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Confluent Certified Developer for Apache Kafka
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Killexams : Confluent Confluent test - BingNews https://killexams.com/pass4sure/exam-detail/CCDAK Search results Killexams : Confluent Confluent test - BingNews https://killexams.com/pass4sure/exam-detail/CCDAK https://killexams.com/exam_list/Confluent Killexams : What Makes Confluent (CFLT) a New Buy Stock No result found, try new keyword!Confluent (CFLT) could be a solid choice for investors given its accurate upgrade to a Zacks Rank #2 (Buy). An upward trend in earnings estimates -- one of the most powerful forces impacting stock ... Tue, 04 Oct 2022 05:22:00 -0500 text/html https://www.nasdaq.com/articles/what-makes-confluent-cflt-a-new-buy-stock Killexams : Developing Kafka Data Pipelines Just Got Easier

(Blue Planet Studio/Shutterstock)

Developing data pipelines in Apache Kafka just got easier thanks to the launch of Stream Designer, a graphical design tool that is now available on Confluent Cloud. Confluent also used this week’s Kafka conference, dubbed Current 2022, to announce a new version of its Stream Governance offering that adds point-in-time lineage tracking to the mix.

There’s no denying the power and popularity of Apache Kafka for building streaming data pipelines. Kafka is pretty much the undisputed heavyweight champion in this category, with 80% of the Fortune 100 using the open source product, which was originally developed at LinkedIn to store and query large amounts of streaming event data.

But along with that streaming power comes technological complexity, both in terms of getting the Kafka cluster set up and also in the development of data pipelines. Confluent has addressed the infrastructure complexity with its hosted Kafka offering, dubbed Confluent Cloud. And with today’s launch of Stream Designer, it’s taking a bite out of the design-time complexity too.

With Stream Designer, Confluent is giving Kafka users a way to design data pipelines in a visual manner. Instead of constructing a Kafka data pipeline from scratch by writing SQL. As a Directed Acyclic Graph (DAG), Stream Design allows users to construct data pipelines by dragging and dropping elements on a screen, which the product then converts to SQL that’s executed on the Kafka cluster, just as it did before.

Stream Designer is a drag-and-drop environment for creating data pipelines for Apache Confluent

Stream Designer will appeal to all Kafka users, including Kafka newbies who are just getting their feet wet with streaming data, as well as those with a lot of experience on the platform, says Jon Fancey, principal product manager at Confluent.

“It can often feel with any new technology that you have to learn everything before you do anything,” Fancey says. “If you’re relatively new to Kafka, some of the concepts and the learning curve can feel pretty steep. So Stream Designer provides an easier on ramp for you to be able to build things graphically.”

Confluent does a lot of stuff for the user automatically. For instance, since Kafka Connect connectors write data to subjects (“It’s what they do,” Fancey says), Confluent created Stream Designer to automatically create and configure a subject for the user when they select one of the 70-plus connectors available.

The product also lets users add stream processing capabilities to the pipeline, including filtering data and context-based routing, which will push results to an analytical database like Snowflake or Google Cloud Big Query, Fancey says.

“We can also do things like aggregation on the data, so maybe you can group it, summarize it over that streaming set of data,” he tells . “So essentially everything you can do in ksql that we have as our stream processing query engine, you can do in Stream Designer. And everything you can do in Connect with all the connectors that we have, you can do in Stream Designer as well.”

Stream Designer includes a built-in SQL editor, allowing users to go back and forth from the GUI design tool to the command line editor. Users can export the SQL generated by Stream Designer into code repositories, like GitHub, to provide change management capabilities. Users can also bring externally written SQL into Stream Designer, and work with it there, Fancey says.

But Stream Designer won’t just function as training wheels for Kafka beginners. According to Fancey, old Kafka hands will also find useful capabilities in the new product, such as the new observability metrics that highlight potential problems in a running Kafka cluster, and then surface the information necessary for the engineer to fix it.

“You can see the data flowing end to end and you can look at the lag of the data so you can understand if the pipeline is running effect and correctly at all times,” Fancey says. “And if there is a problem–maybe you have an issue with one of the tasks that’s running on the connector–we actually flag that for you. We alert you in the design canvas, and you can click into that and do a diagnosis, where we’re kind of surfacing up some of the internal log information into one place, instead of having to … jump around the platform to figure out what’s going on.”

Everything you can do with ksqlDB, including filtering and aggregations, you can do with Confluent’s new Stream Designer

As data pipelines start to proliferate at companies, the creation and management of them can quickly become a bottleneck to productivity. The tools and techniques that data engineers originally used with a handful of pipelines may not work when 100 or 1,000 pipelines are at play. By adding a GUI to the mix with Stream Designer, Confluent is giving users the option to choose which modality works for them. And users can always go back to and make tweaks to the generated SQL by hand, Fancey says.

“The code you would write in Stream Designer is the same code you would write without Stream Designer, with zero performance penalty,” Fancey says. “Some other tools don’t work the same way.”

For more info on Stream Designer, check out today’s Confluent blog post on the subject (no Connector necessary).

Streaming Data Governance

The other big announcement is the launch of Stream Governance Advanced.

Confluent previously launched its Stream Governance suite about a year ago. Today, Confluent is debuting Stream Governance Advanced, which adds several important new capabilities to the mix (the capabilities in the pre-existing product are now referred to as Stream Governance Essentials).

