Streaming architectures have been on the rise steadily and as a result, we have seen the adoption of Kafka go up too. With the diverse spread of use cases across multiple industries, we have seen a variety of Kafka deployments across our hundreds of Kafka customers. Along the way, we have learnt some best practices as well as what not to do in mission-critical architectures. Join Joe Niemiec, Sr. Product Manager at Cloudera, as he shares these insights in this session that covers topics such as - The many ways that Kafka has been deployed in the field Standalone clusters, multiple clusters in a single data center and multiple clusters geographically distributed performing replication Clusters of all sizes small and large, few messages to hundreds of thousands per second Discussion about architecture failure domains Configurations tuned and used in specific deployments
Fan-out, fan-in & the multiplexer: Replication recipes for global platform di...HostedbyConfluent
This session will dive into our most successful (and unsuccessful!) multi-cluster event replication patterns.
An x-ray of the cross cluster distribution model that powers our globally distributed APIs will touch on the benefits that this model has provided in terms of client API experience, delivery agility and developer experience.
We will focus on recipes for effective use of Mirror Maker event replication to power platform distribution including the challenges of managing a 'fan in' event replication workflow - pulling events created in satellite clusters back to a mothership cluster for processing.
We will introduce the elegant technique of replication event multiplexing - which can be used to simplify the burden of managing a 'fan-in' replication topology by eliminating regional awareness from the application domain and improving replication health monitoring & observability.
Using Kafka as a Database For Real-Time Transaction Processing | Chad Preisle...HostedbyConfluent
You have learned about Kafka event sourcing with streams and using Kafka as a database, but you may be having a tough time wrapping your head around what that means and what challenges you will face. Kafka’s exactly once semantics, data retention rules, and stream DSL make it a great database for real-time transaction processing. This talk will focus on how to use Kafka events as a database. We will talk about using KTables vs GlobalKTables, and how to apply them to patterns we use with traditional databases. We will go over a real-world example of joining events against existing data and some issues to be aware of. We will finish covering some important things to remember about state stores, partitions, and streams to help you avoid problems when your data sets become large.
Mainframe Integration, Offloading and Replacement with Apache Kafka | Kai Wae...HostedbyConfluent
Legacy migration is a journey. Mainframes cannot be replaced in a single project. A big bang will fail. This has to be planned long-term.
Mainframe offloading and replacement with Apache Kafka and its ecosystem can be used to keep a more modern data store in real-time sync with the mainframe, while at the same time persisting the event data on the bus to enable microservices, and deliver the data to other systems such as data warehouses and search indexes.
This session walks through the different steps some companies are already gone through. Technical options like Change Data Capture (CDC), MQ, and third-party tools for mainframe integration, offloading and replacement are explored.
0-330km/h: Porsche's Data Streaming Journey | Sridhar Mamella, PorscheHostedbyConfluent
The auto industry is midst a data revolution that is transforming how companies do business. Once a scarce resource, data has now become abundant and cheap. What are the new technologies that change the way we produce, collect, process, store, and analyze data. What new streams of data are being created with Industry 4.0 and the Internet of Things on the horizon, is there significant value to taking a strategic approach to Fast Data. How is Porsche building the next level Data Streaming Platform with open source technologies and how we are using CI/CD pipelines amongst others in order to serve our use cases.
Kubernetes connectivity to Cloud Native Kafka | Evan Shortiss and Hugo Guerre...HostedbyConfluent
If you want to build an ecosystem of streaming data to your Kafka platform, you will need a much easier way for your developer to quickly move what’s on the source to your cluster. Better yet, making the connector serverless so it would NOT waste any resources for being idle, and having a trusted partner manage your Kafka infrastructure for you. In this session, we will show you how easy we have made streaming data with great user experience. Flexible resource management with our new secret weapon in the Apache Camel project -- Kamelet. We’ll also demonstrate how Red Hat OpenShift Streams for Apache Kafka simplifies the provisioning of Kafka deployments in a public cloud, managing the cluster,topics, and configuring secure access to the Kafka cluster for your developers.
