Map dependencies before choosing a replacement design or migration date. Start by defining the business scope and owners, build an inventory of applications and the compute, storage, network, and external services around them, then verify each relationship with observed communications and stakeholder knowledge. Use the validated map to decide what can move independently, what must be coordinated, and in what order. Keep updating it as the target system and transition plan change.
This approach is informed by AWS Prescriptive Guidance for application portfolio assessment and migration. Its discovery and sequencing logic also works for a non-cloud replacement, but terms such as migration wave, target architecture, and platform services must be adapted to your program.
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What a dependency map must answer
A useful map is more than an architecture picture. It is a record of relationships that could affect design, testing, cutover, support, cost, or business continuity. For every in-scope application or component, the map should let a project team answer:
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- What data, interfaces, jobs, identities, infrastructure, and third-party services does it require?
- Which systems send it data, and which systems consume its outputs?
- What operational relationships matter, such as maintenance windows, release calendars, certificates, batch schedules, or on-call ownership?
- Can it transition independently, or is coordinated sequencing required?
- What evidence proves each relationship, and when was that evidence last checked?
Record the reason a relationship matters. A database connection may be a hard runtime requirement; a weekly report exchange may be a periodic dependency; a shared support team may be an operational constraint rather than a technical one. Those distinctions produce better transition decisions than a diagram that treats every line as equal.
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1. Set scope, outcomes, and owners first
Dependency discovery becomes unmanageable when “the legacy system” has no defined boundary. Write a scope statement that names the business capabilities, applications, environments, interfaces, and infrastructure included in the replacement. State what is explicitly out of scope, such as an unrelated corporate identity service or a downstream reporting platform that will remain unchanged.
Identify the people who can confirm the map
Assign named contacts for business ownership, application ownership, architecture, infrastructure, operations, security, support, and relevant platform teams. Include owners of external services and connectivity where contracts or third parties are involved. One person may hold several roles in a small organization, but each responsibility still needs an accountable name.
Capture significance, not just inventory names
For each application, record its business, functional, technical, and financial significance. Note critical processing periods, recovery expectations, regulatory or contractual obligations, data sensitivity, and the consequences of an outage. This context helps prioritize discovery and testing: a rarely used utility may have a simple technical footprint but still be essential during financial close.
Define the replacement outcome
Describe what “replaced” means: a new package, a rewritten service, a hosted platform, a consolidated product, or a staged coexistence arrangement. Identify known constraints such as required interfaces, data-retention rules, location or latency needs, and a deadline driven by contract or hardware support. Do not force a cloud migration vocabulary onto a program that is not moving to cloud infrastructure; preserve the dependency logic while using your own destination and sequencing terms.
2. Build a high-fidelity baseline inventory
Reconcile existing portfolio records with what is actually running. The inventory is the foundation for deciding a transition strategy for each application and for grouping work into feasible waves.
| Inventory area | Record | Why it matters |
|---|---|---|
| Application | Name, purpose, business capability, owner, lifecycle status, version, environment, criticality | Separates strategic applications from supporting utilities and identifies candidates for retirement, replacement, or retention |
| Compute | Hosts, virtual machines, containers, clusters, operating systems, processors, memory, locations | Reveals capacity, platform, licensing, and location constraints |
| Storage and data | Databases, file stores, queues, schemas, data owners, retention, backup and recovery arrangements | Shows what must be migrated, synchronized, archived, or kept available during coexistence |
| Network and identity | Segments, routes, firewalls, load balancers, DNS, certificates, service accounts, directory integrations | Exposes access paths and security changes that can block a cutover |
| Interfaces | API, file, message, database, batch, and manual exchanges; direction, frequency, format, owner | Identifies upstream and downstream sequencing and test obligations |
| External services | Suppliers, payment or data providers, managed connections, contracts, support contacts | Captures dependencies outside the team’s direct control |
| Operations | Maintenance windows, release and patch cycles, jobs, monitoring, on-call, incident procedures | Prevents a technically valid design from failing operationally |
Give every record a status such as confirmed, inferred, disputed, or unknown. Include an evidence reference and a last-validated date. “Unknown” is useful: it makes a gap visible instead of allowing an assumption to become a cutover surprise.
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3. Choose a discovery route: top-down, bottom-up, or both
Top-down discovery
Start from a known application, business process, or user journey. Interview its owner and trace calls, data feeds, scheduled jobs, identity dependencies, and operational procedures outward. This route works well when the application’s identity and boundaries are clear, such as a named order-management system with a documented interface catalog.
