Microsoft Corp. announced new capabilities that further simplify the customer journey and deliver highly secured IoT solutions.
These solutions help customers embrace IoT as a core strategy to drive better business outcomes, improve safety and address social issues by predicting and preventing equipment failures, optimizing smart buildings for space utilization and energy management, improving patient outcomes and worker safety, tracking assets across a supply chain, and more.
“At Microsoft, we are committed to building a trusted, easy-to-use platform that allows our customers and partners to build seamless, smart, secure solutions regardless of where they are in the IoT journey,” said Sam George, CVP of Azure IoT at Microsoft. “That’s why we are investing $5B in IoT and intelligent edge — technology that is accelerating ubiquitous computing and bringing unparalleled opportunity across industries.”
IoT Central is a fully managed IoT app platform that provides solution builders with built-in security, scale and extensibility needed to develop enterprise-grade IoT solutions.
New features to IoT Central simplify challenges of building and deploying scalable and affordable enterprise applications:
- 11 new industry-focused application templates to accelerate solution builders across retail, healthcare, government and energy.
- API support for extending IoT Central or integrating it with other solutions, including API support for device modelling, provisioning, lifecycle management, operations and data querying.
- IoT Edge support, including management for edge devices and IoT Edge module deployments, which enable customers to deploy cloud workloads, including AI, directly to connected devices.
- IoT Plug and Play support, for rapid device development and connectivity.
- The ability to Save & Load applications to enable application reusability.
- More Data Export options for continually exporting data to other Azure PaaS services, such as storage for rich analytics.
- Multitenancy support for building and managing a single application with multiple tenants, each with their own isolated data, devices, users and roles. And updates to that single application are visible to all tenants for easy manageability.
- Custom user roles for fine-grained access control to data, actions and configurations in the system.
- New pricing model for early 2020, designed to help customers and partners have predictable pricing as usage scales.
Azure IoT Hub helps enterprise developers reduce costs and optimize operations through IoT cloud applications. New capabilities with IoT Hub message enrichment add the ability to stamp messages coming from devices with rich information before they are sent to downstream cloud services, making integration easy. IoT Hub integrates with Azure Event Grid, making it easy to consume IoT Hub device messages from an even broader variety of downstream services.
Azure Maps customers can add geospatial weather intelligence into their applications to enable scenarios like weather-based routing, weather-based targeted marketing and weather-based operations optimization, in partnership with AccuWeather. Azure Maps will now be available on Gov Cloud, simplifying the onboarding process for customers.
Azure Time Series Insights is announcing new preview capabilities including:
- Multilayered storage provides the best of both worlds: lightning fast access to frequently used data (“warm data”) and fast access to infrequently used historical data (“cold data”).
- Flexible cold storage: Historical data is stored in a customer’s own Azure Storage account, giving customers complete control of their IoT data. Data is stored in open source Apache Parquet format, enabling predictive analytics, machine learning and other custom computations using familiar technologies including Spark, Databricks and Jupyter.
- Rich analytics: Rich query APIs and user experience support interpolation, new scalar and aggregate functions, categorical variables, scatter plots, and time shifting between time series signals for in-depth analysis.
- Enterprise-grade scale: Scale and performance improvements at all layers, including ingestion, storage, query and metadata/model.
- Extensibility and integration: New Time Series Insights Power BI connector allows customers to take queries from Time Series Insights into Power BI to get a unified view in a single pane of glass.
Microsoft also added new features to Azure Security Center for IoT with the announcement of a Security Partner program and support for national clouds, and the upcoming general availability of Azure Sphere in February 2020.
Enabling a future of intelligent and secure computing at the edge for organizations, enterprises and consumers will require advances in computer architecture all the way down to the chip level, with security built in from the beginning. Microsoft Azure Sphere is taking a holistic approach to securing the intelligent edge and IoT from the silicon to the cloud in a way that gives customers flexibility and control. For example, Qualcomm recently announced a partnership with Microsoft to develop mobile hardware for Microsoft’s Azure Sphere IoT operating system.
The Latest
In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...
In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...
Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...
In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ...
Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...
Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...
Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...
The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...
The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...
In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...