Availability of Kafka - Beyond the Brokers | Andrew Borley and Emma Humber, IBMHostedbyConfluent
While Kafka has guarantees around the number of server failures a cluster can tolerate, to avoid service interruptions, or even data loss, it is prudent to have infrastructure in place for when an environment becomes unavailable during a planned or unplanned outage.
This talk describes the architectures available to you when planning for an outage. We will examine configurations including active/passive and active/active as well as availability zones and debate the benefits and limitations of each. We will also cover how to set up each configuration using the tools in Kafka.
Whether downtime while you fail over clients to a backup is acceptable or you require your Kafka clusters to be highly available, this talk will give you an understanding of the options available to mitigate the impact of the loss of an environment.
How to Discover, Visualize, Catalog, Share and Reuse your Kafka Streams (Jona...HostedbyConfluent
As Kafka deployments grow within your organization, so do the challenges around lifecycle management. For instance, do you really know what streams exist, who is producing and consuming them? What is the effect of upstream changes? How is this information kept up to date, so it is relevant and consistent to others looking to reuse these streams? Ever wish you had a way to view and visualize graphically the relationships between schemas, topics and applications? In this talk we will show you how to do that and get more value from your Kafka Streaming infrastructure using an event portal. It’s like an API portal but specialized for event streams and publish/subscribe patterns. Join us to see how you can automatically discover event streams from your Kafka clusters, import them to a catalog and then leverage code gen capabilities to ease development of new applications.
Building a Modern, Scalable Cyber Intelligence Platform with Apache Kafka | J...HostedbyConfluent
As cyber threats continuously grow in sophistication and frequency, companies need to quickly acclimate to effectively detect, respond, and protect their environments. At Intel, we’ve addressed this need by implementing a modern, scalable Cyber Intelligence Platform (CIP) based on Splunk and Apache Kafka. We believe that CIP positions us for the best defense against cyber threats well into the future.
Our CIP ingests tens of terabytes of data each day and transforms it into actionable insights through streams processing, context-smart applications, and advanced analytics techniques. Kafka serves as a massive data pipeline within the platform. It provides us the ability to operate on data in-stream, enabling us to reduce Mean Time to Detect (MTTD) and Mean Time to Respond (MTTR). Faster detection and response ultimately leads to better prevention.
In our session, we’ll discuss the details described in the IT@Intel white paper that was published in Nov 2020 with same title.
Fan-out, fan-in & the multiplexer: Replication recipes for global platform di...HostedbyConfluent
This session will dive into our most successful (and unsuccessful!) multi-cluster event replication patterns.
An x-ray of the cross cluster distribution model that powers our globally distributed APIs will touch on the benefits that this model has provided in terms of client API experience, delivery agility and developer experience.
We will focus on recipes for effective use of Mirror Maker event replication to power platform distribution including the challenges of managing a 'fan in' event replication workflow - pulling events created in satellite clusters back to a mothership cluster for processing.
We will introduce the elegant technique of replication event multiplexing - which can be used to simplify the burden of managing a 'fan-in' replication topology by eliminating regional awareness from the application domain and improving replication health monitoring & observability.
Using Kafka as a Database For Real-Time Transaction Processing | Chad Preisle...HostedbyConfluent
You have learned about Kafka event sourcing with streams and using Kafka as a database, but you may be having a tough time wrapping your head around what that means and what challenges you will face. Kafka’s exactly once semantics, data retention rules, and stream DSL make it a great database for real-time transaction processing. This talk will focus on how to use Kafka events as a database. We will talk about using KTables vs GlobalKTables, and how to apply them to patterns we use with traditional databases. We will go over a real-world example of joining events against existing data and some issues to be aware of. We will finish covering some important things to remember about state stores, partitions, and streams to help you avoid problems when your data sets become large.
