Benchmark edge SLO/SLA, failure handling, release practices. Built for DevOps, SRE, and platform teams. 8–12 min to launch and collect actionable insights.
What's Included
AI-Powered Questions
Intelligent follow-up questions based on responses
Automated Analysis
Real-time sentiment and insight detection
Smart Distribution
Target the right audience automatically
Detailed Reports
Comprehensive insights and recommendations
Sample Survey Items
Q1
Chat Message
Welcome! This survey focuses on edge reliability, failure handling, and release practices. Please answer based on your current workload(s). Your responses are confidential and reported in aggregate.
Q2
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
Q3
Dropdown
What is the primary runtime/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
Q4
Opinion Scale
What overall availability target do you aim for on critical edge paths?
Range: 1 – 10
Min: No formal targetMid: Target definedMax: Very high (e.g., 99.99%+)
Q5
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
Q6
Matrix
What targets are typical for your edge services?
Rows
< 1 minute
1–5 minutes
5–30 minutes
30–120 minutes
> 120 minutes
Not defined
RTO target (time to restore service)
•
•
•
•
•
•
RPO target (acceptable data loss)
•
•
•
•
•
•
Q7
Numeric
At what end-user error rate (%) do you typically trigger a rollback for edge changes?
Accepts a numeric value
Whole numbers only
Q8
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
Q9
Multiple Choice
Which patterns do you use under 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
Q10
Ranking
Rank your first responses to a major edge degradation (top = most likely first action).
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
Q11
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
Q12
Rating
How effective are your alerts at promptly detecting edge incidents?
Scale: 10 (star)
Min: IneffectiveMax: Highly effective
Q13
Dropdown
Attention check: To confirm you’re reading the questions, please select “I am paying attention.”
I am paying attention
I am not paying attention
Q14
Matrix
Before releases, how often do you run the following for edge?
Rows
Never
Rarely
Sometimes
Often
Always
Integration tests with device emulators
•
•
•
•
•
Chaos tests (network latency/packet loss)
•
•
•
•
•
Canary by region/site/PoP
•
•
•
•
•
Load tests from edge locations
•
•
•
•
•
Failure injection for offline flows
•
•
•
•
•
Manual exploratory testing
•
•
•
•
•
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 safeguards are in your 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/vuln scan gates
Q17
Constant Sum
Allocate 100 points across the areas below where investment would most reduce edge incidents next quarter (total must equal 100).
Total must equal 100
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
Min per option: 0Whole numbers only
Q18
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
Q19
Numeric
How many years have you worked with edge workloads?
Accepts a numeric value
Whole numbers only
Q20
Dropdown
Organization size (employees)
1–10
11–50
51–200
201–1,000
1,001–5,000
5,001–10,000
10,001+
Q21
Dropdown
Primary industry
Technology
Retail/E-commerce
Manufacturing
Media/Gaming
Telecom
Transportation/Logistics
Healthcare
Finance
Public sector
Other
Q22
Multiple Choice
Where do you primarily operate edge workloads? Select all that apply.
North America
Europe
APAC
LATAM
Middle East
Africa
Global/multi-region
Q23
Numeric
Approximately how many active edge sites/devices do you manage?
Accepts a numeric value
Whole numbers only
Q24
Long Text
Anything else we should know about your edge reliability context or priorities?
Max 600 chars
Q25
AI Interview
AI Interview: 2 Follow-up Questions on your edge reliability practices
AI InterviewLength: 2Personality: Expert InterviewerMode: Fast
Reference questions: 22
Q26
Chat Message
Thank you for participating! Your input helps us improve understanding of edge reliability needs.
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