Illustrative scenario
Energy companies operating widely distributed field assets — wellheads, substations, pipelines, and remote facilities — struggle to consolidate operational data fast enough to support real-time decision-making and regulatory reporting.
Visual overview · Cloud Migration and Modernization
An illustrative diagram drawn from this scenario's architecture and phases. Choose a phase to see what it works on.
Phases
SCADA and historian sources at field sites send telemetry to edge gateways, which buffer and forward it over intermittent connectivity. Choose a phase to highlight the parts of the solution it works on.
Field Data & Systems Assessment Typically 4-6 weeks
Platform Foundation Build Typically 8-10 weeks
Pilot Site Integration Typically 6-8 weeks
Scaled Rollout & Platform Engineering Enablement Typically 4-6 months
Operations Handoff Typically Ongoing
A cloud platform engineering approach builds a scalable, secure data and telemetry backbone connecting field operations to centralized analytics. The intended outcome is a modern operational data platform that gives field, engineering, and executive teams a shared, near-real-time view of asset performance.
Energy operators face a distinctive combination of pressures: highly distributed physical assets across remote geographies, intermittent or low-bandwidth connectivity at many field sites, aging SCADA and historian systems, and increasingly stringent regulatory and reliability reporting requirements. The push toward renewable integration, grid modernization, and predictive maintenance has intensified demand for real-time or near-real-time visibility into field asset performance, but many operators still rely on batch data extracts, manual spreadsheets, or siloed historian systems that were never designed to feed cloud-based analytics.
Workforce constraints in field operations add urgency to reducing manual data-handling effort, while safety and environmental incident reporting timelines leave little room for data latency. Reliability-focused regulatory frameworks add another layer of pressure, requiring auditable, timely data pipelines rather than ad hoc manual reporting processes.
Field operations data — from SCADA systems, remote sensors, and asset historians — is fragmented across regional systems and often reaches central engineering and operations teams with significant delay, sometimes requiring manual consolidation from spreadsheets or point-to-point extracts. This delay limits the organization's ability to detect equipment anomalies early, slows predictive maintenance programs, and creates a heavy manual burden for regulatory and reliability reporting.
Existing on-premises data infrastructure lacks the elasticity to onboard new field sites or sensor types quickly, and there is no consistent platform-engineering discipline (CI/CD, infrastructure as code, self-service environments) supporting the internal teams who build operational dashboards and analytics.
New field sites and sensor types are onboarded through standardized, self-service pipelines rather than custom point-to-point integration projects. Internal engineering teams operate on a modern platform-engineering foundation — golden-path CI/CD pipelines, reusable infrastructure templates, and self-service environments — that lets them ship new analytics and monitoring capabilities without depending on scarce centralized infrastructure resources.
In this scenario, the delivery team designs and builds a cloud-native field-operations data platform combining scalable ingestion pipelines from SCADA/historian sources, a governed data lake and analytics layer, and a platform-engineering foundation of reusable infrastructure-as-code modules and CI/CD pipelines. The engagement is delivered as a project, embedding platform engineers and DevOps specialists directly within the organization's existing operations technology and data programs to accelerate delivery without disrupting ongoing initiatives, with a defined path to documented handover.
The target architecture centers on a secure landing zone with a segmented network boundary between OT/field systems and the cloud data platform, using edge gateways at field sites to buffer and forward telemetry reliably even over intermittent connectivity. Ingested data lands in a governed data lake with defined zones (raw, curated, analytics-ready), feeding both real-time dashboards and longer-term predictive maintenance and reliability analytics.
A platform-engineering layer provides internal teams with self-service, templated environments and automated CI/CD pipelines so new dashboards, models, or field-site integrations can be built and deployed consistently without specific infrastructure work each time. Centralized monitoring and access governance give operations leadership auditable visibility into data flows for regulatory reporting.
Typically 4-6 weeks
Inventory of SCADA/historian sources, field connectivity constraints, and existing reporting workflows; platform architecture and integration design.
Typically 8-10 weeks
Landing zone, network segmentation, edge gateway deployment, data lake zones, and initial CI/CD pipeline templates.
Typically 6-8 weeks
Onboard a subset of field sites onto the new ingestion pipeline; validate latency, data quality, and dashboard accuracy.
Typically 4-6 months
Onboard remaining field sites in waves; roll out self-service platform tooling and golden-path pipelines to internal engineering teams.
Typically Ongoing
Transition to internal ownership or managed operations, documentation and an agreed handover, knowledge transfer workshops.
Scope: business systems and the data they take from operational environments. Operational control and safety systems stay with the operator and its specialist vendors.
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The service and industry pages behind this scenario, and other scenarios like it.
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