Mainframe Integration, Offloading and Replacement with Apache Kafka | Kai Wae...HostedbyConfluent
Legacy migration is a journey. Mainframes cannot be replaced in a single project. A big bang will fail. This has to be planned long-term.
Mainframe offloading and replacement with Apache Kafka and its ecosystem can be used to keep a more modern data store in real-time sync with the mainframe, while at the same time persisting the event data on the bus to enable microservices, and deliver the data to other systems such as data warehouses and search indexes.
This session walks through the different steps some companies are already gone through. Technical options like Change Data Capture (CDC), MQ, and third-party tools for mainframe integration, offloading and replacement are explored.
0-330km/h: Porsche's Data Streaming Journey | Sridhar Mamella, PorscheHostedbyConfluent
The auto industry is midst a data revolution that is transforming how companies do business. Once a scarce resource, data has now become abundant and cheap. What are the new technologies that change the way we produce, collect, process, store, and analyze data. What new streams of data are being created with Industry 4.0 and the Internet of Things on the horizon, is there significant value to taking a strategic approach to Fast Data. How is Porsche building the next level Data Streaming Platform with open source technologies and how we are using CI/CD pipelines amongst others in order to serve our use cases.
Kubernetes connectivity to Cloud Native Kafka | Evan Shortiss and Hugo Guerre...HostedbyConfluent
If you want to build an ecosystem of streaming data to your Kafka platform, you will need a much easier way for your developer to quickly move what’s on the source to your cluster. Better yet, making the connector serverless so it would NOT waste any resources for being idle, and having a trusted partner manage your Kafka infrastructure for you. In this session, we will show you how easy we have made streaming data with great user experience. Flexible resource management with our new secret weapon in the Apache Camel project -- Kamelet. We’ll also demonstrate how Red Hat OpenShift Streams for Apache Kafka simplifies the provisioning of Kafka deployments in a public cloud, managing the cluster,topics, and configuring secure access to the Kafka cluster for your developers.
Availability of Kafka - Beyond the Brokers | Andrew Borley and Emma Humber, IBMHostedbyConfluent
While Kafka has guarantees around the number of server failures a cluster can tolerate, to avoid service interruptions, or even data loss, it is prudent to have infrastructure in place for when an environment becomes unavailable during a planned or unplanned outage.
This talk describes the architectures available to you when planning for an outage. We will examine configurations including active/passive and active/active as well as availability zones and debate the benefits and limitations of each. We will also cover how to set up each configuration using the tools in Kafka.
Whether downtime while you fail over clients to a backup is acceptable or you require your Kafka clusters to be highly available, this talk will give you an understanding of the options available to mitigate the impact of the loss of an environment.
How to Discover, Visualize, Catalog, Share and Reuse your Kafka Streams (Jona...HostedbyConfluent
As Kafka deployments grow within your organization, so do the challenges around lifecycle management. For instance, do you really know what streams exist, who is producing and consuming them? What is the effect of upstream changes? How is this information kept up to date, so it is relevant and consistent to others looking to reuse these streams? Ever wish you had a way to view and visualize graphically the relationships between schemas, topics and applications? In this talk we will show you how to do that and get more value from your Kafka Streaming infrastructure using an event portal. It’s like an API portal but specialized for event streams and publish/subscribe patterns. Join us to see how you can automatically discover event streams from your Kafka clusters, import them to a catalog and then leverage code gen capabilities to ease development of new applications.
Building a Modern, Scalable Cyber Intelligence Platform with Apache Kafka | J...HostedbyConfluent
As cyber threats continuously grow in sophistication and frequency, companies need to quickly acclimate to effectively detect, respond, and protect their environments. At Intel, we’ve addressed this need by implementing a modern, scalable Cyber Intelligence Platform (CIP) based on Splunk and Apache Kafka. We believe that CIP positions us for the best defense against cyber threats well into the future.
