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Telecom

Investigate network
outages.

Connect alarms, network dependencies and recent changes. Help engineers find what affected sites share and retrieve the relevant runbook.

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Outage investigation
Three telecom sites connect to an upstream switch, with the affected network route highlighted.

Trace affected sites to a shared network dependency.

Illustrative use case

01 / Use case guide

10 practical use cases.

Compare the data models behind everyday industry tasks, from finding records to following connections.

SQL Filter and calculate Vector Match similar meaning Graph Follow relationships Full-text Find words and phrases

Suggested model combination

Scroll across to compare all four models
Use case How the data models help SQL Vector Graph Full-text Source
Prioritize active network alarms Engineers need a manageable list of current alarms to investigate. SQL filters alarms by severity, site and time; Full-text finds specific alarm codes and messages.
Map affected customer services An incident team needs to know which services depend on failing equipment. Graph follows equipment and service dependencies; SQL checks active services and current incident timestamps.
Compare recent maintenance changes Engineers need to see whether affected systems share a recent maintenance change. Graph connects changes to affected equipment and services; SQL compares maintenance times with alarm onset for engineer review.
Find similar resolved incidents An engineer needs useful precedents for an unfamiliar network symptom. Vector finds similar incident descriptions; SQL filters by equipment and resolution status; Full-text retrieves recorded fault codes and recovery notes.
Track customer trouble tickets Support teams need the current state of a fault reported across partner systems. SQL filters open tickets by severity and age; Graph follows related partner tickets; Full-text finds fault descriptions and ticket references.
Check service order progress Operations staff need to find service orders that are still incomplete. SQL filters orders by status and requested date; Graph connects each order to its service items for staff review.
Check address service availability A sales agent needs to know whether a requested service can be delivered. Graph follows service designs to required resources; SQL checks location, capacity and qualification results before the service team confirms availability.
Find installation appointment slots A customer needs an available time for an installation or repair visit. SQL filters open appointment slots by place and time; Graph links the visit to its order or trouble ticket.
Reconcile network inventory records Recorded equipment details no longer match the latest network discovery. SQL compares discovered and recorded resource attributes; Graph traces changed equipment relationships for inventory staff to review.
Explain monthly bill changes A support agent needs to explain an increase in a customer's bill. SQL compares charges, credits and discounts across billing periods; Graph connects each changed charge to its account and product.

Use the query interfaces you need, then connect their results through shared record IDs in your application.

Industry sources 9

These sources describe real industry workflows. The model combinations above are proposed OriginChainDB designs, not customer deployment claims.

  1. TM Forum — Fault Management
  2. KDDI — Starting Operation of Fault Recovery support Agent
  3. Telefónica — Driving network incident resolution with AI agents and LLMs
  4. TM Forum — TMF621 Trouble Ticket REST API Specification R14.5.1
  5. TM Forum — TMF641 Service Ordering Management API User Guide v4.1.1
  6. TM Forum — Service Qualification Management
  7. TM Forum — TMF646 Appointment Management API REST Specification R19.0.1
  8. TM Forum — Resource Discovery and Reconciliation
  9. TM Forum — TMFC031 Bill Calculation Management v3.0.0

02 / A closer look

Several sites fail after a network change

Several sites report degraded service after a network change. Alarms arrive from different systems, customer reports use different descriptions, and the affected sites may share an upstream device. Engineers need evidence before choosing a recovery action.

What makes it difficult

  1. 01

    Alarm volume hides related symptoms.

  2. 02

    Service impact and physical dependencies live apart.

  3. 03

    Old topology or runbooks can mislead an investigation.

Suggested approach

Trace shared network dependencies

Start with the affected sites and follow their upstream connections. Compare alarms with recent changes, then retrieve runbooks and previous incidents that help engineers test a cause.

03 / Queries

What each data model does

Select a model to see the question it answers.

SQL · Find the facts

The question

Show critical alarms for these sites since the change.

Narrow events by region, time, device and severity.

Explore SQL
Vector · Match the meaning

The question

Find past incidents describing intermittent packet loss.

Find incidents and guidance with similar symptoms.

Explore Vector
Graph · Follow the connections

The question

Which device is shared by the affected sites?

Trace service, site and upstream network dependencies.

Explore Graph
Full-text · Find the exact wording

The question

Find the approved procedure for this error code.

Locate exact alarm codes and runbook instructions.

Explore Full-text

Use shared record IDs to combine results from the different query interfaces in your application.

04 / Implementation

How to build it

  1. STEP 01

    Choose a region or service

    Use authorized read-only alarm exports, topology records and resolved incidents. Define the investigation questions with engineers.

  2. STEP 02

    Record topology and timestamps

    Assign service, device and change IDs. Store event and ingestion times, topology validity and runbook versions. Refresh indexes after source changes.

  3. STEP 03

    Show candidate causes

    Combine affected services, dependency paths and recent changes. Link supporting runbooks and mark uncertain relationships for the engineer to check.

  4. STEP 04

    Replay resolved incidents

    Check missed dependencies and stale topology against known incidents. Pilot read-only triage first; keep network changes behind existing operator approvals.

05 / Testing

What to measure

Compare these results with your current process before rollout.

Time to useful evidence

Measure how quickly an engineer finds a relevant dependency and supporting records.

Incident coverage

Check whether the known cause appears among the evidence in replayed incidents.

Topology freshness

Track stale or incorrect links discovered during incident review.

06 / Sources

Examples from the industry

Published projects and reference material relevant to this use case.

Industry example 19 February 2026

KDDI

Starting operation of Fault Recovery Support Agent

KDDI announced operation of a fault-recovery support agent for selected services. It connects system information, equipment alarms and operational history to help staff identify failure causes.

Read the source
Industry context 30 March 2026

Telefónica

Driving network incident resolution with AI agents and LLMs

Telefónica discusses network incident resolution using correlated information across services, users and network elements, alongside operational systems and AI assistance.

Read the source

These are industry references, not OriginChainDB customer stories. The implementation above is a proposed example.

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