The biggest feature is the addition of point-in-time playback capability for data stream lineage. In the previous product, customers could go back and do a deep inspection of the previous 10 minute’s worth of streaming data. With this release, that window has been expanded to 24 hours, which will deliver users a much finer-grained look at what happened with their data, Fancey says.

“Maybe you had an issue in your environment yesterday,” he says. “You can actually go back in time to determine what caused that, and you can actually wind the clock back and look at those data flows as they existed at a previous point in time.”

In fact, Stream Governance Advanced goes beyond that, and allows users to inspect the previous seven-day window. However, that capability is only available with hourly blocks of data, meaning the data is less fine-grained (but still potentially useful).

When somebody says there’s a problem with the cluster, and they want to look at the log, the response often has been “well, they’re gone. The idea is to avoid those types of situations and given users the ability to track down those problems instead of waiting for them to reoccur, Fancey says.

Stream Governance Advanced also builds on the data catalog capability that Confluent previously launched (which is now available in Essentials). In the previous release, users could tag objects. With this release, Confluent has added the ability to track business metadata, which the company says will Strengthen the ability for users to discover data in their streaming data catalog.

Confluent has also added a GraphQL API, which will allow users to be more targeted in receiving only the specific data elements that they’re looking for in their query, as opposed to getting back much more data than they wanted.

Stream Governance has been well-received by Confluent customers so far, Fancey says, and the new features Confluent is launching with Advanced reflect the needs that early adopters have.

“It solves a problem that creeps up on you,” Fancey says. “The ability to govern data at scale…in a large estate can feel like a problem that you wish you’d planned for. Governance provides this capability straight away, and this is why we’re introducing Advanced.”

While users could conceivable create their own tools to govern the data, or perhaps buy third-party tools (although few, if any, exist for streaming data, which is a nascent category), the option of going without any governance increasingly is not an option for companies.

“The alternative is no governance, which means you end up with poor outcomes,” Fancey says. “Maybe [you get] low quality, untrusted data. You don’t understand the provenance of it. You don’t know who owns it. Governance solves a lot of these challenge, and Advanced provides more ability to add things like business metadata to the schemas, to the data, flowing through, so you can understand where it comes from, who owns it, how you contact them, and how you should be using it.”

Today marks the first full day of Current 2022, which is the follow-on to the Kafka Summit conference that Confluent previously sponsored. You can find more information about this currentevent.io.

Related Items:

It’s Time for Governance on Streaming Data, Confluent Says

Confluent Delivers New Cluster Controls, Data Connectors for Hosted Kafka

Intimidated by Kafka? Check Out Confluent’s New Developer Site

Tue, 04 Oct 2022 08:19:00 -0500 text/html https://www.datanami.com/2022/10/04/developing-kafka-data-pipelines-just-got-easier/
Killexams : Confluent launches visual streaming data pipeline designer

Confluent, the company that built a streaming service on top of the open source Apache Kafka project, has always been about helping companies capture streams of data. First it was on prem, then later in the cloud. By moving the streaming service to the cloud, it was able to abstract away a lot of the complexity related to managing the underlying infrastructure.

Today, at the Current conference, the company is introducing a new tool called Stream Designer to make it easier to build a streaming data pipeline in a visual workflow. Users can easily connect a set of data components to build a customized stream of data, and Confluent handles the coding in the background for them, essentially moving the abstraction up the stack from infrastructure to design.

Company co-founder and CEO Jay Kreps says that while it’s still aimed at developers, the goal is to put stream design within reach of more people than Apache Kafka experts.

“We’re still serving developers of all types, but this makes it something where you can just click and build a data pipeline that connects things, transforms data, sends things from place to place. And it inherits and works on the same underlying streaming infrastructure. That means all the data streams are reusable, they’re all real time and they’re all horizontally scalable,” Kreps told TechCrunch.

He says that although the program writes the underlying code for the developer, it is still accessible for developers who need to work with it. “One of the cool things about how we’ve done this, is even though you don’t have to write any code, all the code is there. You can see exactly what it’s doing under the hood. You can see exactly the kind of transformations in SQL that we’d be doing on this data, so it works with the existing developer tool chains if you need to do that,” he said.

Confluent Stream Designer tool © Provided by TechCrunch Confluent Stream Designer tool

Confluent Stream Designer example Image Credits: Confluent

For Kreps, this is all part of the evolution of Kafka, a project originally conceived at LinkedIn to move massive amounts of data. At first, it was a highly technical undertaking, but over time the company has been trying to make it increasingly accessible to a greater number of people inside an organization.

In addition to Stream Designer, the company is also announcing Stream Governance, which helps ensure the data is being using correctly and only authorized users can see data.

“For a lot of organizations it’s almost like there’s two competing pressures: One is to unlock the data and use it to be effective and serve customers better and be more efficient. And the other is to lock it up and be safe and don’t let anything bad happened. And unless you have tooling that helps with both of these dimensions, you kind of end up a little bit stuck,” he said. Stream Governance helps users make sure they are using the data flowing through these data streams in a safe and compliant way.

While they were at it, Confluent announced a new Confluent for Startups program, designed to get startups using the platform with free credits and access to expertise to help them get started with data streaming technologies.

Stream Designer and Stream Governance are available starting today as part of the Confluent cloud service subscription package, and there will no additional charge for the new capabilities, he said.

Confluent launches visual streaming data pipeline designer by Ron Miller originally published on TechCrunch

Tue, 04 Oct 2022 01:38:00 -0500 en-US text/html https://www.msn.com/en-us/news/technology/confluent-launches-visual-streaming-data-pipeline-designer/ar-AA12Aqeu
Killexams : Confluent Reimagines Data Pipelines for the Streaming Era with Stream Designer

The MarketWatch News Department was not involved in the creation of this content.

