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.

This video covers the security aspects of Edge Flow Manager (EFM). It shows the differences between an admin and a regular user. The important thing to note is that authorization is based on Agent Classes so if a user has no defined policy on a particular Agent Class, then the user won’t see any class / agent / event information that belongs to such a class. For convenience users can be grouped so permissions can be inherited from pre-defined groups.

Watch this quick demo to learn how CDP One can help you build an end-to-end data and analytics workflow with the first all-in-one lakehouse for fast and easy analytics.

Hear from Cloudera CTO Ram Venkatesh about the announcement of CDP One, Cloudera's new all-in-one data lakehouse for fast and easy analytics.

Data analytics is a big deal, with big goals, and even bigger transformation. Unlocking that potential often requires big complex projects, big teams, and big budgets. Introducing Cloudera Data Platform One or CDP One. An all in one cloud service that radically simplifies the entire data lifecycle from ingestion to analysis while delivering the power of an enterprise data platform with the simplicity of a turnkey solution. CDP One integrates with all your existing tools, bringing all your siloed data together in an open data lake house without the need for specialized ops and cloud expertize.

You have so much data. It's time to put it to work. Learn all of the benefits you can realize with an effective big data strategy at cloudera.com

This video shows how Cloudera DataFlow powered by Apache NiFi solves the first-mile problem by making it easy and efficient to acquire, transform, and move data so that we can enable streaming analytics use cases with very little effort. It will also briefly discuss the advantages of running this flow in a cloud-native Kubernetes deployment of Cloudera DataFlow. Then, we will explore how we can run real-time streaming analytics using Apache Flink, and we will use Cloudera SQL Stream Builder GUI to easily create streaming jobs using only SQL language (no Java/Scala coding required).

Applied Machine Learning Prototypes (AMPs) are open source projects that will fundamentally change the way data scientists build, deploy, and monitor ML models. These fully-developed prototypes are built around common industry use cases — like Churn Prediction Monitoring, Anomaly Detection, and more — and can be customized to give you significant head start. Available in Cloudera Machine Learning, AMPs are tested, trusted, and research backed by Fast Forward Labs.

This video explains Edge Flow Manager (EFM) integration with Prometheus and Grafana. After installing and configuring Prometheus to scrape, EFM should also be configured to expose metrics. When the time series are in place, Grafana is also installed and configured to visualize exposed metrics. There are some EFM specific Grafana dashboards that are publicly available that can be easily downloaded and imported to Grafana. When everything is configured correctly agent specific dashboards can be accessed from the EFM UI.

Data is more than ones and zeroes. If you can put it to work, data has the power to transform your entire company, even your entire industry. With more than 2000 customers in over 85 countries, Cloudera is helping companies across industries generate more revenue, build new products and understand their customers at scale and speed.