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Bottom-up discovery
Start from infrastructure when the application-to-host relationship is uncertain. Enumerate servers, processes, listening ports, installed software, database instances, network flows, and scheduled tasks, then associate those observations with applications and owners. This is particularly useful after years of server moves, acquisitions, or undocumented workarounds.
Combine the two for higher confidence
Top-down interviews reveal business intent and infrequent procedures; bottom-up observation reveals what is actually communicating. Reconcile the results rather than selecting one as the “truth.” A diagram may show a retired interface, while traffic data may reveal an undocumented connection. Conversely, a flow seen during one observation window may be a temporary job or a test environment rather than a production dependency.
4. Draw an initial relationship map
Use current diagrams as a starting point, not as proof. If no reliable diagram exists, sketch the known applications, environments, data stores, interfaces, infrastructure, and external parties. Use distinct notation for different relationship types so a reviewer can tell a runtime call from a support or scheduling relationship.
Technical relationships to capture
- Application-to-application calls, including protocol, direction, authentication, and expected response behavior.
- Reads and writes to databases, files, queues, caches, and shared storage.
- Application-to-host, cluster, operating-system, runtime, and network relationships.
- Identity, secrets, certificate, DNS, time, logging, monitoring, and backup services.
- Batch schedules, event triggers, retries, timeouts, and volume or latency requirements.
Operational and external relationships
- Release, patch, maintenance, and blackout windows.
- Manual steps, reconciliations, approvals, and support handoffs.
- Third-party APIs, managed file transfers, payment or data feeds, and connectivity providers.
- Service-level commitments, support contacts, contracts, and notice periods.
- Dependencies on a particular location, network path, time zone, or business calendar.
For each edge, write a short statement in the form “A depends on B because …” and add the consequence of changing or interrupting B. This prevents a visually impressive graph from hiding an unexamined assumption.
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Validation is the step that exposes the gap between documented design and observed behavior. Use application-performance or discovery tooling where appropriate to identify components and communication patterns. Compare those results with interviews involving owners, business stakeholders, infrastructure engineers, and operations staff.
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Use several evidence types
| Evidence | Strength | Typical limitation |
|---|---|---|
| Architecture diagrams and interface catalogs | Fast overview and intended design | May contain retired, missing, or incorrectly labeled relationships |
| Owner and operator interviews | Explains business meaning, exceptions, and infrequent work | Relies on memory and may differ between teams |
| Configuration and inventory records | Shows declared endpoints, jobs, packages, and ownership | Configuration can be stale or copied between environments |
| Observed network and process data | Shows components that actually communicate during the observation period | Rare or seasonal dependencies may not appear |
| Logs, traces, job histories, and tickets | Provides examples of calls, failures, and operational handling | Retention, redaction, or inconsistent logging can leave gaps |
Mark each relationship with its evidence and confidence. Schedule additional observation around month-end, quarter-end, seasonal peaks, scheduled file exchanges, and other periods when infrequent dependencies are likely to occur.
When no discovery tooling is available
A manual approach can inspect open ports, established connections, running processes, installed software, scheduled tasks, configuration files, and relevant logs. It requires careful coordination and can leave errors or omissions. AWS guidance describes programmatic discovery as capable of capturing most dependencies in a few days, except relationships that occur at greater intervals, while manual discovery can take weeks. These are qualitative planning estimates from that guidance, not universal measured benchmarks.
6. Separate true coupling from shared infrastructure
Do not group applications merely because they share a host, cluster, database server, network segment, or platform service. Individualize each application-to-infrastructure relationship and describe the actual requirement.
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Example: one shared database server
Three applications may use the same database server but have separate schemas, connection pools, release calendars, and data owners. One may be replaced independently; another may require a data conversion; the third may remain on the old platform for a year. The server is a shared infrastructure constraint, not proof that all three applications must transition together.
When coordination really is required
Coordinate components when a relationship creates a measurable transition constraint, such as an incompatible data model, an atomic transaction across systems, a latency requirement that the target cannot meet independently, a shared cutover record, a certificate or identity change that affects both sides, or a contractual window controlled by a third party. Record the constraint and its owner rather than relying on a visual cluster.
7. Turn the map into transition and wave decisions
For each application or component, record a proposed strategy: replace, rehost, refactor, retain, retire, or another locally defined category. The exact labels are less important than documenting the decision, rationale, unresolved dependencies, and evidence.
