Observability Stack ROI Assessment

Welcome to the Observability ROI Assessment. This survey asks about your experience with logs, metrics, tracing, and related observability tools over the last 3–6 months. It takes approximately 8–10 minutes to complete. Your participation is entirely voluntary, and you may stop at any time. There are no right or wrong answers—we want your honest opinions. All responses are confidential and will be reported only in aggregate to guide observability investment decisions. Please click Next to begin.

In the last 3 months, have you actively used any observability tools (e.g., logging, metrics dashboards, tracing, APM) as part of your work?

• Yes
• No

Which of the following observability signals or tools do you actively use at least once a month? Select all that apply.

• Logs
• Metrics
• Distributed tracing
• Application Performance Monitoring (APM) dashboards
• Real User Monitoring (RUM)
• Synthetic monitoring
• Error tracking / exception management
• Other (please specify)

Rank your team's current observability objectives from most to least important.

1. Detect and respond to incidents faster
2. Reduce mean time to resolution (MTTR)
3. Improve release confidence and quality
4. Optimize infrastructure costs and capacity
5. Understand end-user experience

How would you rate the overall return on investment (ROI) of your organization's observability stack over the last 6 months?

Rank the following observability signals by the ROI they have delivered for your team over the last 6 months (top = highest ROI).

1. Logs
2. Metrics
3. Distributed tracing
4. APM / dashboards
5. Alerting and on-call tooling

Which of the following outcomes contribute most to observability ROI for you? Select all that apply.

• Fewer production incidents
• Faster triage and root-cause identification
• Better alert quality (fewer false positives)
• Improved developer productivity
• Infrastructure cost savings
• Reduced operational toil
• Fewer customer-facing support tickets
• Improved SLA/SLO attainment
• Other (please specify)

During incident investigations in the past quarter, rank where you spent the most analysis time (top = most time).

1. Searching and filtering logs
2. Querying and interpreting metrics
3. Tracing request paths across services
4. Correlating data across multiple tools
5. Communicating status and findings to stakeholders

In the last 3 months, how often did data gaps or missing context hinder your incident investigations?

What are the most significant friction points you experience with your current observability tooling? Select all that apply.

• High data ingestion or storage costs
• Slow query performance
• Lack of correlation across signals (logs, metrics, traces)
• Inconsistent naming conventions or tag schemas
• Too many low-value alerts
• Insufficient trace coverage
• Difficult onboarding for new team members
• Tool sprawl / too many separate platforms
• Other (please specify)

How confident are you in making operational decisions based on the data your observability tools provide?

Rank where additional investment would most improve observability ROI (top = highest expected impact).

1. Expand distributed tracing coverage
2. Improve log structure, semantics, and search
3. Define or refine SLIs, SLOs, and alert thresholds
4. Unify correlation and navigation across signals
5. Invest in team training, runbooks, and documentation

What are the biggest barriers to realizing ROI from your observability investments? Select all that apply.

• Insufficient tracing coverage
• Unstructured or inconsistent logs
• Siloed tools and data
• Lack of defined SLOs/SLIs
• High data or licensing costs
• Limited team skills or dedicated time
• Unclear ownership or processes
• Competing organizational priorities
• Other (please specify)

What percentage reduction in mean time to resolution (MTTR) over the next 6 months would clearly demonstrate observability ROI to your stakeholders?

• Less than 10%
• 10–20%
• 21–30%
• 31–40%
• 41–50%
• More than 50%
• Not sure

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.

What single change would most improve the return on investment from your observability tools?

Based on your responses in this survey, please share any additional thoughts about observability, tooling, or investment priorities that we should consider.

What is your primary role?

• Site Reliability / DevOps Engineer
• Backend Engineer
• Frontend / Mobile Engineer
• Platform / Infrastructure Engineer
• Data / ML Engineer
• QA / Test Engineer
• Engineering Manager
• Product / Program Manager
• Customer Support / Success
• Other

Which team or area do you primarily support?

• Product / Application team
• Platform / Infrastructure
• Security
• Data / Analytics
• Customer Support / Success
• Other

How many years have you worked in production operations or on-call contexts?

• Less than 1 year
• 1–3 years
• 4–7 years
• 8–12 years
• More than 12 years

How often have you been on call in the last 6 months?

• Never
• Occasionally (less than monthly)
• Monthly
• Weekly or more

Which region are you primarily based in?

• Americas
• EMEA
• APAC

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.