StackScopes
01 · Digital Twin
A living map of the cloud.
Connect resources, identities, applications, ownership, and time in one reviewable system.
Explore the digital twin →
Cloud Infrastructure Intelligence
See What Breaks
See What Breaks
Before It Breaks.
Create a living digital twin of your cloud infrastructure.
Live Infrastructure Map
Internet
Edge Gateway
DNS
Load Balancer
WAF
Web Tier
App Tier
Cache
Database
Object Storage
Simulation Timeline
▶
Read-only discoverySeparate collection and execution roles
Evidence on every pathSource, timestamp, and confidence stay visible
Time-aware topologyReview the environment before and after change
Human-controlled recoveryApproval before production-impacting action
DetectScope the signal
MapFollow the path
SimulateTest the model
RecoverVerify each step
One operational model
Move from cloud state to an explainable decision.
Map the system, explore a failure, and prepare recovery without turning the homepage into a manual.
02 · Failure Simulation
Explore impact safely.
Follow direct and downstream paths in the model before production is touched.
Simulate failure →
03 · Recovery
Restore in dependency order.
Prepare prerequisites, approval, validation, and rollback around the actual path.
Plan recovery →Operational context
The graph is useful when it explains a decision.
StackScopes keeps the technical path, its evidence, and the business consequence in the same reviewable frame.
The result is not another inventory. It is a working model for asking better questions before a change, during an incident, and throughout recovery.
A dependency is more than a line.
Every relationship retains its source, observation time, confidence, scope, and the reason it exists. Teams can distinguish confirmed paths from useful hypotheses.
Time changes the answer.
Current state, historical state, and proposed state answer different questions. The model preserves those boundaries so a past incident is not explained with today’s topology.
Impact needs a destination.
A resource becomes operationally important when its path reaches a workload, customer journey, tenant, owner, recovery objective, or shared control plane.
Recovery starts with prerequisites.
Restoration follows dependency order, validation checkpoints, approval boundaries, rollback conditions, and evidence—not a flat list of resources.
Questions worth answering
Use one model across planning, incidents, and recovery.
Clear questions keep the interface focused and the engineering discussion concrete.
What paths could this deployment alter?
Review shared dependencies, downstream workloads, customer exposure, and safer alternatives before release.
What changed before the signal appeared?
Place configuration, identity, topology, and health evidence on one incident-time view.
Where does this scenario propagate?
Trace direct and indirect impact while keeping assumptions and unknowns visible.
What must return first?
Build a sequence around prerequisites, RTO, RPO, validation, and rollback.
Which identity path reaches the asset?
Follow role trust, policy, secrets, networks, and cross-account relationships in context.
Who needs this evidence next?
Connect the technical path to services, teams, environments, tenants, and decision owners.
What We’ve Built
View all 12 systems
The engineering systems behind the model.
Explore how discovery, graph normalization, temporal state, simulation, and evidence work together.
01Engineering system
Temporal Cloud Digital Twin Engine
A time-aware model of cloud resources, configuration, dependencies, and operational events.
See how it works →
02Engineering system
Multi-Account AWS Discovery Pipeline
A resilient read-only discovery pipeline for approved AWS accounts and Regions.
See how it works →
03Engineering system
Normalized Resource Graph
A consistent graph model spanning different infrastructure resource types and relationship semantics.
See how it works →
Use Cases
One model. Different decisions.
Give each team the context it needs without fragmenting the cloud into separate stories.
Platform EngineeringCreate a shared, evidence-backed model of multi-account infrastructure, standards, ownership, and risk.↗Site Reliability EngineeringInvestigate incidents, simulate failure, measure resilience, and prepare dependency-aware recovery.↗DevOpsConnect infrastructure changes with the resources and services they can affect before and after deployment.↗Cloud SecurityFollow identity, network, policy, secret, and data paths to understand operational exposure.↗
Explore all solutions
Pricing Preview
Start with a clear scope.
Choose the operating context that fits today, then expand with the environment.
Starter1 AWS account · 500 resources$299 /mo
GrowthUp to 10 accounts · 5,000 resources$999 /mo
EnterpriseCustom scale, controls, and onboardingCustom
Compare plans
Read-only discoveryEvidence-backed pathsHuman-controlled operations
Latest Insights
Read all 16 articles
Field notes for connected cloud systems.
Practical analysis of dependency evidence, failure, change risk, security, and recovery.
How to Map AWS Dependencies Without Relying on Outdated Architecture Diagrams
A practical approach to explicit, inferred, runtime, and user-confirmed AWS dependency mapping.
Read the article →
Hidden AWS Dependencies: DNS, IAM, Queues, Secrets, and the Paths Teams Miss
A field guide to the identity, configuration, messaging, and network relationships that escape static diagrams.
Read the article →
Modeling Multi-Account, Multi-Region AWS Environments at Scale
Address identity, boundaries, throttling, partial failure, freshness, and normalization across an AWS estate.
Read the article →Evidence before automation
Bring one critical dependency to the demo.
See how StackScopes connects topology, failure simulation, blast radius, and recovery context around a real operational question.