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IoT

Fleets of devices speaking into one layer.

An IoT estate is a fleet of identifiers producing telemetry, and the hard parts are device identity, current state and history that survives a device being replaced.

See IoT All of Infrastructure & Technology

A fleet whose history survives every replacement and re-keying.

The story

A fleet whose history survives every replacement and re-keying.

Where it starts

Device telemetry

Readings with device and sensor identity attached. It is the first of 4 workloads running in IoT.

The question it raises

Fleet questions in one request

Device records, telemetry windows and lifecycle events read together rather than across an ingestion stack.

Why one question is hard

From Provision to Maintain

IoT data moves through 4 stages — Provision → Ingest → Resolve state → Maintain. The shapes in play are Time series, SQL, JSON / documents, Key-value, Events, and answering one question means reading across all of them.

What PLOMID contributes

A fleet is many writers and one identity model. These are the parts that keep them consistent.

  • Time-ordered storage Measurements and events are stored beside the records and documents they describe, so history and current state agree.
  • One data layer Rows, documents and time-ordered events live in one system, so a question is asked once instead of once per store.
  • Every client, one layer Applications, AI clients, services and background jobs reach the same data through the same interfaces.
The environment

Device fleets, telemetry, device state and the events between them.

Devices are records, telemetry is time-ordered, current state is direct access by one key, and fleet events describe lifecycle changes. PLOMID keeps the device record, its telemetry and its events in one layer, so fleet questions read from one system rather than from an ingestion pipeline’s output store.

Workload architecture

The system reading itself.

Planning, execution and transactions first — then the workloads that use them and the shapes they name.

IoT · workload architecture
Workloads

What runs against this data.

  • Device telemetry
  • Device records
  • State by key
  • Fleet events
Data models

The shapes those workloads read and write.

  • Time series
  • SQL
  • JSON / documents
  • Key-value
  • Events
The layer

One path from a request to the data it names.

  • Planning Predicates narrow the work before it runs
  • Execution Records, fields and windows answered together
  • Transactions Readers and writers do not block each other
Surfaces

How the work reaches the layer.

  • SQL surface The query language the layer is documented in
  • Applications Services and jobs writing and reading as they run
  • Analytics & AI clients The same layer, the same access path
One environment · many workloads

What runs against iot data.

4 workload families over one set of shapes. Choose one to see what it moves and where it lands.

Readings with device and sensor identity attached.

  • Planned once against the layer, not once per store
  • Read beside the records it shares a key with
  • Persisted under one storage contract
The data journey

How iot data reaches one layer.

Walk the path the data takes, from the environment that produces it to the questions it answers. Select a station, or a shape, to read each step.

A fleet whose history survives every replacement and re-keying.

Environment

The device

Identity, model and firmware recorded at provisioning.

SQL

Data models in play

The shapes, in one layer.

5 shapes carry this domain. Choose a stage to read the operation, or a shape to see every stage that handles it.

PLOMID · IoT provision · ingest · resolve state · maintain Select a stage
Stage

Provision

Device identity, model and ownership records

SQL

Workload map IoT workload map. Every shape on it is a surface of the layer, and each stage names the part of the operation it carries.
  • Time series Measurements and events in time order
  • SQL Records, keys and joins
  • JSON / documents Documents and nested objects
  • Key-value Direct access by key
  • Events Operational events as they happen
Where the data goes to work

Questions a fleet asks about itself.

Each one reads telemetry with the records that explain it, from the same layer rather than a sidecar store.

Fleet questions in one request

Device records, telemetry windows and lifecycle events read together rather than across an ingestion stack.

  • SQL

State without a scan

Current state is addressed by key instead of by scanning the newest measurements.

  • Time series
  • JSON / documents

Device replacement

Identity changes are records, so history survives a hardware swap.

  • Key-value

Firmware cohort analysis

Update events are read against the readings that followed them.

  • Events
  • SQL
Deployment & residency

Where this data is allowed to run.

Devices write from wherever they are, so ingestion has to tolerate intermittent links and duplicate delivery.

Deployment, residency and control
What you build next

IoT

Device fleets: identity, telemetry, current state and lifecycle events.

If Fleet questions in one request is your question, start here.

See IoT Every solution
Next

Where to go next

Solutions The workload answers this industry leans on, with their models and status. Platform The data models in the product today, and the ones extending the layer. Architecture How a request is planned, executed and persisted once it reaches the layer.