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Fraud Detection With Cloudera Stream Processing Part 2: Real-Time Streaming Analytics

In part 1 of this blog we discussed how Cloudera DataFlow for the Public Cloud (CDF-PC), the universal data distribution service powered by Apache NiFi, can make it easy to acquire data from wherever it originates and move it efficiently to make it available to other applications in a streaming fashion.

5 Security Tips for Your GraphQL API

In 2015 GraphQL was created by Facebook as an alternative to REST APIs to give more power to frontend developers by making API calls more flexible. GraphQL achieves this goal by providing its API consumers with a query language that allows them to query just the data they need. While GraphQL can improve frontend developer experience, its specification doesn’t have opinions on security.

Three Industries That Rely On Microservices

With the ever-changing demands of business and new technologies, countless companies are ditching monolithic applications in favor of microservices applications. Monolithic application architectures can’t keep up with the consumer requests that microservices applications can. Read on to learn more about the benefits, and to discover which industries rely on microservices in their daily operations.

What Is a Data Pipeline and Why Your Ecommerce Business Needs One

Our six key points on data pipelines include: Whether you’re a one-person show reselling items on an online marketplace or a large Ecommerce enterprise with hundreds of employees, these businesses share a common factor: both generate data. The size of your business can influence the amount of data you generate, sure. But any amount of data — if it’s not adequately accessible — is worthless. Every business, especially an Ecommerce business, needs a data pipeline.

Kafka best practices: Monitoring and optimizing the performance of Kafka applications

Apache Kafka is an open-source distributed event streaming platform used by thousands of companies for high-performance data pipelines, streaming analytics, data integration, and mission-critical applications. Administrators, developers, and data engineers who use Kafka clusters struggle to understand what is happening in their Kafka implementations.