AUSTIN, Texas, (BUSINESS WIRE) -- Confluent, Inc. (NASDAQ: CFLT), the data streaming pioneer, today announced Stream Designer, a visual interface that enables developers to build and deploy streaming data pipelines in minutes. This point-and-click visual builder is a major advancement toward democratizing data streams so they are accessible to developers beyond specialized Apache Kafka experts. With more teams able to rapidly build and iterate on streaming pipelines, organizations can quickly connect more data throughout their business for agile development and better, faster, in-the-moment decision making.

"We are in the middle of a major technological shift, where data streaming is making real time the new normal, enabling new business models, better customer experiences, and more efficient operations,” said Jay Kreps, Cofounder and CEO, Confluent. “With Stream Designer we want to democratize this movement towards data streaming and make real time the default for all data flow in an organization.”

In the streaming era, data streaming is the default mode of data operations for successful modern businesses. The streaming technologies that were once at the edges have become core to critical business functions. This shift is fueled by the growing demand to deliver data instantaneously and scalably across a full range of customer experiences and business operations. Traditional batch processing can no longer keep pace with the growing number of use cases that depend on sub-millisecond updates across an ever-expansive set of data sources.

Organizations are seeking ways to accelerate their data streaming initiatives as more of their business is operating in real time. Kafka is the de facto standard for data streaming, as it enables over 80% of Fortune 100 companies to reliably handle large volumes and varieties of data in real time. However, building streaming data pipelines on open-source Kafka requires large teams of highly specialized engineering talent and time-consuming development spread across multiple tools. This puts pervasive data streaming out of reach for many organizations and leaves existing legacy pipelines clogged with stale and outdated data.

“A rising number of organizations are realizing streaming data is imperative to achieving innovation and maintaining a healthy business,” said Amy Machado, Research Manager, Streaming Data Pipeline, IDC. “Businesses need to add more streaming use cases, but the lack of developer talent and increasing technical debt stand in the way. Visual interfaces, like Stream Designer, are key advancements to overcoming these challenges and make it easier to develop data pipelines for existing teams and the next generation of developers.”

Stream Designer: The First Visual Interface for Rapidly Building Streaming Data Pipelines Natively on Kafka

“Data streaming is quickly becoming the central nervous system of our infrastructure as it powers real-time customer experiences across our 12 countries of operations,” said Enes Hoxha, Enterprise Architect, Raiffeisen Bank International. “Stream Designer’s low-code, visual interface will enable more developers, across our entire organization, to leverage data in motion. With a unified, end-to-end view of our streaming data pipelines, it will Strengthen our developer productivity by making real-time applications, pipeline development, and troubleshooting much easier.”

Stream Designer provides developers a flexible point-and-click canvas to build pipelines in minutes and describe data flows and business logic easily within the Confluent Cloud UI. It takes a developer-centric approach, where users with different skills and needs can seamlessly switch between the UI, a code editor, and command-line interface to declaratively build data flow logic at top speed. It brings developer-oriented practices to pipelines, making it easier for developers new to Kafka to scale data streaming projects faster.

With Stream Designer, organizations can:

  • Boost developer productivity: Instead of spending days or months managing individual components on open source Kafka, developers can build pipelines with the complete Kafka ecosystem accessible in one visual interface. They can build, iterate and test before deploying into production in a modular fashion, keeping with popular agile development methodologies. There’s no longer a need to work across multiple discrete components, like Kafka Streams and Kafka Connect, that each require their own boilerplate code.
  • Unlock a unified end-to-end view:After building a pipeline, the next challenge is maintaining and updating it over its lifecycle as business requirements change and tech stacks evolve. Stream Designer provides a unified, end-to-end view to easily observe, edit, and manage pipelines and keep them up to date.
  • Accelerate development of real-time applications:Pipelines built on Stream Designer can be exported as SQL source code for sharing with other teams, deploying to another environment, or fitting into existing CI/CD workflows. Stream Designer allows multiple users to edit and work on the same pipeline live, enabling seamless collaboration and knowledge transfer.

Connect with Confluent at Current to learn more!

See Stream Designer in action at Current. Today, October 4 at 10:00 am CT, Confluent CEO and Cofounder Jay Kreps takes the stage to talk about the data streaming category in the keynote “Welcome to the Streaming Era.” And, on October 5 at 10:00 am CT tune into the mainstage for a deep dive into the product. Register now to see it virtually. Live demos will be given for in-person attendees at the Confluent booth.

Additional Resources

About Confluent

Confluent is the data streaming platform that is pioneering a fundamentally new category of data infrastructure that sets data in motion. Confluent’s cloud-native offering is the foundational platform for data in motion—designed to be the intelligent connective tissue enabling real-time data, from multiple sources, to constantly stream across the organization. With Confluent, organizations can meet the new business imperative of delivering rich, digital front-end customer experiences and transitioning to sophisticated, real-time, software-driven backend operations. To learn more, please visit www.confluent.io.

The preceding outlines our general product direction and is not a commitment to deliver any material, code, or functionality. The development, release, timing, and pricing of any features or functionality described may change. Customers should make their purchase decisions based upon services, features, and functions that are currently available.

Confluent and associated marks are trademarks or registered trademarks of Confluent, Inc.

