Announcements

The Data In Motion Team is pleased to announce the release of Cloudera Data Flow 3.2 for Cloudera on cloud.In this release, we’ve focused on major architectural modernization and eliminating friction across the development lifecycle. By introducing zero-touch, cross-cluster authentication, smarter cloud resource management, and a massive upgrade to our underlying infrastructure, we are delivering a more resilient, secure, and intuitive Cloudera Data Flow.Release Highlights:Frictionless Cross-Cluster Communication: We introduced DefaultNodeSSLContextService. This allows you to seamlessly send data from one NiFi cluster (deployment or test session) to another within the same Cloudera Data Flow environment, completely removing the overhead of manually managing and rotating certificates.Optimized Parameter Groups in Drafts: Drafts that import Shared Parameter Groups benefit from dramatically improved performance, timeout resilience, and reliability when managing parameters at scale.Primary

Important Timeline Update: Read-Only Mode Started on September 21 Evolving the Cloudera Community What to Expect in Our Upcoming Upgrade The Cloudera Community runs on your expertise: the questions you ask, the solutions you share, and the knowledge you pass along to the next person stuck on the same problem. To give that collaboration a stronger foundation, we're upgrading to a new community platform. This upgrade comes down to three things: helping you find answers faster, making it easier to share solutions, and giving you clearer recognition for what you contribute. Here's what's changing, when it's happening, and what to expect on the other side. Important Timeline Update: Read-Only Mode Started on September 21 To safely carry every post, reply, and accepted solution into the new environment, the Community will enter a temporary read-only mode starting September 21.       What this means for you: You can still search, browse, and read every existing discussion and

The Data In Motion Team is pleased to announce the release of Cloudera Flow Management Operator for Kubernetes version 3.3. This release focuses on improving security, streamlining deployments, and enhancing upgrade paths. The core highlights include first-class Apache Ranger authorization, seamless inter-cluster communication, declarative flow deployments, and rolling upgrades for NiFi 2 clusters.Release Highlights:Unified Security Governance Across NiFi Clusters: Centralized, policy-based access control for Operator-Managed NiFi clusters is now possible by integrating customer-managed Apache Ranger with the Cloudera Flow Management Operator for Kubernetes. Automated, Secure Cross-Cluster Communication: The Operator now automatically provisions SSL context services using existing node keystores and truststores, eliminating manual TLS configuration for secure cluster-to-cluster data movement.Zero-Downtime Rolling Upgrades for NiFi 2: Upgrade between NiFi 2 versions smoothly withou

Cloudera’s Data In Motion Team is pleased to announce the release of the Cloudera Streams Messaging Operator for Kubernetes v1.7. This milestone release centers on a major platform update to Strimzi 1.0.1 and Apache Kafka 4.2.0, mandatory API standardization, high-availability maintenance tooling with Strimzi Drain Cleaner, refined Kafka configuration controls, and a redesigned Cloudera Surveyor experience.Release HighlightsRebase to Strimzi 1.0.1 and Kafka 4.2.0This release updates the Operator to Strimzi 1.0.1 (up from 0.49.1) and Apache Kafka 4.2.0 (up from 4.1.1). This upgrade delivers upstream enhancements, including per-listener Kafka configurations, advertised port templates for predictable external broker port mapping, environment variable-based rack awareness without requiring ClusterRoleBindings, and on-demand KafkaUser certificate renewal via annotations.Strimzi v1 API EnforcementThe v1 API  is now the sole supported API version for all Strimzi Custom Resource Definitio

Here are some highlights from the month of June Upcoming Events Read Here Watch Now Community Authors Leaderboard @MattWho @9een @upadhyayk04 @tnair @RAGHUY     

Here are some highlights from the month of May Upcoming Events Read Here Register Here Community Authors Leaderboard  @MattWho @RAGHUY @vafs @ganzuoni @AlokKumar  Community Unanswered Questions  

Bridging the Visibility Gap for Legacy and Niche SystemsWhile Cloudera Data Lineage  provides native harvesting for various BI systems, many organizations rely on niche, homegrown, or legacy tools that aren't covered by our standard support. To bridge this gap, we previously offered the "Universal Connector," enabling users to import lineage from ETL tools, reports, or databases using CSV templates.However, a significant hurdle remained: while SQL scripts power many processes and reports, users were forced to manually define every source column and its associated logic. Furthermore, the platform lacked a way to represent the actual scripts or the specific logic they contained.The Solution: Custom Lineage ConnectorThe latest update to this capability introduces the ability to include Source SQL scripts directly within CSV files. This update allows direct injections of source SQL queries for databases, ETL/ELT tools, and BI tools via CSV. To emphasize this new flexibility and acknow

