Q01
Long Text
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Observability Stack ROI Assessment
Measures perceived return on investment from logs, metrics, tracing, and monitoring tools across DevOps and SRE teams, identifying high-impact areas for investment and key barriers to value realization.
Sample questions
A preview of what’s in the template. Every question is editable before you launch.
23 questions · ~4 min
Q02
Multiple Choice
In the last 3 months, have you actively used any observability tools (e.g., logging, metrics dashboards, tracing, APM) as part of your work?
Q03
Multiple Choice
Which of the following observability signals or tools do you actively use at least once a month? Select all that apply.
Q04
Long Text
How would you rate the overall return on investment (ROI) of your organization's observability stack over the last 6 months?
Q05
Long Text
During incident investigations in the past quarter, rank where you spent the most analysis time (top = most time).
Q06
Long Text
How confident are you in making operational decisions based on the data your observability tools provide?
Q07
Multiple Choice
What are the biggest barriers to realizing ROI from your observability investments? Select all that apply.
Q08
AI Interview
Describe one recent case (within the last 6 months) where logs, metrics, or tracing clearly helped—or failed—to deliver value during an incident or investigation.
Q09
Long Text
What is your primary role?
Q10
Long Text
Thank you for completing the Observability ROI Assessment! Your responses are confidential and will be analyzed in aggregate. Results will directly inform upcoming investment and tooling decisions. If you have any questions, please contact your platform team lead.
Q11
Long Text
Rank your team's current observability objectives from most to least important.
Q12
Long Text
Rank the following observability signals by the ROI they have delivered for your team over the last 6 months (top = highest ROI).
Q13
Long Text
In the last 3 months, how often did data gaps or missing context hinder your incident investigations?
Q14
Long Text
Rank where additional investment would most improve observability ROI (top = highest expected impact).
Q15
Long Text
What percentage reduction in mean time to resolution (MTTR) over the next 6 months would clearly demonstrate observability ROI to your stakeholders?
Q16
Long Text
What single change would most improve the return on investment from your observability tools?
Q17
Long Text
Which team or area do you primarily support?
Q18
Multiple Choice
Which of the following outcomes contribute most to observability ROI for you? Select all that apply.
Q19
Multiple Choice
What are the most significant friction points you experience with your current observability tooling? Select all that apply.
Q20
Long Text
Based on your responses in this survey, please share any additional thoughts about observability, tooling, or investment priorities that we should consider.
Q21
Long Text
How many years have you worked in production operations or on-call contexts?
Q22
Multiple Choice
How often have you been on call in the last 6 months?
Q23
Long Text
Which region are you primarily based in?
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.
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Open this template in the editor. Every part is yours to change before the first respondent sees it.