Apache® and Apache Kafka® are either registered trademarks or trademarks of the Apache Software Foundation in the United States and/or other countries. No endorsement by the Apache Software Foundation is implied by the use of these marks. All other trademarks are the property of their respective owners.

View source version on businesswire.com: https://www.businesswire.com/news/home/20221004005013/en/

SOURCE: Confluent, Inc.

Lyn Eyad
pr@confluent.io

COMTEX_415898714/2456/2022-10-04T09:00:25

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The MarketWatch News Department was not involved in the creation of this content.

Tue, 04 Oct 2022 01:00:00 -0500 en-US text/html https://www.marketwatch.com/press-release/confluent-reimagines-data-pipelines-for-the-streaming-era-with-stream-designer-2022-10-04
Killexams : Confluent Launches Stream Governance Advanced to Safely Extend the Power of Data Streaming to Every Part of the Business

Enterprise-grade governance is now possible with point-in-time lineage insights, rich context cataloging, and globally available quality controls

Confluent’s Q4 ‘22 Launch also delivers Private Service Connect for Google Cloud

AUSTIN, Texas, October 04, 2022--(BUSINESS WIRE)--Confluent, Inc. (NASDAQ: CFLT), the data streaming pioneer, today announced a new tier of capabilities for Stream Governance, the industry’s only fully managed governance suite for Apache Kafka® and data in motion. With Stream Governance Advanced, organizations can resolve issues within complex pipelines easier with point-in-time lineage, discover and understand subjects faster with business metadata, and enforce quality controls globally with Schema Registry. With more teams able to safely and confidently access data streams, organizations can build critical applications faster.

"Businesses heavily rely on real-time data to make fast and informed decisions, so it’s paramount that the right teams have quick access to trustworthy data," said Chad Verbowski, Senior Vice President of Engineering, Confluent. "With Stream Governance, organizations can understand the full scope of streams flowing across their business so they can quickly leverage that data to power endless use cases."

Stream Governance Advanced: Point-in-Time Lineage Insights, Sophisticated Data Cataloging, and Global Quality Controls

"SecurityScorecard observes over 180 billion signals a week to provide customers with 360-degree, real-time security prevention," said Brandon Brown, Senior Staff Software Engineer, Data Platform, SecurityScorecard. "With Stream Governance, we have clear visibility into all our data, where we generate it, what it looks like, and how it has changed over time. We have confidence that our high-quality data is powering our business as we extend the use of data streaming across our entire organization. As more teams work with data streams and share their projects with others via object tagging and custom metadata details, the possibility of what we can build for our customers becomes incredibly exciting."

Data streaming use cases are rapidly growing as real-time data powers more of the business. This has caused a proliferation of data that holds endless business value if teams are able to confidently share it across the organization. Building on the suite of features initially introduced with Stream Governance Essentials, Stream Governance Advanced delivers more ways to easily discover, understand, and trust data in motion. With scalable quality controls in place, organizations can democratize access to data streams across teams while achieving always-on data integrity and regulatory compliance.

New capabilities include:

  • Point-in-time playbacks for Stream Lineage: Troubleshooting complex data streams is now faster and easier with the ability to understand where, when, and how data streams have changed over time. Point-in-time lineage provides a look back into a data stream’s history over a 24-hour period or within any one-hour window over a seven-day range. Teams can now see what happened on, for example, Thursday at 5pm, when support tickets started coming in. Paired with the new ability to search across lineage graphs for specific objects such as client IDs or topics, point-in-time lineage makes it easier to identify and resolve issues in order to keep mission-critical services up for customers and new projects on track for deployment.

  • Business metadata for Stream Catalog: Strengthen data discovery with the ability to build more contextual, detail-rich catalogs of data streams. Alongside previously available tagging of objects, business metadata gives individual users the ability to add custom, open-form details represented as key-value pairs to entities they create such as topics. These details, from users who know the platform best, are critical to enabling self-service access to data for the larger organization. While tagging has allowed users to flag a subject as "sensitive," business metadata allows that user to add more context, such as which team owns the topic, how it is being used, who to contact with questions about the data, or any other details necessary.

    Exploring the catalog is now even easier with GraphQL API, giving users a simple, declarative method to specify and get the exact data they need while enabling a better understanding of data relationships on the platform.

  • Globally available Schema Registry for Stream Quality: By more than doubling the global availability of Schema Registry to 28 regions, teams have more flexibility to manage schemas directly alongside their Kafka clusters in order to maintain strict compliance requirements and data sovereignty. Additionally, Schema Registry is even more resilient with an increased 99.95% uptime SLA, giving businesses the confidence they need that quality controls for Kafka will always be in place as more groups start working with the technology.

Confluent Q4 ‘22 Launch Expands Support for Private Networking

Confluent’s quarterly launch announcements provide an easy way to get up to speed on new innovations that are now available. In addition to Stream Governance Advanced, this quarter’s highlights include:

Private Service Connect for Google Cloud delivers a simple and secure connection from a Google Cloud virtual private cloud (VPC) to Confluent Cloud. This highly secure private networking setup minimizes the complexity and burden of manually connecting virtual networks in the public cloud while keeping all details about a customer’s network private. Now, Confluent Cloud supports private endpoints across all three major cloud service providers, including AWS Private Link and Azure Private Link.