Our CIP ingests tens of terabytes of data each day and transforms it into actionable insights through streams processing, context-smart applications, and advanced analytics techniques. Kafka serves as a massive data pipeline within the platform. It provides us the ability to operate on data in-stream, enabling us to reduce Mean Time to Detect (MTTD) and Mean Time to Respond (MTTR). Faster detection and response ultimately leads to better prevention.
In our session, we’ll discuss the details described in the IT@Intel white paper that was published in Nov 2020 with same title.
Low-latency real-time data processing at giga-scale with Kafka | John DesJard...HostedbyConfluent
Data volumes continue to grow, demanding new, more scalable solutions for low-latency data processing. Previously, the default approach to deploying such systems was to throw a ton of hardware at the problem. However, that is no longer necessary, as newer technologies showcase a level of efficiency that enables smaller, more manageable clusters while handling extreme workloads. Processing billions of events per second on Kafka can now be done with a modest investment in compute resources. In this session, you will learn how to architect and build the fastest data processing applications that scale linearly, and combine streaming data and reference data data-in-motion and data-at-rest with machine learning. We will take you through the end-to-end framework and example application, built on the Hazelcast Platform, an open source software engine designed for ultra-fast performance. We will also show how you can leverage SQL to further explore the operational data in the solution including querying Kafka topics and key-value data on the in-memory data store. Attendees will also get access to the Github sample application shown.
A Look into the Mirror: Patterns and Best Practices for MirrorMaker2 | Cliff ...HostedbyConfluent
From migrations between Apache Kafka clusters to multi-region deployments across datacenters, the introduction of MirrorMaker2 has expanded the possibilities for Apache Kafka deployments and use cases. In this session you will learn about patterns, best practices, and learnings compiled from running MirrorMaker2 in production at every scale.
Kafka error handling patterns and best practices | Hemant Desale and Aruna Ka...HostedbyConfluent
Transaction Banking from Goldman Sachs is a high volume, latency sensitive digital banking platform offering. We have chosen an event driven architecture to build highly decoupled and independent microservices in a cloud native manner and are designed to meet the objectives of Security, Availability Latency and Scalability. Kafka was a natural choice – to decouple producers and consumers and to scale easily for high volume processing. However, there are certain aspects that require careful consideration – handling errors and partial failures, managing downtime of consumers, secure communication between brokers and producers / consumers. In this session, we will present the patterns and best practices that helped us build robust event driven applications. We will also present our solution approach that has been reused across multiple application domains. We hope that by sharing our experience, we can establish a reference implementation that application developers can benefit from.
Building Scalable Real-Time Data Pipelines with the Couchbase Kafka Connector...HostedbyConfluent
Many organizations use Apache Kafka to facilitate the flow of data between multiple applications or data sources. Thanks to Kafka’s distributed architecture, it is easy to set up a scalable and reliable broker, but doing the same with producers or consumers is quite often a fine art. This session provides a quick overview of Couchbase, describes the Couchbase Kafka Connector, and showcases a demo of how it can be used as both a source and a sink for building real-time data processing pipelines for mission-critical applications.
Supercharge Your Real-time Event Processing with Neo4j's Streams Kafka Connec...HostedbyConfluent
Do your event streams use connected-data domains such as fraud detection, live logistics routing, or predicting network outages? How can you maintain the analysis and leverage those connections real-time?
Graph databases differ from traditional, tabular ones in that they treat connections between data as first class citizens. This means they are optimized for detecting and understanding these relationships – providing insight at speed and at scale.
By combining event streams from Kafka along with the power of the Neo4j graph database for interrogating and investigating connections, you make real-time, event-driven intelligent insight a reality.
Neo4j Streams integrates Neo4j with Apache Kafka event streams, to serve as a source of data, for instance Change Data Capture or a sink to ingest any kind of Kafka event into your graph. In this session we’ll show you how to get up and running with Neo4j Streams to show you how to sink and source between graphs and streams.
