Infrastructure & Technology
Systems that produce data about themselves.
Telecom, device fleets, observability, security, twins and city infrastructure are one problem in different clothes: a growing fleet of endpoints writing state, and a small set of questions asked across all of it.
Systems that produce data about themselves.
The system, then the data underneath it.
Start with the path a request takes — planning, execution, transactions — then the workloads that use it and the shapes they name. The system that produces data about itself is read first as architecture.
What runs against this data.
- Device telemetry
- Device records
- State by key
- Fleet events
- Security events
The shapes those workloads read and write.
- Time series
- SQL
- JSON / documents
- Key-value
- Events
- Graph
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
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
Where this industry runs.
The environments in this industry. Every one of them is a fleet writing state continuously while a much smaller number of readers ask questions across it.
- IoT Device fleets, telemetry, device state and the events between them.
- Cybersecurity Telemetry, identity, asset relationships and the cases that follow.
- Observability Metrics, logs, traces and the service records they describe.
- Digital Twins Asset models, live telemetry, relationships and the queries run against them.
- Autonomous Systems Sensor streams, perception output, decisions, interventions and logs.
- Smart Infrastructure Buildings, transport and civic systems with sensors attached.
What runs against infrastructure data.
Workloads drawn from every environment in this industry. Choose one to see the shapes it moves and where it lands.
Readings with device and sensor identity attached. — IoT
- Planned once against the layer, not once per store
- Read beside the records it shares a key with
- Persisted under one storage contract
Fleets, models, firmware, provisioning and ownership. — IoT
- Planned once against the layer, not once per store
- Read beside the records it shares a key with
- Persisted under one storage contract
Last known state and configuration addressed directly. — IoT
- Planned once against the layer, not once per store
- Read beside the records it shares a key with
- Persisted under one storage contract
Provisioning, firmware updates, faults and decommissions. — IoT
- Planned once against the layer, not once per store
- Read beside the records it shares a key with
- Persisted under one storage contract
Authentication, network, endpoint and application events. — Cybersecurity
- Planned once against the layer, not once per store
- Read beside the records it shares a key with
- Persisted under one storage contract
Users, service accounts, hosts, services and their owners. — Cybersecurity
- Planned once against the layer, not once per store
- Read beside the records it shares a key with
- Persisted under one storage contract
Access, membership, trust and reachability structure. — Cybersecurity
- Planned once against the layer, not once per store
- Read beside the records it shares a key with
- Persisted under one storage contract
Investigations, notes, evidence and remediation records. — Cybersecurity
- Planned once against the layer, not once per store
- Read beside the records it shares a key with
- Persisted under one storage contract
From the system that emits to the layer that holds.
Systems that produce data about themselves, and the networks they run on. Four readings of the same system, ending where the system reads itself: the environments, the shapes, the layer, and the questions a fleet asks about its own state.
The contexts this industry runs in.
- IoT Device fleets, telemetry, device state and the events between them.
- Cybersecurity Telemetry, identity, asset relationships and the cases that follow.
- Observability Metrics, logs, traces and the service records they describe.
- Digital Twins Asset models, live telemetry, relationships and the queries run against them.
- Autonomous Systems Sensor streams, perception output, decisions, interventions and logs.
The shapes the data takes across them.
- 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 shapes stop being separate systems.
- One plan per request
- Snapshot reads under continuous writes
- One storage contract
The questions asked across the industry.
- Fleet questions in one request
- State without a scan
- Device replacement
- Firmware cohort analysis
One layer holds these shapes at once, which is what removes the copy between them: an event, the record it belongs to and the document around it are read from the same place, whichever environment is asking.
The parts of the layer this industry leans on.
Counted across the environments above rather than chosen for this page: the properties every environment in this industry depends on, and the workload answers they keep returning to.
- 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.
- Deployment is a decision Self-hosted, edge and managed topologies are design destinations of the deployment fabric, and the fabric is specified as its own part of the platform.
- Relationships held as data Edges expressed directly remove the reconstruction that happens at query time when relationships live in a join.
- Predicates narrow the work Indexes and access paths decide what a query touches before a page is read, so operational reads stay bounded.
- Control over operation Who runs the system, and where it runs, is part of the first conversation rather than a tier on a pricing page.
Solutions this industry keeps returning to.
Derived from the industry's own environments: the solutions referenced by the most of them, each one a page of its own.
- Time-series Workloads → Measurements and events stored beside the records they describe. Referenced by 4 of 6 environments.
- Real-time Analytics → Windows and aggregates over data that is still being written. Referenced by 4 of 6 environments.
- Edge Computing → Data and reads close to the source, with one durable record behind them. Referenced by 4 of 6 environments.
- IoT → Device fleets: identity, telemetry, current state and lifecycle events. Referenced by 3 of 6 environments.
- Digital Twins → An asset model that is read from operational data instead of synchronised with it. Referenced by 3 of 6 environments.
- Operational Analytics → Reporting that reads the operational source instead of a copy of it. Referenced by 3 of 6 environments.
- IoTDevice fleets, telemetry, device state and the events between them.
- CybersecurityTelemetry, identity, asset relationships and the cases that follow.
- ObservabilityMetrics, logs, traces and the service records they describe.
- Digital TwinsAsset models, live telemetry, relationships and the queries run against them.
- Autonomous SystemsSensor streams, perception output, decisions, interventions and logs.
- Smart InfrastructureBuildings, transport and civic systems with sensors attached.
The fleet writes about itself.
Tell us which networks, devices and platforms you operate and who asks questions of their state. We will map them to the workloads, the shapes and the parts of the layer that carry them.