Times are tight across technology teams and organizations everywhere. Companies are looking to optimize cloud and tech spend, and being incredibly thoughtful about which priorities get assigned precious engineering and operations resources. “Build vs. Buy” is being taken seriously again. And if we’re honest, this probably makes sense. There is a lot to optimize.
Join the upcoming Data Discovery Blueprint series hosted by Confluent. These sessions will help your team move faster and optimize their cloud deployments.
The sessions:
WATCH ON DEMAND : Enabling Production Workloads with Private Networking Connectivity
WATCH ON DEMAND : Maximize Streaming Data Quality with Stream Governance Advanced
WATCH ON DEMAND : Apache Flink SQL on Confluent Cloud
WATCH ON DEMAND : Enabling Cluster Linking on Confluent Cloud
The business value of streaming applications is often about connecting, processing, and distributing data that is located across clouds, regions, and networks. This talk discusses secure scalable network patterns in Confluent Cloud that provide golden paths for onboarding applications.
Key Takeaways:
-Discover the options available to connect workloads to Confluent Cloud using private connectivity
-Evaluate the options through the lens of cost, security, and performance
-Operationalize the deployment of selected option
Presenter:
Sudarshan Pathalam, Staff Product Manager
Confluent
Join to learn how to ensure high data quality, discoverability, and compatibility for your real-time data streams on Confluent Cloud using the latest Stream Governance capabilities.
With its recently expanded suite of features on Confluent Cloud, Stream Governance enables you and your team to innovate faster without bypassing controls for data quality or compliance.
Confluent’s Stream Governance product team will showcase how to deliver real-time, trusted data streams to downstream consumers while remaining compliant within an ever-evolving landscape of data regulations, including how to:
-Enforce data integrity and compatibility, quickly resolve data quality issues, and simplify schema evolution with Data Quality Rules in Schema Registry
-Enhance data discovery within your streaming catalog with user-generated business context and easy, declarative search via GraphQL API
-Simplify comprehension and troubleshooting of complex data streams with lineage search and historical point-in-time insights in Stream Lineage
Presenters:
Olivia Greene, Sr. Product Marketing Manager
David Araujo, Sr. Product Manager - Data Governance
Confluent
Are you using Apache Kafka® to stream data? Running Confluent Cloud? Building real-time systems?
Join Flink committer Timo Walther as he shows you how to process Kafka data with Apache Flink SQL.
Many of the largest real-time systems in the world use Flink to make streaming data stateful and to analyze it with Flink SQL and other powerful Flink APIs. We hope you can join us to learn about state-of-the-art stream processing development, including:
-Apache Flink SQL overview
-When and why to use Flink SQL and Kafka together
-Apache Flink SQL use case examples
-Real-time aggregations, pattern matching, and analytics
-Streaming batch processing
-Apache Flink for Confluent Cloud—easiest way to get started with Flink SQL
-Demo: How to use Flink SQL on the Confluent Cloud to process Kafka data in real time
Presenter:
Timo Walther, Flink Committer
Principal Software Developer
Confluent
Cluster Linking on Confluent Cloud is a fully managed service for replicating data from one Confluent cluster to another. Programmatically, it creates perfect copies of your topics and keeps data in sync across clusters. Join this session to learn why Cluster Linking is a powerful geo-replication technology for:
-Multicloud and global architectures powered by real-time data in motion
-Data sharing between different teams, lines of business, or organizations
-High availability (HA)/Disaster recovery (DR) during an outage of a cloud provider’s region
-Data and workload migration from a Apache Kafka® cluster to Confluent Cloud or Confluent Platform cluster to Confluent Cloud
-Protect Tier 1, customer-facing applications and workloads from disruption by creating a read-replica cluster for lower-priority applications and workloads
-Hybrid cloud architectures that supply real-time data to applications across on-premises datacenters and the cloud
Learn how Cluster Linking reduces operational burden and cloud egress fees, while improving the performance and reliability of your cloud data pipelines.
Presenter:
Luke Knepper, Senior Product Manager
Confluent
David is a product manager for Data Governance at Confluent. An engineer turned product manager, over the years he has worked across multiple industries and continents, mostly in the data management and strategy space. He holds a master’s and bachelor’s degree in computer science from the University of Evora in Portugal.
Luke is a Product Manager at Confluent for Kafka’s geo-replication tools (Cluster Linking, Multi-Region Clusters, and Apache Kafka® MirrorMaker 2). Over the past four years, he’s helped hundreds of enterprise companies reach success with multi-region / multicloud / hybrid cloud data streaming. Previously, Luke was a software engineer and engineering manager. He has a bachelor's degree in computer science and an MBA, both from Stanford.
Sudarshan is a Staff Product Manager at Confluent who tackles issues that involve the convergence of data, cloud, and network. It has been a remarkable experience for him to create and implement solutions for diverse customer groups and assist them in effectively applying these solutions to their specific needs. Prior to joining Confluent, he worked at various software startups, as well as Brocade and Cisco, where his focus was on areas such as in-memory file systems, software-defined networking, data center fabrics, virtualization, and network architecture.
Timo is a Principal Software Developer at Confluent. He is a long-term committer and PMC member of the Apache Flink project. He studied computer science at TU Berlin. Alongside his studies, he participated in the Database Systems and Information Management Group there and worked at IBM Germany. Timo is currently a principal software engineer on the Flink team at Confluent. In Flink, he is working on various topics in the Table & SQL ecosystem.
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