Benchmarks edge SLO/SLA maturity, failure handling patterns, and release safeguards for DevOps, SRE, and platform engineering teams managing edge workloads.
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Template Overview
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This professionally designed survey template helps you gather valuable insights with intelligent question flow and automated analysis.
Sample Survey Items
Q1
Chat Message
Welcome! This survey explores edge reliability, failure handling, and release practices across teams and organizations.
Please answer based on your current workload(s). There are no right or wrong answers — we are interested in your honest experience.
Participation is voluntary, and you may stop at any time. Your responses are confidential, anonymized, and reported only in aggregate. Results will be used for benchmarking research.
Estimated time: 8–10 minutes.
Q2
Multiple Choice
Do you currently work with, manage, or make technical decisions about edge computing workloads?
Yes
No
Q3
Multiple Choice
Which edge use cases are you currently working on? Select all that apply.
IoT/IIoT telemetry or control
Video analytics or computer vision
AR/VR or real-time interaction
Retail POS or in-store systems
Gaming or real-time multiplayer
AI/ML inference at the edge
Content delivery or CDN workers
Offline-first mobile/web
Autonomous/robotics
Industrial gateways
Other (please specify)
Q4
Dropdown
What is the primary runtime or environment for your edge workload?
Serverless at edge (e.g., CDN workers)
Embedded Linux on device
RTOS / microcontroller
On-prem edge gateway/appliance
Containers on edge (e.g., K8s at edge)
Mobile app (native/hybrid) with edge logic
Browser service worker
Other (please specify)
Q5
Dropdown
What overall availability target do you aim for on your most critical edge paths?
No formal target
< 99% (less than two 9s)
99% (two 9s)
99.5%
99.9% (three 9s)
99.95%
99.99% (four 9s)
99.999%+ (five 9s or higher)
Q6
Multiple Choice
Do you maintain SLIs/SLOs specifically for edge components?
Yes, for most edge components
Yes, for critical paths only
Partially defined
No
Not sure
Q7
Dropdown
What is your typical end-to-end latency target (p95) for critical edge requests?
< 10 ms
10–50 ms
50–100 ms
100–250 ms
250–500 ms
500 ms–1 s
> 1 s
No defined target
Q8
Dropdown
What is your typical acceptable error rate target for edge services?
< 0.01%
0.01–0.1%
0.1–0.5%
0.5–1%
1–5%
> 5%
No defined target
Q9
Dropdown
At approximately what end-user error rate would you typically trigger a rollback for an edge change?
< 0.1%
0.1–0.5%
0.5–1%
1–2%
2–5%
> 5%
No defined rollback threshold
It depends on the service/path
Q10
Multiple Choice
In the past 90 days, which failure modes affected your edge workload? Select all that occurred.
Network partition or high packet loss
DNS or CDN routing issues
Cold starts or warmup delays
Certificate expiry or clock drift
Configuration drift/mismatch
Cache inconsistency or stale data
Device resource exhaustion (CPU/RAM/storage)
Upstream dependency outage
Datastore write conflicts
Inconsistent model versions at edge
Timeout/retry storms
OTA/update failure
None of the above
Q11
Multiple Choice
Which patterns do you use to handle intermittent connectivity? Select all that apply.
Write-behind with background sync
CRDTs or conflict-free merges
Local-first storage with reconciliation
Event sourcing with replay
Queued writes with exponential backoff
Graceful degradation / limited offline mode
Block writes until online
None of the above
Other (please specify)
Q12
Ranking
When a major edge degradation occurs, rank your team's typical response actions in the order you would perform them (first action at top).
Drag to order (top = most important)
Rollback or disable via feature flag
Shift traffic to cloud fallback
Degrade UX gracefully (reduced functionality)
Increase cache TTL / serve stale on error
Apply backpressure / tighter rate limits
Trip circuit breakers to isolate faults
Q13
Multiple Choice
Which signals do you actively monitor for edge reliability? Select all that apply.
Latency percentiles (p50/p95/p99)
Success/error rate
Cold start rate
Cache hit ratio
Sync backlog size or queue depth
Device heartbeat/uptime
Resource usage (CPU/memory/disk)
TLS/cert errors
Offline duration per device/site
Version drift across sites
Custom business KPIs
Other (please specify)
Q14
Opinion Scale
How effective are your current alerts at promptly detecting edge incidents?
Range: 1 – 5
Min: Not at all effectiveMid: NeutralMax: Extremely effective
Q15
Dropdown
How often do you deploy changes to edge components?
On every commit (continuous deployment)
Daily
Weekly
Biweekly
Monthly
Less often
Q16
Multiple Choice
Which of the following pre-release practices do you perform for edge deployments? Select all that apply.
Integration tests against edge environment
Load/performance testing at edge
Chaos/fault injection testing
Connectivity/offline simulation testing
Security/compliance scans
Manual QA or smoke tests
None of the above
Other (please specify)
Q17
Multiple Choice
Which safeguards are part of your edge release process? Select all that apply.
Feature flags
Staged rollouts
Canary by PoP/region/site
Auto-rollback on SLO breach
Policy checks in CI/CD
Two-person review/approval
Signed releases/attestations
SBOM/vulnerability scan gates
None of the above
Other (please specify)
Q18
Ranking
Rank the following areas by where investment would most reduce edge incidents for your team next quarter (most impactful at top).
Drag to order (top = most important)
Observability/monitoring
Pre-release testing at edge
Release safeguards (flags/canary/rollback)
Resilience patterns for offline/intermittent
Capacity and performance tuning
Runbooks/automation and on-call training
Q19
AI Interview
We'd like to explore your edge reliability practices in a bit more depth. An AI moderator will ask you a couple of follow-up questions based on your experience.
AI InterviewLength: 2Personality: [Object Object]Mode: Fast
Reference questions: 8
Q20
Long Text
Based on your responses in this survey, please share any additional thoughts about your edge reliability challenges, priorities, or anything we may have missed.
Max chars
Q21
Dropdown
What is your primary role?
Backend/Platform engineer
Mobile/Web app engineer
SRE/DevOps
Data/ML engineer
Edge/Embedded engineer
Engineering manager/Tech lead
Other (please specify)
Q22
Dropdown
How many years have you worked with edge workloads?
Less than 1 year
1–2 years
3–5 years
6–10 years
More than 10 years
Q23
Dropdown
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+
Q24
Dropdown
What is your organization's primary industry?
Technology
Retail/E-commerce
Manufacturing
Media/Gaming
Telecom
Transportation/Logistics
Healthcare
Finance
Public sector
Other (please specify)
Q25
Multiple Choice
In which regions do you primarily operate edge workloads? Select all that apply.
North America
Europe
APAC
LATAM
Middle East
Africa
Global/multi-region
Q26
Dropdown
Approximately how many active edge sites or devices do you manage?
1–10
11–50
51–200
201–1,000
1,001–10,000
10,001–100,000
100,001+
Q27
Chat Message
Thank you for participating! Your input helps advance understanding of edge reliability practices across the industry. Results will be shared in aggregate form.
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