In this hands-on follow-up, we walk through the deployment of the NetApp DataOps Toolkit, MCP Server integration, and a LangGraph-powered chatbot to turn AI-driven storage automation into reality. ... View more

Introducing an agentic system built with the NetApp DataOps Toolkit and LangGraph Agent, bringing a new layer of intelligence to storage automation. Watch how AI agents simplify and orchestrate basic ONTAP operations through natural conversations. ... View more

Exciting news! Google Cloud NetApp Volumes Flex service level now supports block storage. In this blog, we will go through the steps required to provision and attach iSCSI storage to an Windows server from Google Cloud NetApp Volumes.  ... View more

Confidently deploy ONTAP tools for VMware vSphere 10.5 thanks to a whole host of new supportability enhancements, aimed at improving the end user experience, accelerating, and simplifying the support process. Unpack what’s new in this final installment of our three-part series. ... View more

Organizations are modernizing legacy Hadoop data platforms by migrating from HDFS-based Hive tables to Apache Iceberg on object storage, leveraging NetApp technologies for efficient, scalable, and resilient cloud-native architectures.   • Need for interoperable data solutions: Enterprises require data platforms that eliminate vendor lock-in, support multiple processing engines, and maintain a single data copy accessible via REST APIs to avoid duplication and streamline analytics.  • Challenges in Hadoop modernization: Key hurdles include strategic migration of petabytes of data, architectural shifts to Kubernetes-native workflows, decoupling of storage and compute, workload modernization, performance assurance, unified data access, disaster recovery, infrastructure upgrades, and resource contention management.  • Limitations of traditional Hive: Hive requires manual partition management, lacks ACID transaction support, needs downtime for schema evolution, suffers performance issues with small files, lacks time travel, and depends on manual maintenance and compaction.  • Advantages of Apache Iceberg: Iceberg offers automatic partition management, full ACID transactions, schema changes without downtime, optimized file layouts, time travel and rollback capabilities, and built-in maintenance operations.  • Iceberg’s superior performance: Metadata pruning, optimized file layouts, predicate pushdown, and vectorized operations enable faster query execution compared to Hive. Performance tests show Iceberg is 54-80% faster across various query types.  • NetApp’s data migration tools: The XCP tool facilitates data migration from HDFS to S3-compatible Iceberg storage with metadata integrity and minimal downtime, supporting both production and non-production environments. • Data access and resiliency technologies: FlexClone and FlexCache enable simultaneous multi-application data access with low storage overhead and improved read latency, while SnapMirror and MetroCluster provide asynchronous and synchronous replication for disaster recovery.  • Infrastructure enhancements: Upgrading to NetApp ONTAP AFF all-flash storage and StorageGRID supports high IOPS and low latency for analytics workloads, tenant isolation, and scalable object storage for Iceberg tables with features like snapshot views, isolated testing, and fast recovery.  • Industry adoption and benefits: Iceberg is widely used in banking, trading, brokerage, and research sectors, with NetApp solutions delivering advanced analytics, operational simplicity, and resilience that help enterprises move beyond legacy Hadoop systems.  ... View more