The Data In Motion Team is pleased to announce the release of Cloudera Flow Management Operator for Kubernetes version 3.1. This release introduces powerful new security and automation features, focusing on programmatic identity and access management, automated certificate generation, and intelligent cluster lifecycle enhancements that significantly reduce admin overhead and streamline user onboarding.Release Highlights:Programmatic User Group Management via UserGroup Custom Resource Definition (CRD): This new CRD enables admins to configure NiFi user groups directly in YAML. By managing user groups as code within the Kubernetes environment, it streamlines the organization of users, reduces manual configuration, and ensures consistent group management across clusters, significantly improving overall admin efficiency.Streamlined Access Control with AccessPolicyProfile CRD: This new CRD allows admins to define sets of access policies and roles for users programmatically. By consolidating

The Data In Motion Team is pleased to announce the release of Cloudera Data Flow 3.1 for Cloudera on cloud.In this release, we’ve focused on removing some friction that slows teams down. By introducing command line interface (CLI) automations and advanced debugging tools, we’re giving developers more visibility and admins more control. These efficiency gains are backed by a leaner, more performant Flow Designer and a hardened foundation that stays ahead of evolving security standards.Release Highlights:Command-Line Test Session Management: Users can now manage Flow Designer test sessions via the CLI. This update enables seamless automation of test session  workflows, eliminating repetitive manual steps in the UI.Streamlined Parameter Orchestration: We’ve extended full CLI support to Shared Parameter Groups, including the ability to reference them by CRN. By removing the need for exhaustive group details during CLI deployment and enabling full Create, Read, Update, Delete (CRUD) op

Here are some highlights from the month of April Upcoming Events Read Here Register Here Community Authors Leaderboard @MattWho @vafs @nshetty @snm1523 @s-raju @grimcha @nisaar  Community Unanswered Questions

This update allows organizations to move beyond reactive troubleshooting by providing a live, continuous pulse of their data ecosystem. By delivering instant visibility into infrastructure, services, and active workloads, RTM ensures that your platform remains healthy, performant, and reliable.Eliminate Blind Spots with Proactive VisibilityIn high-scale data environments, even a few minutes of downtime or a runaway query can derail critical business operations. RTM addresses this by monitoring three core areas:Cluster Infrastructure: Track the health of your underlying hardware and cloud resources (e.g., CPU, memory, and disk I/O) to spot resource exhaustion before it triggers a crash.Service Health: Monitor the uptime and performance of vital services like Hive, Impala, and Spark in real time.Workload Performance: Identify failing jobs or deviating queries as they happen, allowing for immediate intervention to prevent cascading failures across the cluster.Key Benefits:Proactive Mitiga

Cloudera’s Data In Motion team is pleased to announce the release of Cloudera Streaming Analytics 1.17.0 for on-premises deployments. This release focuses on enterprise-grade stability, enhanced security protocols for Kafka integration, and a modernized approach to extensibility through Python.Release HighlightsJava Upgrade to JDK 17CSA 1.17.0 is now built and verified using JDK 17, providing better performance and long-term support for modern Java applications.Proactive Vulnerability ManagementThis release includes extensive core dependency upgrades specifically targeted at resolving CVEs, ensuring your production streaming pipelines remain secure and compliant.Enhanced Kafka Data Source ConfigurationsStreaming data pipelines require precision. Cloudera Streaming Analytics 1.17.0 now allows users to specify custom properties for Kafka connections directly within the Kafka Data Source form. Furthermore, we have introduced explicit support for JKS, PKCS12, and BCFKS truststore and keyst

We are evolving our community content to ensure you always find the most relevant and up-to-date information, particularly as search and AI-driven tools become central to finding answers. What We Did: A large number of older posts, primarily from 2019 and earlier, have been moved to a read-only archive. These posts are no longer open for new replies, and they have been removed from standard community search and navigation to prioritize current discussions. Why We Did It: As our community has grown, older content sometimes surfaced with outdated product information or contains broken links. This archiving ensures that active discussions accurately reflect today’s products and workflows, addressing challenges like legacy threads competing with new conversations for visibility. How It Benefits You: By prioritizing recent and relevant content, we enable better, more accurate discovery. This strategic change ensures that both community search and external AI-powered tools are guided to the

Hello Community! We recently updated a few community labels to align with the new product naming conventions (largely removing abbreviations) to better align with changes at the organizational level. This is part of an effort to make our product portfolio clearer, more consistent, and easier to navigate—whether you're exploring features, searching for help, or engaging in discussions here in the community. Why the change? As our products evolve, it’s important that their names reflect what they do and how they fit into the bigger picture. These updates help us: Create a more unified product experience Reduce confusion across documentation and support channels Make it easier for you to find the right information quickly You might have noticed some unexpected notifications related to these updates in the community. Due to the label changes tied to product renaming, some subscription notifications were unintentionally triggered. We’re really sorry for the confusion this may have ca

