What's New @ Cloudera

Find the latest Cloudera product news

COD now provides a CLI option to enable HBase region canaries while creating an operational database.

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COD now allows you to create an operational database using a Data Lake template.

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COD supports configuring JWT authentication for HBase clients.

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With the launch of CDP Public Cloud 7.2.16, Cloudera Streaming Analytics for Data Hub deployments has gotten some powerful new features! In this release, the Streaming Analytics templates in Data Hub will come with Apache Flink 1.15.1, a completely rebuilt SQL Stream Builder UI, support for Software Development Lifecycle projects with direct integrations to GitHub, support for Iceberg data format, Job Notifications, and more.

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COD supports to create or update database using a custom image to adhere to the security compliances and meet other necessary requirements. 

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COD now supports managing edge nodes through COD CLI options thereby reducing the dependency of Cloudera Manager

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COD now allows you to disable Kerberos authentication using COD CLI while creating a operational database.

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CDP Operational Database (COD) provides a CldrCopyTable utility that copies tables across Kerberos realms without cross-realm Kerberos trust.

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Cloudera just released CFM 2.1.5 which brings the best of Apache NiFi on both CDP 7.1.7 and 7.1.8. Cloudera Flow Management 2.1.5 is based on NiFi 1.18 and brings a lot of improvements and net new features.

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This release (2.3.0-b347) of Cloudera DataFlow (CDF) on CDP Public Cloud introduces the technical preview of Flow Designer, adds several new ReadyFlows, improves upgrade reliability and fixes issues with stability for clusters with high utilization.

 

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PBJ Workbench Runtimes are GA, rebased on Jupyter for ecosystem compatibility and openness.

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CML Experiments have been rebuilt, leveraging the MLflow ecosystem to complement CML’s existing strengths in model development and deployment. CML now ships the mlflow SDK and an integrated visual experience that enables experiment tracking and comparison via flexible visuals. 

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COD now provides two new CDP CLI commands to update and retrieve HBase configuration values.

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COD now deploys strong meta servers for multiple regions for Multi-AZ deployments

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Cloudera Employee

COD now supports SSD volume types for gateway nodes of HEAVY types.

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As businesses continue to adopt and build open lakehouses built with Apache Iceberg on CDP, data scientists need easy access to these new table formats, so they don’t spend their time figuring out connection dependencies and configurations.

 

Cloudera Machine Learning’s Data Connection and Snippet support simplify data access in CDP. Data scientists can use the cml.data library to gain access to a Data Lake via Spark or query their Virtual Warehouse with Hive or Impala. With recent improvements to the cml.data library, CML Snippets now fully support the Iceberg table format for all Spark, Hive, and Impala data connections. 


To learn more about Data Connection and Snippet read the following article:
https://blog.cloudera.com/one-line-away-from-your-data/

Rising Star

Cloudera Machine Learning now provides a built-in dashboard for monitoring technical metrics relating to deployed CML Models, such as request throughput, latency, and resource consumption.

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CDP now supports SCIM for Azure Active Directory.

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The latest release (2.2.0-b194) of Cloudera DataFlow (CDF) on CDP Public Cloud improves the first time user experience, introduces more ReadyFlows, and supports renewing certificates for Inbound Connection.

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COD now displays alerting notifications on the COD UI for all the key events.

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COD allows you to modify the EBS volumes for HDFS clusters while creating a database.

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CML's Backup and Restore feature is now generally available in the public cloud on AWS. Administrators can backup their CML Workspaces and ensure business continuity in case of failures and outages. 

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We are happy to announce the latest release of Cloudera Data Engineering for the Public Cloud.

Starting this release, CDE will now support in-place upgrades in Tech Preview (TP) alleviating the need to delete and recreate the entire service.  Please reach out to your account team if you want to participate in the TP program.  Additionally, stability and performance improvements increase the deployment scale of the managed Airflow service.

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CML gives new controls for Administrators to disable certain ML Runtime variants or specific versions

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The latest release (2.1.0-b123) of Cloudera DataFlow (CDF) on CDP Public Cloud introduces support for DataFlow service upgrades as a technical preview feature, Inbound Connection configuration through the create-deployment CLI command, Kubernetes 1.22 as well as additional improvements and fixes.

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COD now supports CDP Control Plane for eu-1 (Germany) and ap-1 (Australia) regions.
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CDP Operational Database (COD) ensures high availability and fault tolerance using Multi-AZ deployments.
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Store File Tracking (SFT) is available as a general availability feature delivered through the Cloudera Operational Database (COD) service.

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Data scientists on CML Workspaces have access to GPUs to accelerate their machine learning projects and reduce the time it takes to build and train predictive models. NVIDIA GPU nodes are available for administrators to configure for CML Workspaces in both AWS and Azure.

 

CML now supports adding new GPU nodes to existing CML Workspaces created without GPUs, so data scientists can access GPU acceleration without having to recreate CML Workspaces. Administrators can also replace GPU nodes in CML Workspaces to switch to the latest generation GPUs.

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With these new capabilities, it's easier for administrators to manage GPU nodes in CML Workspaces and enable data scientists to use the newest generation of GPUs. 

The Data Discovery and Visualization experience ships with preconfigured Data Connections, a database browser, interactive SQL editor, drag-and-drop Visual Dashboarding, and Connection Snippets. These new capabilities speed up the development process by cutting down the time spent finding, exploring, understanding, and accessing the data.

 

Data Scientists need to fully understand their data in order to analyze it properly, build models, and power ML use cases. To reduce the time to insights, CML ships all tools required to integrate these tools to reduce the friction between the different steps and to speed up the development process for data science teams.

 

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These new capabilities are built on top of Cloudera Data Visualization, giving state-of-the-art visual capabilities at the hand of Data Scientists. To get started, you can step into any Project in a CML May or newer Workspace and hit the Data tab.

 

You can read more about the new capabilities in the documentation here.