Additional Resources

About Confluent

Confluent is the data streaming platform that is pioneering a fundamentally new category of data infrastructure that sets data in motion. Confluent’s cloud-native offering is the foundational platform for data in motion—designed to be the intelligent connective tissue enabling real-time data, from multiple sources, to constantly stream across the organization. With Confluent, organizations can meet the new business imperative of delivering rich, digital front-end customer experiences and transitioning to sophisticated, real-time, software-driven backend operations. To learn more, please visit www.confluent.io.

The preceding outlines our general product direction and is not a commitment to deliver any material, code, or functionality. The development, release, timing, and pricing of any features or functionality described may change. Customers should make their purchase decisions based upon services, features, and functions that are currently available.

Confluent and associated marks are trademarks or registered trademarks of Confluent, Inc.

Apache® and Apache Kafka® are either registered trademarks or trademarks of the Apache Software Foundation in the United States and/or other countries. No endorsement by the Apache Software Foundation is implied by the use of these marks. All other trademarks are the property of their respective owners.

View source version on businesswire.com: https://www.businesswire.com/news/home/20221004005085/en/

Contacts

Lyn Eyad
pr@confluent.io

Tue, 04 Oct 2022 01:43:00 -0500 en-US text/html https://www.yahoo.com/lifestyle/confluent-launches-stream-governance-advanced-130000083.html
Killexams : Why I Own Confluent Stock No result found, try new keyword!When it comes to data processing, Confluent(NASDAQ: CFLT) is reimagining the way businesses derive real-time operational decisions. The company has seen massive traction, and this video explains ... Mon, 03 Oct 2022 09:44:00 -0500 text/html https://www.theglobeandmail.com/investing/markets/markets-news/Motley%20Fool/10540396/why-i-own-confluent-stock/ Killexams : Confluent Introduces Stream Governance Advanced to Safely Extend Data Streaming Power

Confluent recently announced new enhancements to its Stream Governance product that will Strengthen engineering teams' ability to discover, understand, and trust real-time data. Organizations can use Stream Governance Advanced to resolve issues within complex pipelines more easily with point-in-time lineage, discover and understand subjects more quickly with business metadata, and enforce quality controls globally with Schema Registry.

Chad Verbowski, senior vice president of engineering, Confluent, said in a press release:

Businesses heavily rely on real-time data to make fast and informed decisions, so it’s paramount that the right teams have quick access to trustworthy data. With Stream Governance, organizations can understand the full scope of streams flowing across their business so they can quickly leverage that data to power endless use cases.

To learn more about Stream Governance Advanced, InfoQ reached out to David Araujo, principal product manager at Confluent.

InfoQ: Where did the Stream Governance Advanced tier come from? Was this created from customer feedback?

David Araujo: Stream Governance Advanced was devised following the launch of our governance suite in September 2021. Wide adoption of Stream Governance features proved this to be a critical need for businesses. Still, customer feedback guided us toward where and how we needed to continue evolving the product. Customers seeking to expand their use of Apache Kafka and real-time data streaming for even more sophisticated, mission-critical use cases were dependent upon the quality and visibility/discovery tools that could scale enterprise deployment.

InfoQ: What are the clear use cases for the Stream Governance Advanced tier?

Araujo: Stream Governance Advanced delivers enterprise-grade governance and data visibility for production workloads, allowing businesses to:

  • Confidently govern mission-critical workloads at any scale with a new 99.95% uptime SLA for Schema Registry available across 28 global regions (Stream Quality)
    • The 99.95% uptime SLA for Schema Registry (new for Advanced) allows teams to offload more workloads to the cloud with high confidence that data quality controls for Apache Kafka will be highly available—especially valuable for teams self-managing open-source Kafka deployments who can shift to a highly available, fully managed service.
    • Schema Registry support across 28 global regions (expanded for Advanced) allows teams to optimize performance on the data streaming platform and further establish data sovereignty with schemas sitting closer to their corresponding Kafka clusters or any available region of choice.
  • Enhance data discovery within your streaming catalog with user-generated business context and easy, declarative search via GraphQL API (Stream Catalog)
    • Business metadata (new for Advanced) allows individual users to add custom, open-form details to platform objects such as a subject in order to help other users understand which team owns the topic, how it is being used, who to contact with questions about the data, or any other details they deem necessary.
    • The GraphQL API (new for Advanced) allows users to take advantage of the graph nature of the Stream Catalog, which is modeled as a graph of entities and relationships, and provides them with a more natural, efficient, and productive way of programmatically exploring the catalog.
  • Simplify comprehension and troubleshooting of complex data streams with lineage search and historical point-in-time insights (Stream Lineage)
    • Point-in-time lineage (new for Advanced) provides users with a look into the past—allowing them to see data stream evolutions over 24 hours or within any 1-hour window over a 7-day range in order to answer questions such as, "What happened to the pipeline on Friday at 3 pm when support tickets started arriving?" or "What did this pipeline look like last week when my manager seemed happier with the configuration?"
    • Search the lineage graph (new for Advanced) allows users to save time during development or investigations by finding specific objects such as client IDs or subjects buried with complex data pipelines.

InfoQ: Is there complete feature parity between the new advanced tier and the essentials tier? What are the differences?

Araujo: All features included within the Essentials tier are included within Advanced. Stream Governance Advanced introduces net-new features for stream catalog and stream lineage not found in Essentials alongside higher limits, expanded regional coverage, and an increased SLA for Schema Registry (stream quality). Full side-by-side details here.   

InfoQ: How does pricing now work for the Stream Governance offering?