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Build a transition matrix
| Field | Example entry |
|---|---|
| Component | Legacy invoicing service |
| Proposed action | Replace with a new service while retaining historical records in read-only storage |
| Prerequisites | Customer master interface, tax-rate feed, identity integration, archival export |
| Can move independently? | Only after the outbound ledger interface supports the new schema |
| Operational constraints | Monthly close blackout; finance reconciliation required before cutover |
| Evidence and confidence | Observed API traffic, job history, owner confirmation; high for daily flows, medium for quarterly adjustment feed |
| Validation owner | Application owner with finance operations representative |
Group by dependency and constraint
Use the matrix to form waves or releases that can be tested, supported, and cut over together. A wave may contain one application, a tightly coupled set, or a platform prerequisite followed by dependent applications. Keep a visible list of items that are deliberately separated despite shared infrastructure, and explain why.
Carry cutover work into the plan
For every wave, define data synchronization, interface switching, credential and certificate changes, rollback conditions, monitoring, user support, and reconciliation. A dependency map that stops at architecture does not answer whether the business can operate during the transition.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.8. Revisit the map as the design changes
Discovery is iterative. A target architecture may introduce a new identity provider, message broker, integration layer, or reporting path; each can create new dependencies. Conversely, a replacement may remove old interfaces or consolidate several components.
At each planning checkpoint, reassess scope, target architecture, platform requirements, transition approach, and cutover considerations. Update owners, evidence, confidence, and dates when a new relationship is found. Require the wave lead to sign off on the dependency set before detailed testing and again before production cutover. AWS Prescriptive Guidance emphasizes avoiding last-minute changes during and after migration; maintaining the map is one practical way to surface those changes earlier.
9. Select discovery tooling by capability, not brand
Evaluate tools or services against the evidence and planning your program actually needs. A product that only imports a static inventory is not equivalent to one that observes component communications.
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|---|---|
| Evidence depth | Does it inventory assets only, or capture observed flows, processes, and component-level dependencies? |
| Coverage | Can it represent applications, infrastructure, external services, environments, and operational relationships? |
| Validation | Can teams compare discovered data with diagrams, configuration, and owner knowledge, then record confidence and exceptions? |
| Planning support | Does it export data and support visualization, prioritization, grouping, wave planning, or cost estimation where needed? |
| Deployment fit | What credentials, network access, agents, data handling, third-party coordination, and security approvals are required? |
| Maintenance | Can the map be refreshed and diffed as dependencies, scope, and target architecture change? |
Discovery may require privileged credentials, network access, and coordination with third-party operators. Treat those as implementation work with an owner and schedule. Do not assume that a tool’s ability to draw a graph proves that the graph is complete.
10. Common failure modes and corrections
Relying on an old diagram
Symptom: The project discovers an interface during testing that no document showed. Correction: Use diagrams as hypotheses, then reconcile them with observed communications, logs, configuration, and interviews.
Mapping only the application name
Symptom: The team cannot identify the host, data store, identity path, or operational owner needed for cutover. Correction: Extend each application record through compute, storage, network, security, interfaces, external services, and operations.
Treating every shared service as a hard coupling
Symptom: An unnecessarily large wave is created because several applications use one platform. Correction: Map each application’s actual use and record the specific latency, data, business, or operational constraint that requires coordination.
Ignoring infrequent exchanges
Symptom: Daily traffic is understood, but a quarterly or exception process fails after cutover. Correction: Review job histories, tickets, calendars, business procedures, and seasonal observation windows; label unobserved periodic dependencies explicitly.
Stopping discovery when the baseline is published
Symptom: The target design introduces new dependencies that are absent from the plan. Correction: Make map updates a deliverable for every design review, test exit, wave assessment, and cutover readiness review.
11. A practical review checklist
- Scope names included and excluded applications, environments, infrastructure, and interfaces.
- Every in-scope item has a business or technical owner and a significance rating.
- Compute, storage, network, identity, security, monitoring, backup, and operational services are inventoried.
- Upstream, downstream, internal, external, technical, and operational relationships are recorded.
- Each important edge has a reason, evidence, confidence, and validation date.
- Top-down knowledge and bottom-up observation have been reconciled.
- Infrequent, seasonal, manual, and exception processes have been considered.
- Shared infrastructure has not been used as the sole reason to group applications.
- Each component has a transition decision, unresolved-dependency list, and proposed sequence.
- Wave plans include synchronization, interface switching, support, monitoring, reconciliation, and rollback considerations.
- The map has a named maintainer and a refresh schedule tied to design and release milestones.
Putting the method into practice
The safest replacement programs treat dependency mapping as a living decision record. Define the boundary, establish ownership, inventory what exists, discover how it communicates, validate the findings, and distinguish genuine coupling from simple co-location. Then use the resulting evidence to choose transition strategies and sequence work that the organization can test and operate. Recheck the map whenever scope or target architecture changes. This discipline turns an uncertain legacy estate into an explicit set of decisions rather than a last-minute cutover gamble.
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