IoT & Edge Solutions

EPAM’s IoT & Edge Solutions implementation helps CIOs, CTOs, operations leaders, and digital engineering teams design, build, and scale secure IoT & Edge solutions on Microsoft Azure. This offer addresses key enterprise challenges such as fragmented device ecosystems, lack of real-time insights, scalability limitations, and complex edge-to-cloud integration. By leveraging Azure IoT services and Industrial IoT patterns, organizations can accelerate digital transformation, enable predictive analytics, and unlock new business value from connected assets.

What You Will Receive

• End-to-End IoT Architecture: Design and deployment of scalable IoT platforms using Azure IoT Hub, Azure IoT Edge, and Azure IoT Central for device connectivity, management, and telemetry processing.
• Low-Code IoT Enablement: Rapid deployment of prebuilt solutions with Azure IoT Central, enabling fast onboarding, visualization, and monitoring of connected devices.
• Cloud-Native IoT Platforms: Custom IoT solutions integrating Azure PaaS services for real-time ingestion, processing, and advanced analytics.
• Industrial IoT & Edge: Implementation of hybrid and edge architectures using Azure Arc-enabled Kubernetes for centralized governance, low-latency processing, and resilient operations.
• Data & Analytics Integration: Integration with Microsoft Fabric, Azure Data Services, and AI/ML capabilities to enable predictive maintenance, anomaly detection, and digital twins.

Typical Implementation Approach

Phase 1 — Discovery

• Assessment of business, operational, and security requirements.
• Evaluation of IoT assets, protocols, and device compatibility.
• Definition of use cases, KPIs, and solution scope.
• Artifacts: IoT readiness assessment, architecture vision, and use-case backlog.

Phase 2 — Foundation

• Design of device management framework and IoT platform architecture.
• Setup of data ingestion, storage, and processing layers.
• Selection of Azure IoT services and edge components.
• Artifacts: Solution architecture design, data model, security baseline, and platform blueprint.

Phase 3 — Jumpstart

• Deployment of IoT devices, edge components, and telemetry pipelines.
• Integration with enterprise systems and analytics platforms.
• Implementation of dashboards, alerts, and AI-driven insights.
• Artifacts: Deployed IoT workloads, data pipelines, dashboards, and initial AI models.

Phase 4 — Delivery at Scale

• Scaling device connectivity and production-grade IoT environments.
• Implementation of predictive analytics, reporting, and digital twins.
• Operationalization with monitoring, governance, and cost optimization.
• Artifacts: Production IoT platform, operational dashboards, runbooks, and governance model.

Expected Outcomes

• Accelerated deployment of enterprise-grade IoT & Edge solutions on Azure.
• Real-time visibility into operations with centralized telemetry and analytics.
• Improved operational efficiency through automation and predictive insights.
• Scalable and secure Industrial IoT architecture ready for global deployment.
• Reduced time-to-value with standardized, reusable IoT patterns and accelerators.