Araujo: Stream Governance Essentials is made available to all Confluent Cloud customers free of charge for up to 1,000 schemas per environment, after which schemas are billed at a rate of $0.002/schema/hour. 
Stream Governance Advanced is priced at $1/hour/environment with support for up to 20,000 total schemas per environment.

InfoQ: What is the roadmap for the future of Stream Governance?

Araujo: Since launching in 2021, Stream Governance has become a critical suite of capabilities for Confluent customers seeking to safely expand data streaming deployments in the cloud to deliver against growing customer expectations for "real-time everything." As such, we continue to invest heavily in developing more governance features across Confluent’s entire data streaming platform to simplify further customer efforts to move real-time data throughout their entire tech stack and achieve that goal.

Fri, 07 Oct 2022 04:35:00 -0500 en text/html https://www.infoq.com/news/2022/10/confluent-stream-governance/?topicPageSponsorship=7014c5ba-cbd3-434a-a53e-1a344908657e
Killexams : Confluent debuts ‘point-and-click’ canvas for building streaming data pipelines

To further strengthen our commitment to providing industry-leading coverage of data technology, VentureBeat is excited to welcome Andrew Brust and Tony Baer as regular contributors. Watch for their articles in the Data Pipeline.

California-based Confluent, which offers an Apache Kafka-based data streaming platform, today announced Stream Designer, a visual interface to help developers build, test and deploy real-time data pipelines in a matter of minutes. The company showcased the tool at its ongoing Current 2022 conference.

In the last few years, real-time data has become crucial to business growth and success. Batch data is still in widespread use, but it fails to answer many challenges and use cases that enterprises encounter in their routine operations. As a result, streaming data technologies that were once at the edges are witnessing a surge in adoption, including Apache Kafka.

Over 80% of Fortune 100 companies use Kafka to handle large volumes of data in real time. However, when it comes to building streaming data pipelines on open-source Kafka, teams have to bring in highly specialized engineering talent and deal with long development timelines spread across multiple tools. This puts pervasive data streaming out of reach for many organizations.

Enter Stream Designer

Confluent’s new Stream Designer, which is now generally available, offers a point-and-click visual canvas to describe data flows and business logic within the Confluent Cloud UI. This way, instead of dealing with the headache of managing individual components on Kafka (each requiring its own boilerplate code), developers can build pipelines with the complete Kafka ecosystem accessible in one visual interface. They can also iterate and test before deploying into production in a modular fashion.

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“This is the industry’s first visual interface for building streaming pipelines natively on Kafka. While there are other GUI-based stream processors out there, they are powered by other, often closed and proprietary, messaging technologies,” Jon Fancey, principal product manager at Confluent, told VentureBeat. “Stream Designer is built on Kafka, which is widely known as the standard for data streaming. It is the developers’ platform of choice because of its highly scalable and resilient architecture as well as strong open-source following.”

Fancey stated that they held a closed beta program for Stream Designer with select customers and witnessed “very positive” feedback.

“It cut down the ramp time for developers new to Kafka and boosted productivity for more experienced Kafka developers,” he said. “With a radically easier way to build, test and deploy streaming data pipelines, they were able to transform traditional ETL pipelines to support a real-time paradigm.”

End-to-end view

Once a pipeline built using Stream Designer is deployed, teams can also use the tooling to get an end-to-end view of their streaming data pipeline, as well as maintain and update it over its lifecycle. Plus, these pipelines can also be exported as SQL source code for sharing with other teams, deploying to another environment, or fitting into existing continuous integration and continuous delivery (CI/CD) workflows — enabling seamless collaboration and knowledge transfer.

“Data streaming is quickly becoming the central nervous system of our infrastructure as it powers real-time customer experiences across our 12 countries of operations,” said Enes Hoxha, enterprise architect at Raiffeisen Bank International.

“Stream Designer’s low-code, visual interface will enable more developers, across our entire organization, to leverage data in motion. With a unified, end-to-end view of our streaming data pipelines, it will Strengthen our developer productivity by making real-time applications, pipeline development and troubleshooting much easier,” he added.

What’s more at Current 2022?

Confluent also used the Current conference to announce Stream Governance Advanced, a new tier of its fully managed governance suite for Apache Kafka and data in motion. 

The offering, as the company explained, will provide enterprises with point-in-time lineage to resolve issues within complex pipelines, business metadata to discover and understand subjects faster and Schema Registry to enforce quality controls globally. 

The company also announced a private service connect for Google Cloud, enabling enterprises to set up a simple and secure connection from a Google Cloud virtual private cloud (VPC) to Confluent Cloud. This will minimize the complexity and burden of manually connecting virtual networks in the public cloud while keeping all details about a customer’s network private. 

Notably, the development means Confluent Cloud now supports private endpoints across all three major cloud service providers.

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Mon, 03 Oct 2022 20:16:00 -0500 Shubham Sharma en-US text/html https://venturebeat.com/data-infrastructure/confluent-debuts-point-and-click-canvas-for-building-streaming-data-pipelines/
Killexams : Confluent CEO on taking data streaming mainstream - ‘How can we make it easy?’
(Image sourced via Confluent)

Confluent’s user conference kicked off in Austin this week with two announcements that were aimed at democratizing data streaming in organizations. The company, which has grown out of the Apache Kafka open source movement, recognizes that as enterprises shift from batch processing and historical data use, to real-time data streams (or ‘data in motion’), this is going to require tooling, guidance and support to expand systems beyond companies that can invest in expensive, highly technical engineering teams. 