Streaming Data Analytics with ksqlDB and Superset | Robert Stolz, PresetHostedbyConfluent
Streaming data systems have been growing rapidly in importance to the modern data stack. Kafka’s kSQL provides an interface for analytic tools that speak SQL. Apache Superset, the most popular modern open-source visualization and analytics solution, plugs into nearly any data source that speaks SQL, including Kafka. Here, we review and compare methods for connecting Kafka to Superset to enable streaming analytics use cases including anomaly detection, operational monitoring, and online data integration.
Kafka Excellence at Scale – Cloud, Kubernetes, Infrastructure as Code (Vik Wa...HostedbyConfluent
Cloud is changing the world; Kubernetes is changing the world; real-time event streaming is changing the world. In this talk we explore some of best practices to synergistically combine the power of these paradigm shifts to achieve a much greater return on your Kafka investments. From declarative deployments, zero-downtime upgrades, elastic scaling to self-healing and automated governance, learn how you can bring the next level of speed, agility, resilience, and security to your Kafka implementations.
Death of the dumb pipes: Using Apache Kafka® for Integration projectsHostedbyConfluent
Guru Sattanathan, Confluent, Senior Solutions Engineer
Enterprise Integration technologies (aka Middleware) are the key enablers when it comes to Real-time data flows or Event Driven Architecture. Starting from real-time payments, e-commerce, travel booking systems, etc, everything is powered by a middleware underneath. It did transform a lot of things but with caveats!
Are ESB’s & MQ’s enough for today’s integration needs? Do you know their technical debts?
If you are someone looking at integrating your applications or an Integration Architect this session is for you. It's time to refresh yourself and see how organizations are building integrations today.
In this session, we will go in this order:
-Recap on Enterprise Integration technologies
-What are the key flaws & What needs improvement?
-What is Apache Kafka?
-Rethinking Integration using Apache Kafka
https://www.meetup.com/KafkaMelbourne/events/280590162/
Building a Modern, Scalable Cyber Intelligence Platform with Apache Kafka | J...HostedbyConfluent
As cyber threats continuously grow in sophistication and frequency, companies need to quickly acclimate to effectively detect, respond, and protect their environments. At Intel, we’ve addressed this need by implementing a modern, scalable Cyber Intelligence Platform (CIP) based on Splunk and Apache Kafka. We believe that CIP positions us for the best defense against cyber threats well into the future.
Our CIP ingests tens of terabytes of data each day and transforms it into actionable insights through streams processing, context-smart applications, and advanced analytics techniques. Kafka serves as a massive data pipeline within the platform. It achieves economies of scale by acquiring data once and consuming it many times. It reduces technical debt by eliminating custom point-to-point connections for producing and consuming data. At the same time, it provides the ability to operate on data in-stream, enabling us to reduce Mean Time to Detect (MTTD) and Mean Time to Respond (MTTR). Faster detection and response ultimately lead to better prevention.
In our session, we’ll discuss the details described in the IT@Intel white paper that was published in Nov 2020 with same title. We’ll share some stream processing techniques, such as filtering and enriching in Kafka to deliver contextually rich data to Splunk and many of our security controls.
Event-driven Applications with Kafka, Micronaut, and AWS Lambda | Dave Klein,...HostedbyConfluent
One of the great things about running applications in the cloud is that you only pay for the resources that you use. But that also makes it more important than ever for our applications to be resource-efficient. This becomes even more critical when we use serverless functions.
Micronaut is an application framework that provides dependency injection, developer productivity features, and excellent support for Apache Kafka. By performing dependency injection, AOP, and other productivity-enhancing magic at compile time, Micronaut allows us to build smaller, more efficient microservices and serverless functions.
In this session, we'll explore the ways that Apache Kafka and Micronaut work together to enable us to build fast, efficient, event-driven applications. Then we'll see it in action, using the AWS Lambda Sink Connector for Confluent Cloud.
