Wind River Studio provides unrivaled observability into the distributed cloud network.

Collect. Monitor. Analyze. Report. Alert.

Once a distributed cloud is deployed, Wind River® Studio Analytics supports effective management of a distributed cloud system by consuming and processing data through machine-learning algorithms, to produce meaningful insights for decision-making.

Wind River Studio Analytics Solutions


Collect a broad and deep data set tailored for your needs. Data can be pulled across all layers of the system, including the hardware, container abstractions, services, and applications. Detailed memory, CPU, storage, network traffic, and service state are gathered to ensure that the entire operational landscape is monitored.


Aggregate both structured and unstructured data, including logs and metrics. Whether at the individual host level or aggregated with the local or distributed cluster, data is enriched to provide context beyond the metric and timestamp and includes tagging, transformation, and preprocessing. Pre-integrated plugins permit distribution of select data to various end points.

Processing and Storage

Studio includes replication indexing, which provides redundancy as robust as the system and makes the data faster for search. Lifecycle management ensures that the data is managed appropriately and persists only as it needs to.


Put the data to use to derive powerful insights into the distributed cloud. Visualizations, dashboards, and ML-based trend analysis provide a view that can be interpreted for proactive decision-making to keep your network healthy and optimized.


Proactive alerts and comprehensive reports keep you up-to-date about what is happening in your distributed cloud.

Full-Stack Monitoring of Infrastructure and Services

Because Studio Analytics is fully integrated into Wind River Studio, it allows you to access a much larger, full-stack data set that you can use to keep your system optimized.

Full-Stack Monitoring of Infrastructure and Services

Wind River Studio Analytics

Analytics Capabilities Overview

Studio Analytics provides insights to keep your system up and optimized. This demonstration provides a brief tour of the key capabilities.

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System overview

Studio provides an overview of overall infrastructure health and removes the operational burden of analyzing individual systems and hosts. Users may drill down to individual entities for detailed analysis.

Machine learning and anomaly explorer

Track system-wide anomalies over a time horizon, noting the highest anomaly level present. Studio also displays the severity level learned at the measuring interval.

Machine learning and analysis

Learn patterns, note and record abnormal behavior and create an anomaly event, forecast trends, and change behavior to adapt.

Wind River Studio Analytics Ecosystem Partners

Elastic Search Logo

Elasticsearch is a search engine based on the Lucene library. It provides a distributed, multi-tenant–capable full-text search engine with an HTTP web interface and schema-free JSON documents.

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Kibana Logo

Kibana is a data visualization and exploration tool used for log and time-series analytics, application monitoring, and operational intelligence use cases.

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Kafka Logo

Apache Kafka is a distributed event store and stream-processing platform. The project aims to provide a unified, high-throughput, low-latency platform for handling real-time data feeds.

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Infographic 5G

The World Is Evolving Rapidly with 5G

Service providers are expected to invest over $900M worldwide in 5G network infrastructure in the next five years. See this infographic to understand some of the key drivers and considerations.

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Wind River Studio Analytics FAQs

Studio Analytics supports the ability to analyze real-time and historical, structured, and unstructured data across the entire distributed cloud infrastructure and services. It can gather detailed memory, CPU, file system, service state, and applications data to ensure that the entire operational landscape is monitored. It can also compare historical data with current operation data to determine whether there is an anomaly in the system.
Whether at the individual host level or aggregated with the local or distributed cluster, data is enriched to provide context beyond the metric and timestamp and includes tagging, transformation, and preprocessing.
Studio Analytics has a built-in alerting system with the ability to integrate with several third-party monitoring systems. The productized, predefined alerts may also be reconfigured to meet exacting user requirements.
Studio Analytics provides multiple avenues through which external systems can consume data, including Kafka and pre-built plugins.
Studio Analytics has productized ML jobs for infrastructure and services monitoring. Automatically deployed ML jobs perform data analysis and anomaly detection of hosts and containerized services.
Studio Analytics enriches logs and metrics data with metadata for post-processing. The search engine feature, integral to the Studio Analytics platform, allows searching and correlating data.