This was a key part of the themes explored by Confluent CEO Jay Kreps this week during both his keynote and the press briefing. Kreps argued that Confluent - and more broadly, data streaming - is at an inflection point of technology adoption, whereby it’s rising on the curve towards becoming popular enough to disrupt industries and the economy. 

He used the example of electricity to explain, however, that there is an inherent tension at play between disruptive new technologies and managing the demand/supply dynamics in order to fuel more adoption and use cases. Kreps said: 

When electricity was invented, you might imagine we went from the steam powered factory with the crankshaft and then something happens with Benjamin Franklin and everything is electrified, 

It's actually a little more complicated than that, how a new technology is developed and how it rolls out. There's actually a chicken and egg problem to solve. How do you get the egg if you don't have the chicken? And there wouldn't have been a chicken if you didn't have an egg? 

It turns out you have kind of a virtuous cycle here, where there's some increase in supply, some early innovation starts to drive a little demand for electricity and a few use cases here and there. But it's hard, it's difficult. 

Additional demand drives more supply, right? There's more markets to sell electricity to and and this starts to kind of spin something up and that's how you go up that adoption curve - that's how you start to hit that inflection point, And at a certain point it becomes reliable enough and plentiful enough and well known enough and there's enough skills around it that it starts to really take off.

Kreps said that in many ways this is what data streaming is experiencing, where companies have been partaking in some experimental projects that have stimulated more opportunities for vendors, such as Confluent. But this virtuous cycle of innovation stimulating more supply/demand has reached a “deployment period” now, Kreps added, and the capabilities are expanding and building. 

Making Apache Kafka approachable

Kreps believes that real-time data streaming and Confluent have an opportunity to impact economies in the same way that electricity did. Whether or not you buy into that idea, it’s hard not to argue that organizations are wising up to the fact that data is fundamental to their future success. And when you think about relying on historical data, which can often paint an inaccurate picture about what’s happening ‘now’, it’s not too hard to understand why Confluent and this idea of ‘real time data events’ is seeing success. 

It’s not just the real-time nature of data streaming that’s appealing, it’s the opportunity to understand every data event that has taken place at any moment in time - whereas traditional databases are prone to errors and corrections that make this difficult. It’s no surprise that Confluent’s offering has been compared to distributed ledger technology (or Blockchain) a number of times at the event this week (although they are distinctly different). 

But Kreps is right to say that this will require effort on Confluent’s part, and the part of the ecosystem, to make Apache Kafka and data streaming more accessible to a wider audience. Or, to put it another way, make it easier to use. Many of the conversations I’ve had with customers since I started covering this area have focused on both the organizational shift required to adopting a real-time streaming operating model, as well as the investment required in engineering skills to make it successful. 

This is the next stage of Confluent’s journey, since its successful launch of its cloud offering. I asked Kreps what his larger customers are asking of the company, what do they still want to see from Confluent? And his response tied directly into this agenda. He said: 

I think there’s probably two really big driving needs. One is very crisply stated and the other is less crisp. The first is around governance, these larger companies are incredibly diverse and they need automated ways of governing things, so that the right thing happens and the data is understandable. 

The second one is more vague - how can we make it easy? How can we make it easy to adopt? 

Early on it was really only approachable for the Silicon Valley tech companies who were going to hire a big team of engineers to run Kafka and then kind of build it by hand, into each system they had. It was very valuable for them, but a large undertaking, hard to do. So if you think about it from Confluent’s point of view, what is it we need to do? We need to make it easy, make it approachable, and then that makes it applicable to the rest of the world.

I think that is the combination of cloud, making the operations problem go away. Also, helping to orchestrate that mindset shift for these bigger companies. And then tools, like the stream processing tools, KSQL, Stream Designer - I think that can make people much more productive in this area. 

However, Kreps also was desparate to point out that you don’t have to reinvent the wheel on your first attempt. Companies need time to adjust and part of that involves starting small, identifying quick wins, and then scaling up. He added: 

This whole idea of real time streaming data, it’s kind of obvious that [everything]] should work that way - but it doesn’t today. So how do you get from here to there? 

The first use case is the first use case, you don’t have to transform the whole organization to do that one thing. But we try to work with organizations throughout that whole journey. How can you do the first thing as easily as possible and how do you spread that across the organization? What do you have to have in place when data is exchanged broadly across the organization? 

My take

I think this frames Confluent’s ambitions nicely for the next few years. Data streaming is highly technical and complex, but if it’s going to change the way the world operates, Kreps knows that it needs to be made more accessible. We’ve seen this in other sectors - NoSQL databases, for example - where vendors that have built the technical foundation of their platform have then been able to move up the pyramid and get the attention of business leaders too. Confluent is on an interesting path and it’s building an impressive portfolio of customers. How it adapts and responds to reaching this ‘inflection point’ - and going beyond it - will be its defining moment. 

Tue, 04 Oct 2022 12:00:00 -0500 BRAINSUM en text/html https://diginomica.com/confluent-ceo-taking-data-streaming-mainstream-how-can-we-make-it-easy
Killexams : Confluent Reimagines Data Pipelines for the Streaming Era with Stream Designer

Accelerate the shift to real-time with the industry’s first visual interface for building, testing, and deploying data pipelines natively on Apache Kafka®

AUSTIN, Texas, October 04, 2022--(BUSINESS WIRE)--Confluent, Inc. (NASDAQ: CFLT), the data streaming pioneer, today announced Stream Designer, a visual interface that enables developers to build and deploy streaming data pipelines in minutes. This point-and-click visual builder is a major advancement toward democratizing data streams so they are accessible to developers beyond specialized Apache Kafka experts. With more teams able to rapidly build and iterate on streaming pipelines, organizations can quickly connect more data throughout their business for agile development and better, faster, in-the-moment decision making.

