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Cloudera

Get to anomaly detection faster with Cloudera's Applied Machine Learning Prototypes

The Applied Machine Learning Prototype (AMP) for anomaly detection reduces implementation time by providing a reference model that you can build from. Built by Fast Forward Labs, and tested on AMD EYPC™ CPUs with Dell Technologies, this AMP enables data scientists across industries to truly practice predictive maintenance.

The Modern Data Lakehouse: An Architectural Innovation

Imagine having self-service access to all business data, anywhere it may be, and being able to explore it all at once. Imagine quickly answering burning business questions nearly instantly, without waiting for data to be found, shared, and ingested. Imagine independently discovering rich new business insights from both structured and unstructured data working together, without having to beg for data sets to be made available.

Kubernetes Logs Collection with MiNiFi C++

The MiNiFi C++ agent provides many features for collecting and processing data at the edge. All the strengths of MiNiFi C++ make it a perfect candidate for collecting logs of cloud native applications running on Kubernetes. This video explains how to use the MiNiFi C++ agent as a side-car pod or as a DaemonSet to collect logs from Kubernetes applications. It goes through many examples and demonstrations to get you started with your own deployments. Don’t hesitate to reach out to Cloudera to get more details and discuss further options and integrations with Edge Flow Manager.

Large Scale Industrialization Key to Open Source Innovation

We are now well into 2022 and the megatrends that drove the last decade in data—The Apache Software Foundation as a primary innovation vehicle for big data, the arrival of cloud computing, and the debut of cheap distributed storage—have now converged and offer clear patterns for competitive advantage for vendors and value for customers.

Modern Data Architecture for Telecommunications

In the wake of the disruption caused by the world’s turbulence over the past few years, the telecommunications industry has come out reasonably unscathed. There remain challenges in workforce management, particularly in call centers, and order backlogs for fiber broadband and other physical infrastructure are being worked through. But digital transformation programs are accelerating, services innovation around 5G is continuing apace, and results to the stock market have been robust.

Managing agents in Edge Flow Manager

This video explains the Agent Manager view introduced with the 1.4 release. The main goal of this view was to give the user better understanding and more control over the agents in the system. Monitoring individual agents’ health becomes easier as you can see rich details about them. From the Agent Details view, you can also request and download debug logs from the agents, so in case of any issues you don’t need to log in to the agent’s environment. The highly customizable main table and the different tabs (details, alerts, commands and properties) are explained in detail.

Five Reasons for Migrating HBase Applications to Cloudera Operational Database in the Public Cloud

Apache HBase has long been the database of choice for business-critical applications across industries. This is primarily because HBase provides unmatched scale, performance, and fault-tolerance that few other databases can come close to. Think petabytes of data spread across trillions of rows, ready for consumption in real-time.

Breaking State and Local Data Silos with Modern Data Architectures

Data is the fuel that drives government, enables transparency, and powers citizen services. But while state and local governments seek to improve policies, decision making, and the services constituents rely upon, data silos create accessibility and sharing challenges that hinder public sector agencies from transforming their data into a strategic asset and leveraging it for the common good.

Incremental Strategies to Move Your Data Strategy Forward

Firms are burdened with tech debt and endless regulatory compliance, often leaving innovation last to receive the necessary budgets. Data-fuelled innovation requires a pragmatic strategy. This blog lays out some steps to help you incrementally advance efforts to be a more data-driven, customer-centric organization.