Native Governance and Data Lineage for the Unified Data FabricThe Cloudera Data Lineage team is happy to announce that Cloudera Data Lineage now supports Trino federated query engine for big data.This integration allows Trino users to access data wherever it lives without sacrificing governance, trust, or visibility.As modern enterprises navigate increasingly complex, hybrid, and multi-cloud environments, data often becomes fragmented across various systems and silos. Combining the federated query engine of Trino with the automated lineage of Cloudera Data Lineage provides organizations with unprecedented insight and  visibility.Here are the primary benefits and use cases that the  integration of Cloudera Data Lineage with Trino provides:Interoperability and Federated Access: Cloudera Data Lineage's newly released Trino integration enables customers to federate queries and securely access data from both Cloudera and non-Cloudera engines. This capability allows organizations t

Cloudera’s Data In Motion Team is pleased to announce the release of the Cloudera Streaming Analytics Operator for Kubernetes v1.5. This release advances our cloud-native streaming capabilities by introducing the Materialized View engine to Kubernetes, optimizing job handling responsiveness, and updating core infrastructure components for better performance and security.Release HighlightsMaterialized View Engine on Kubernetes Cloudera SQL Stream Builder now supports the Materialized View (MV) engine within Kubernetes deployments. This allows users to create and maintain mutating snapshots of queried data, which can be seamlessly accessed via REST APIs, bridging the gap between real-time streams and request-response applications.Asynchronous Flink Job Handling To improve the user experience, SQL Stream Builder now handles Flink jobs asynchronously. This architectural change significantly enhances the responsiveness of the Streaming SQL Console and ensures more stable job statu

We are thrilled to announce the general availability of Cloudera Data Services On Premises 1.5.5 Service Pack 2 (SP2)!This release is packed with massive updates designed to accelerate your AI journey, boost your analytics performance, and lock down your on-premises data environments. Whether you want to deploy LLMs securely or speed up your SQL queries, 1.5.5 SP2 brings the capabilities you need to modernize your data ecosystem.💥 Release HighlightsDeploy Private GenAI at Scale: Powered by NVIDIA, Cloudera AI Inference is now Generally Available (GA). You can now securely deploy and scale private GenAI applications directly behind your firewall, maintaining strict 100% data sovereignty.Blazing-Fast SQL with Trino: Trino is now fully GA within Cloudera Data Warehouse! Take advantage of highly efficient, federated distributed SQL querying across your entire data estate.Enhanced Observability: Say goodbye to operational blind spots. Faster troubleshooting is now possible via full, n

Release HighlightsRebase to Strimzi 0.49.1 and Kafka 4.1.1This release of the Operator is now based on Strimzi 0.49.1 (up from 0.47.0) and Apache Kafka 4.1.1 (up from 4.0.1). This rebase brings the latest performance optimizations and feature sets from the upstream community, ensuring your streaming infrastructure remains at the cutting edge.Introduction of Cloudera Schema RegistryNew in version 1.6, Schema Registry is now available as a standalone application that allows you to efficiently store and manage schemas for your streaming data. It supports Avro and JSON schema formats, and provides schema evolution capabilities with configurable compatibility modes. Schema Registry helps ensure data consistency across your streaming applications by providing a central repository of schemas that applications use to validate their data. It provides a REST API and client libraries for programmatic access.Apache Iceberg Sink Connector CertificationTo empower modern data lakehouse architectures,

Here are some highlights from the month of December 68 new support questions 2863 new members       WEBINAR The Future of Agents with Private AI   Watch Now       WEBINAR A Leader's Fireside Chat about Securing Next-Gen AI Watch Now Check out the FY26 Cloudera Meetup Events Calendar for upcoming & past event details!   We would like to recognize the below community members and employees for their efforts over the last month to provide community solutions.  See all our top participants at Top Solution Authors leaderboard and all the other leaderboards on our Leaderboards and Badges page.     @MattWho @vafs @venkatsambath @pajoshi @upadhyayk04 @Pedro_E @Bern @blackboks @zzzz77    Share your expertise and answer some of the below open questions. Also, be sure to bookmark the unanswered question page to find additional open questions.  U

Our goal is to provide a seamless, high-performance environment that bridges the gap between raw data and actionable insights. By integrating AI-driven SQL conversion and strengthening our connector suite, we are empowering teams to work faster, more securely, and with greater visibility across the entire data lifecycle.To better align with Cloudera’s suite of solutions, the Octopai convention and reference will now be labelled Cloudera Data Lineage. All materials referencing Cloudera Data Lineage relate to what was formerly Octopai.New FeaturesThis release focuses on three core pillars: advanced cloud-data integration, enterprise-grade security, and robust pipeline connectivity.Enterprise-Grade AuthenticationThe following releases prioritize support for Cloudera authentication protocols.Spark Lineage + Kerberos Authentication Support – Secure your Spark lineage leveraging secure integration with industry-standard Kerberos authentication.Secure Hive & Impala Kerberos Integration –

