Mobile apps (iOS/Android)
  • Browser RUM
  • Databases
  • Message brokers/streaming (e.g., Kafka)
  • Serverless functions
  • Batch/ETL workloads
  • Other (please specify)
Q07
AI Interview

We'd like to understand more about your experience with observability and OpenTelemetry. An AI moderator will ask a few brief follow-up questions based on your earlier responses.

Q08
Multiple Choice

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

  • 0–1
  • 2–4
  • 5–9
  • 10–14
  • 15+
  • Prefer not to say
Q09
Message

Thank you for completing this survey! Your responses are anonymous and will be used in aggregate to identify adoption patterns and prioritize improvements to the OpenTelemetry ecosystem.

Q10
Dropdown

What is your primary programming language for services you work on today?

  • Java
  • JavaScript/TypeScript
  • Python
  • Go
  • C#/.NET
  • C/C++
  • Ruby
  • PHP
  • Rust
  • Other (please specify)
  • Prefer not to say
Q11
Opinion Scale

How familiar are you with OpenTelemetry concepts and components?

Scale: 15
Min:Not at all familiarMax:Extremely familiar
Q12
Dropdown

Approximately what percentage of your production services are currently instrumented with OpenTelemetry?

  • 0%
  • 1–10%
  • 11–25%
  • 26–50%
  • 51–75%
  • 76–99%
  • 100%
  • Not sure
Q13
Multiple Choice

Which of the following support resources would be most helpful for your OpenTelemetry adoption? (Select up to 3.)

  • Official documentation improvements
  • Language-specific getting-started guides
  • Reference architectures and deployment patterns
  • Hands-on workshops or training sessions
  • Internal champions / OTel working group
  • Vendor-neutral migration tooling
  • Community forums or Slack channels
  • Consulting or professional services
  • Other (please specify)
Q14
Opinion Scale

How likely is your team or organization to adopt or expand OpenTelemetry usage in the next 6 months?

Scale: 17
Min:Very unlikelyMax:Very likely
Q15
Long Text

Based on your responses in this survey, if you could change one thing about OpenTelemetry or its ecosystem, what would it be?

Q16
Dropdown

Where are you primarily based?

  • North America
  • Europe
  • Asia-Pacific
  • Latin America
  • Middle East
  • Africa
  • Other (please specify)
  • Prefer not to say
Q17
Multiple Choice

Where do your production workloads run today? (Select all that apply.)

  • Kubernetes
  • Serverless (e.g., AWS Lambda, Azure Functions)
  • Containers without an orchestrator
  • Virtual machines (VMs)
  • Bare metal
  • PaaS (e.g., Heroku, App Engine)
  • On-premises data center
  • Hybrid or multi-cloud
Q18
Multiple Choice

Which OpenTelemetry components or capabilities are you using today, if any? (Select all that apply.)

  • OTel SDKs (language libraries)
  • OTel Collector (any deployment)
  • OTLP export protocol
  • Auto-instrumentation
  • Manual instrumentation
  • Semantic conventions
  • Sampling configuration (e.g., tail-based)
  • Not using OTel yet
Q19
Ranking

Rank the following outcomes by how important they are to your organization's OpenTelemetry goals (most important first).

  1. Faster incident detection and response
  2. Better root-cause analysis
  3. Cross-service traceability
  4. Standardized telemetry across teams
  5. Vendor portability / avoiding lock-in
  6. Cost control and optimization
  7. Improved application performance
  8. Security/compliance visibility
Drag to rank
Q20
Dropdown

Approximately how many employees are in your organization?

  • 1–10
  • 11–50
  • 51–200
  • 201–1,000
  • 1,001–5,000
  • 5,001–10,000
  • 10,001+
  • Prefer not to say

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.

How it compares

We reviewed the closest templates from other survey tools. Here’s what they do well — and where this template goes further.

Why this template

  • Includes a dedicated AI follow-up interview segment that adaptively probes each respondent's actual observability and OpenTelemetry experience, rather than relying only on fixed-choice questions
  • Combines quantitative signals (opinion-scale familiarity and likelihood-to-adopt ratings, dropdown for percentage of services instrumented) with a ranking question to prioritize rollout outcomes and multiple-choice questions on blockers, support needs, and next instrumentation targets
  • Closes with an open-text reflection question asking what respondents would change about OpenTelemetry, capturing qualitative detail a static form would miss
  • Covers the full readiness picture in one flow — role, tech stack, current tools, adoption stage, blockers, and org demographics — feeding directly into instrumentation strategy and resource planning

SurveyMonkey

AI Readiness Assessment Template

This is a fielding-ready template but it assesses general organizational AI readiness, not OpenTelemetry or observability adoption specifically, so it would need substantial rewriting for this use case. It's useful as a structural reference for readiness-assessment question design.

What it does well

  • Established survey platform with broad template library and easy distribution
  • Likely includes standard readiness-assessment scaffolding (maturity stages, barriers) transferable across tech topics

Where it falls short

  • Static questionnaire with no adaptive AI follow-up interviewing to probe individual responses
  • No voice AI interview or guided screen-share task option
  • Not domain-specific to OpenTelemetry/observability tooling, adoption stages, or instrumentation targets

SurveySparrow

Information Security Risk Assessment Questionnaire

A ready-to-field questionnaire aimed at a technical/engineering audience, which makes it a reasonable structural comparison, but it targets security risk assessment rather than observability tooling adoption. Its conversational chat-style format is a known SurveySparrow strength.

What it does well

  • Conversational, chat-like question flow that can feel more engaging than a plain form
  • Ready-to-field questionnaire targeted at technical/engineering respondents

Where it falls short

  • No adaptive AI follow-up interview or automated per-response quality scoring
  • No voice AI interview capability
  • Topic is security risk, not OpenTelemetry adoption stage, blockers, or rollout prioritization

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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