Cloudera Edge Management
Manage, control, and monitor data collection and processing at the edge, ensuring edge data is ready for real-time AI applications.
OVERVIEW
Data access and control designed for AI at the edge
Cloudera Edge Management enhances AI and other data applications with real-time data using advanced functionality and accessible low-code tools.
Achieve seamless data collection and processing at the edge using a lightweight edge agent.
Manage the entire edge flow lifecycle—including authorship, deployment, and monitoring—from a single hub.
Design and execute edge device data flows with accessible low-code authorship tools.
USE CASES
Address streaming and IoT challenges.
Ingest, capture, and deliver data in real time from any streaming source—including clickstreams, social media, mobile, and IoT devices—to build AI applications and scale operations.
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Predictive maintenance
Lower costs and reduce downtime with earlier issue detection and resolution.
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Fraud detection
Identify potential security risks earlier and protect against losses.
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Cybersecurity
Build pipelines using edge data to improve cybersecurity.
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Predictive maintenance
Lower costs and reduce downtime with earlier issue detection and resolution.
-
Fraud detection
Identify potential security risks earlier and protect against losses.
-
Cybersecurity
Build pipelines using edge data to improve cybersecurity.
Modernize, simplify, and accelerate data ingestion and processing from hundreds of connected edge assets.
Analyze IoT and sensor data to predict asset failure, detect variances, and understand warning signals—critical for transportation and manufacturing.
Use edge data to train AI models that analyze patterns and flag deviations.
Enable insights and actions on edge data as it’s generated, enhancing SIEM—especially critical in industries like financial services.
Cloudera SDX provides a unified framework, enhancing security and governance of pipelines.
Process log data from thousands of servers and edge devices to make more informed business decisions that are immediately actionable.
Hundreds of prebuilt processors enable easy connection with a range of data sources, devices, and protocols. An intuitive, drag-and-drop UI lets you build sophisticated data flow pipelines with ease.
Lightweight Apache NiFi agents provide data collection and processing at the edge: MiNiFi Java agents for full capabilities of Apache NiFi and MiNiFi C++ for very low footprint agents.
Provides a low-code experience for designing, deploying, and monitoring edge flow applications using NiFi’s 450+ processors and a custom-build dashboard. Acts as the single management layer for all edge agents.
Handle any throughput: Move petabytes of data in just a few hours from data center to cloud or vice versa. Enable a multi-cloud model with a cloud-vendor-agnostic approach to managing data.
Adopt a DevOps-style data flow lifecycle with NiFi Registry: Enable dev teams to version data flows, set up promotion schemes across environments, deliver applications faster, and so on.
Enable edge-to-AI data processing at scale: Command, control, and monitor thousands of agents; minimal footprint to collect, filter, and process data; and end-to-end machine learning algorithms with automated learning loops.
Customers
Edge Management drives real value across industries.
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