"We are in the middle of a major technological shift, where data streaming is making real time the new normal, enabling new business models, better customer experiences, and more efficient operations," said Jay Kreps, Cofounder and CEO, Confluent. "With Stream Designer we want to democratize this movement towards data streaming and make real time the default for all data flow in an organization."

In the streaming era, data streaming is the default mode of data operations for successful modern businesses. The streaming technologies that were once at the edges have become core to critical business functions. This shift is fueled by the growing demand to deliver data instantaneously and scalably across a full range of customer experiences and business operations. Traditional batch processing can no longer keep pace with the growing number of use cases that depend on sub-millisecond updates across an ever-expansive set of data sources.

Organizations are seeking ways to accelerate their data streaming initiatives as more of their business is operating in real time. Kafka is the de facto standard for data streaming, as it enables over 80% of Fortune 100 companies to reliably handle large volumes and varieties of data in real time. However, building streaming data pipelines on open-source Kafka requires large teams of highly specialized engineering talent and time-consuming development spread across multiple tools. This puts pervasive data streaming out of reach for many organizations and leaves existing legacy pipelines clogged with stale and outdated data.

"A rising number of organizations are realizing streaming data is imperative to achieving innovation and maintaining a healthy business," said Amy Machado, Research Manager, Streaming Data Pipeline, IDC. "Businesses need to add more streaming use cases, but the lack of developer talent and increasing technical debt stand in the way. Visual interfaces, like Stream Designer, are key advancements to overcoming these challenges and make it easier to develop data pipelines for existing teams and the next generation of developers."

Stream Designer: The First Visual Interface for Rapidly Building Streaming Data Pipelines Natively on Kafka

"Data streaming is quickly becoming the central nervous system of our infrastructure as it powers real-time customer experiences across our 12 countries of operations," said Enes Hoxha, Enterprise Architect, Raiffeisen Bank International. "Stream Designer’s low-code, visual interface will enable more developers, across our entire organization, to leverage data in motion. With a unified, end-to-end view of our streaming data pipelines, it will Strengthen our developer productivity by making real-time applications, pipeline development, and troubleshooting much easier."

Stream Designer provides developers a flexible point-and-click canvas to build pipelines in minutes and describe data flows and business logic easily within the Confluent Cloud UI. It takes a developer-centric approach, where users with different skills and needs can seamlessly switch between the UI, a code editor, and command-line interface to declaratively build data flow logic at top speed. It brings developer-oriented practices to pipelines, making it easier for developers new to Kafka to scale data streaming projects faster.

With Stream Designer, organizations can:

  • Boost developer productivity: Instead of spending days or months managing individual components on open source Kafka, developers can build pipelines with the complete Kafka ecosystem accessible in one visual interface. They can build, iterate and test before deploying into production in a modular fashion, keeping with popular agile development methodologies. There’s no longer a need to work across multiple discrete components, like Kafka Streams and Kafka Connect, that each require their own boilerplate code.

  • Unlock a unified end-to-end view: After building a pipeline, the next challenge is maintaining and updating it over its lifecycle as business requirements change and tech stacks evolve. Stream Designer provides a unified, end-to-end view to easily observe, edit, and manage pipelines and keep them up to date.

  • Accelerate development of real-time applications: Pipelines built on Stream Designer can be exported as SQL source code for sharing with other teams, deploying to another environment, or fitting into existing CI/CD workflows. Stream Designer allows multiple users to edit and work on the same pipeline live, enabling seamless collaboration and knowledge transfer.

Connect with Confluent at Current to learn more!

See Stream Designer in action at Current. Today, October 4 at 10:00 am CT, Confluent CEO and Cofounder Jay Kreps takes the stage to talk about the data streaming category in the keynote "Welcome to the Streaming Era." And, on October 5 at 10:00 am CT tune into the mainstage for a deep dive into the product. Register now to see it virtually. Live demos will be given for in-person attendees at the Confluent booth.

Additional Resources

About Confluent

Confluent is the data streaming platform that is pioneering a fundamentally new category of data infrastructure that sets data in motion. Confluent’s cloud-native offering is the foundational platform for data in motion—designed to be the intelligent connective tissue enabling real-time data, from multiple sources, to constantly stream across the organization. With Confluent, organizations can meet the new business imperative of delivering rich, digital front-end customer experiences and transitioning to sophisticated, real-time, software-driven backend operations. To learn more, please visit www.confluent.io.

The preceding outlines our general product direction and is not a commitment to deliver any material, code, or functionality. The development, release, timing, and pricing of any features or functionality described may change. Customers should make their purchase decisions based upon services, features, and functions that are currently available.

Confluent and associated marks are trademarks or registered trademarks of Confluent, Inc.

Apache® and Apache Kafka® are either registered trademarks or trademarks of the Apache Software Foundation in the United States and/or other countries. No endorsement by the Apache Software Foundation is implied by the use of these marks. All other trademarks are the property of their respective owners.

View source version on businesswire.com: https://www.businesswire.com/news/home/20221004005013/en/

Contacts

Lyn Eyad
pr@confluent.io

Tue, 04 Oct 2022 04:19:00 -0500 en-US text/html https://www.yahoo.com/entertainment/confluent-reimagines-data-pipelines-streaming-130000002.html
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