What is Edge Management?
Cloudera Edge Management (CEM) manages, controls, and monitors data collection and processing at the edge with a low code authorship experience addressing data management challenges with streaming and IoT use cases.
It provides two categories of capabilities:
Edge Data Collection: MiNiFi is a lightweight edge agent that implements the core features of Apache NiFi, focusing on data collection and processing at the edge. The MiNiFi agents come in two flavors: MiNiFi Java agents for full capabilities of Apache NiFi and MiNiFi C++ for very low footprint agents
Edge Flow Management: Edge Flow Manager is an agent management hub that provides a low-code experience for designing, deploying, and monitoring edge flow applications on thousands of MiNiFi agents. It also acts as the single management and monitoring layer for all the MiNiFi agents deployed at the edge. EFM supports the entire edge flow lifecycle including authorship, deployment, and monitoring
These capabilities address IoT use cases such as predictive maintenance, fleet management, and asset tracking. The MiNiFi agents are also widely used in cybersecurity logs collection use cases to collect logs in real time across an infinite number of devices, servers, laptops, and so on, as well as a modern solution to collect logs from cloud-native applications running on Kubernetes.
Lower costs and reduce downtime with predictive maintenance.
Predictive Maintenance is a data-driven approach to analyze IoT and sensor data from connected equipment to effectively predict when and how an asset might fail, detect variances, understand warning signals, and quickly identify patterns that might indicate a potential breakdown. Cloudera DataFlow’s Edge Management capabilities modernize and simplify data ingestion from hundreds of connected assets to enhance predictive maintenance.
Capture real-time feeds from patient-monitoring devices to detect anomalies.
Biometric and telemetric devices are used in healthcare organizations to monitor post-surgery or high-risk patients. Ingesting sensor data from these devices about various patient vitals helps detect abnormalities or concerning patterns. Cloudera Edge Management helps capture patient-monitoring data and delivers them to stream-processing engines for insights.
Connect, integrate, and move massive volumes of data across hybrid and multi-cloud environments.
Traditional ETL processes are for use cases where data must move from one database to another. Modern enterprises transfer data from on-premises to cloud or cloud-to-cloud, moving petabytes of information in a matter of just hours.