Industry patterns · Utilities and field services

Field inspection and asset maintenance

Inspectors capture evidence on mobile devices, offline if needed. Findings flow to the asset register and generate work orders with a complete, timestamped evidence trail.

A reference architecture from EITSAA, not a named client system. Service limits, prices and product features change, so confirm current details before you commit to a design.

  • Australian Privacy Principles
  • ACSC Essential Eight
  • Critical infrastructure security expectations where applicable

Architecture

Architecture diagram. Tinted boundaries show regions, accounts, networks and trust zones. Numbered arrows match the flow below.
Field inspection and asset maintenance architectureInspector app to API Gateway + Cognito: sync. API Gateway + Cognito to Sync service: batch. Sync service to S3 evidence: evidence. Sync service to Aurora + PostGIS: findings. S3 evidence to Defect detection: suggest. Supervisor to Aurora + PostGIS: approve. Sync service to Asset and work-order system: work orderFieldAWS account · ap-southeast-2Enterprise assetsystemsInspector appOffline-first, GPS, photosSupervisorReview, approveAPI Gateway + CognitoDevice-bound authSync serviceConflict rulesS3 evidencePhotos, video, hashAurora + PostGISInspections, findingsDefect detectionRekognition or SageMakerAsset and work-ordersystemSAP PM, Maximo, IBM1sync2batch3evidence4findings5suggest6approve7work orderPlatform servicesAWS IAMAmazonCloudWatchAWS CloudTrailAWS KMS
  • People and clients
  • Network and edge
  • Databases and data
  • Object and file storage
  • AI and ML
  • Monitoring, audit and analytics
  • SaaS and business systems
  • Security and identity
  • Request or data flow
  • Asynchronous or optional
  • Boundary: region, account, network or trust zone

Request and data flow

  1. Inspectors complete checklists offline, with GPS, photos and signatures captured on the device.

  2. When coverage returns, the app syncs in batches through an authenticated API with device-bound tokens.

  3. Evidence is stored with a content hash and timestamp, so it can be shown to be unaltered.

  4. Findings are written to the database with location and asset references.

  5. Optional computer vision suggests defects for the inspector to confirm. It never closes a finding.

  6. Supervisors review and approve, and critical findings alert immediately.

  7. Approved findings create work orders in the enterprise asset system, which remains the system of record.

Components and why they were chosen

ComponentWhat it doesWhy this choice
Offline-first mobile appCapture with no coverage.Field reality.
API Gateway and CognitoAuth and sync API.Short-lived tokens, device binding.
Sync serviceMerge and conflict rules.Predictable results.
S3 with hashingEvidence store.Integrity for audits and disputes.
Aurora PostgreSQL with PostGISFindings and maps.Spatial queries.
Rekognition or SageMaker (optional)Defect suggestions.Assistive only.
Enterprise asset integrationWork orders and asset data.No second asset register.
AlertingCritical findings.Safety first.

Design decisions and trade-offs

Offline

Local-first with idempotent batch sync.

Why. Connectivity is unreliable.

Trade-off. Conflict handling must be designed.

Evidence integrity

Hash and timestamp at capture.

Why. Disputes and audits.

Trade-off. Extra processing.

AI

Suggestions only, inspector decides.

Why. Safety.

Trade-off. Less automation.

System of record

Asset system remains authoritative.

Why. One asset register.

Trade-off. Integration dependency.

Well-architected pillars

Security

Private networking, IAM Identity Center and Cognito with MFA, encryption with customer-managed keys, least-privilege roles and WAF on the public edge.

Reliability

Multi-AZ services, backups with tested restores and queue-based retries for integrations.

Performance

Edge caching for public content, asynchronous processing for anything slow and indexes tuned to the main queries.

Cost optimisation

Scale with demand, use reservations or savings plans for the steady baseline and set budgets and alerts per environment.

Operational excellence

Infrastructure as code, pipeline deployments with rollback, dashboards on service-level objectives and runbooks for the top failure modes.

Sustainability

Right-size, schedule down non-production and archive data to colder tiers on a retention schedule.

Network, identity and data

Networking

VPC with public, private and isolated data subnets and VPC endpoints. Public ingress only through the edge service with WAF. Private connectivity to on-premises or partner systems by VPN or dedicated link.

Identity and least privilege

Device-bound sessions with MFA at sign-in. Roles for inspector, supervisor and admin. Contractors on time-limited accounts.

Data and encryption

Photos may include people and sensitive infrastructure. Restrict access, encrypt, consider security classification of asset locations and retain per policy.

Security and compliance mapping

ControlHow this design addresses it
Multi-factor authenticationRequired for staff and administrators. Essential Eight.
Restrict administrative privilegesJust-in-time elevation and separate admin accounts. Essential Eight.
Regular backupsAutomated backups with a copy held outside the workload account or subscription. Essential Eight.
Privacy and security of personal informationEncryption, access logging and retention support APP 11.
LoggingCentral, tamper-resistant logs support ISM event logging guidance and ISMF expectations.

Mappings show how the design supports each control. They are not certifications, and EITSAA does not claim IRAP assessment or compliance for any reference architecture.

Failure modes, targets and scaling

  • Target RTOMinutes for zone failure; hours for a rebuild from code
  • Target RPOSeconds to minutes with point-in-time recovery
  • Scaling and limitsSized from measured peak demand with a load test before go-live. Check service quotas early.
Failure modeMitigation
Lost deviceRemote wipe, encrypted storage and short tokens.
Sync conflictServer-wins on status, merge on notes.
Large uploads failResumable multipart uploads.
Work order API downQueue and retry.

Observability and runbooks

  • Service-level objectives for availability and latency with burn-rate alerts.
  • Audit log review for sensitive actions.
  • Queue depth and integration error dashboards with a named owner.

Cost drivers and levers

Compute, database, data transfer and licences for any SaaS components.

  • Reserve the baseline.
  • Schedule non-production down.
  • Cache and compress at the edge.
  • Archive old data.

Implementation and fit

Phased approach

  1. Discovery: process, data and obligations mapped with the business owner.
  2. Foundation: landing zone, network, identity and pipeline.
  3. Thin slice: one journey end to end in production for a small group.
  4. Expand and harden: remaining journeys, load and penetration testing.

Anti-patterns to avoid

  • Building before the decision rights and audit needs are agreed.
  • A single shared admin role.
  • Personal data in logs and test data.
  • Integrations without retries or a dead-letter path.

When to use it

  • Inspection, audit and maintenance programs.
  • Teams working in poor coverage.

When not to

  • Safety-critical control systems (OT) integration without specialist review.

More in industry patterns

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    Client records, rosters, care plans and incident reporting connected on a Microsoft stack, with consent, family access and regulatory reporting handled deliberately.

  • State government

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    A public channel for an application, a payment and a case, with the decision kept with an officer and a full audit trail, hosted in Australian regions.

  • Local government

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    Residents lodge requests on web or mobile, crews work offline in the field and the council system of record stays authoritative, with AI used only to triage and summarise.

Related insights

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