Here are some highlights from the month of November 42 new support questions 2124 new members WEBINAR2026 Trends in Data and AIDate: January 14, 2026 Time: 8:00 am PT | 11:00 am ET | 1600 GMTRegister Now     WEBINARThe Future of Agents with Private AI  Watch Now Check out the FY25 Cloudera Meetup Events Calendar for upcoming & past event details!   We would like to recognize the below community members and employees for their efforts over the last month to provide community solutions.  See all our top participants at Top Solution Authors leaderboard and all the other leaderboards on our Leaderboards and Badges page.   @MattWho @vafs @BFBounteous @akuser @PeterKa @casaui @Jaguar    Share your expertise and answer some of the below open questions. Also, be sure to bookmark the unanswered question page to find additional open questions.  Unanswered Community Post  C

We are thrilled to announce the launch of a brand-new Blogs section on the Cloudera Community! This new section is your dedicated home for deeply technical insights and practical content, featuring contributions from Cloudera experts and the broader data community. We've organized the content into two distinct and valuable tracks: Developer Blogs These blogs are written for developers, including Data Engineers, Software Engineers, Architects, and ML/AI Engineers. What to expect: A focus on real-world use cases, practical workflows, and conceptual explanations that help you master the Cloudera product stack and the foundational open source technologies that power it. Key Technologies: Explore practical examples using technologies such as Apache Iceberg, Apache Spark, Apache Kafka, Apache NiFi, Apache Flink, Trino, Apache Ozone, and more. Learn exactly how these technologies are applied to solve a wide range of complex data problems. Engineering Blogs These posts provide in

Here are some highlights from the month of September & October  130 new support questions 9 new community articles 4031 new members WEBINAR2026 Trends in Data and AIDate: January 14, 2026 Time: 8:00 am PT | 11:00 am ET | 1600 GMTRegister Now Check out the FY25 Cloudera Meetup Events Calendar for upcoming & past event details! Community Article Author Components/ Labels Cloudera Flow Management / Apache NiFi Best Practices Cookbook Matthew Burgess  @mburgess  Apache NiFiCloudera DataFlow (CDF) Flow Analysis Rules (enforcing Best Practices in Flow Design) Parameterize All The Things! (part 1 - Parameters and Parameter Contexts)  Parameterize All The Things! (part 2 - Parameterizing Controller Service References) Parameterize All The Things! (part 3 - Parameter Providers) User Limit Factor and Minimum User Limit Percentage for a Specific Queue Ayaz Hussain@AyazHussain  Apache YARN Java Garbage Collection changes

Cloudera’s Data In Motion Team is pleased to announce the release of the Cloudera Streaming Analytics - Kubernetes Operator 1.4. This release focuses on modernization through Flink and Flink Operator rebases, enhancing security with FIPS compliance, and improving developer productivity by enabling Python UDFs by default.Release HighlightsRebase to Flink Operator 1.11 and Apache Flink 1.20This release of the Operator is now based on the Apache Flink Kubernetes Operator 1.11 and Apache Flink 1.20. These rebases bring the latest features, performance optimizations, and stability fixes from the upstream communities, ensuring your streaming workloads benefit from the newest advancements in high-performance stream processing.FIPS Mode Support To meet the strictest security and compliance requirements, the Cloudera Streaming Analytics - Kubernetes Operator can now be configured and deployed in Federal Information Processing Standards (FIPS) mode. This ensures that your deployment utilize

Cloudera’s Data In Motion Team is pleased to announce the release of the Cloudera Streams Messaging - Kubernetes Operator 1.5. This release centers on modernization, adopting the latest Kafka standards, enhancing security, and significantly improving the usability of the Cloudera Surveyor management tool.Release HighlightsRebase to Strimzi 0.47.0 and Kafka 4.0.1This release of the Operator is now based on Strimzi 0.47.0 (up from 0.45.0) and Apache Kafka 4.0.1 (up from 3.9.0). These rebases bring the latest features, performance optimizations, and stability fixes from the upstream communities.FIPS 140-2/3 Compatibility and ComplianceTo meet the strictest security requirements, Cloudera Streams Messaging - Kubernetes Operator components are now FIPS 140-2/3 compliant. The core Operator and its managed components will automatically enable FIPS mode on FIPS-enabled hosts.Cloudera Surveyor is also FIPS compliant, though it requires you to manually enable FIPS mode through configuration. Sur