The Road Most Traveled: A Kafka Story | Heikki Nousiainen, AivenHostedbyConfluent
When moving to a cloud native architecture Moogsoft knew they needed more scale than Rabbit could provide. Moogsoft moved into Kafka which is known for quick writing and driving heavy event driven workloads on top of niceties such as replayability. Choosing the tool was easy, finding a vendor that ticked all their boxes was not. They needed to ensure scalability, upgradability, builds via existing IAC pipelines, and observability via existing tools. When Moogsoft found Aiven, they were impressed with their offering and ability to scale on demand. During this presentation we will explore how Moogsoft used Aiven for Kafka to manage and scale their data in the cloud.
Guaranteed Event Delivery with Kafka and NodeJS | Amitesh Madhur, NutanixHostedbyConfluent
The business systems of an organization are a continuous source of events. Each system also needs to know about events happening in the other systems. Exchanging these events through direct API calls creates a web of inter-dependencies, is fragile and fails to scale. We examine how this problem can be solved through the use of right integration patterns implemented as a light-weight event hub that leverages the power of Kafka and Confluent to operate at enterprise scale. We demonstrate how JavaScript with its event-driven programming model can be a good fit for implementing an event hub that ensures guaranteed message delivery in the face of failures within the individual subscriber systems.
Many organizations having large engineering teams skilled in NodeJS and a multitude of NodeJs applications. We show how these teams can easily leverage the power of Kafka and scale their applications with the right architectural building blocks. We also offer insights from our own experience of building NodeJS based Kafka applications.
Feed Your SIEM Smart with Kafka Connect (Vitalii Rudenskyi, McKesson Corp) Ka...HostedbyConfluent
SIEM platforms are essential to the new cybersecurity paradigm and data collection layer is a very important piece of it.
When you deliver a new platform, you can easily get lost in a variety of different vendors and solutions, too many challenges are facing. What if I change vendors, will I keep my data? How to feed multiple tools with the same data? How to collect data from custom apps and services? How to pay less for an expensive platform? How to keep data without a huge cost?
Join us if you are looking for the answers. In this session, you will learn how we replaced the vendor-provided data collection layer with kafka connect and the lessons we learnt. After the talk you will know:
- architecture and real-life examples of the flexible and highly available data collection platform
- custom connectors that do most of the work for us and how to extend the connectors to consume new data, we made them open sourced
- easy way to receive data from thousands of servers and many cloud services
- how to archive data at low cost
You will leave armed with a set of free tools and recipes to build a truly vendor-agnostic data collection platform. It will allow you to take you SIEM costs under control. You will feed your analytics tools with what they need and archive the rest at low cost. You will feed your SIEM smart!
How Confluent Completes the Event Streaming Platform (Addison Huddy & Dan Ros...HostedbyConfluent
Apache Kafka fundamentally changes how organizations build and deploy a universal data pipeline that is scalable, reliable, and durable enough to meet the needs of digital-first organizations. However, as powerful as Kafka is today, it’s not an event-streaming platform - and getting it there on your own is a long, complicated, and expensive process. Earlier this year Confluent announced Project Metamorphosis - our plan to bring the best characteristics of cloud native systems to Apache Kafka. Since May we’ve begun transforming Confluent Cloud and Confluent Platform to do just that.
Join two of our Product Managers, Dan Rosanova and Addison Huddy to: Learn how we’ve evolved Confluent Cloud with the first phase of Project Metamorphosis releases
See how Confluent Platform 6.0 brings these transformational, cloud-like qualities to self-managed Kafka
Get a sneak peak of our next Metamorphosis theme and how it impacts your Kafka and event-streaming strategy.
SingleStore & Kafka: Better Together to Power Modern Real-Time Data Architect...HostedbyConfluent
To remain competitive, organizations need to democratize access to fast analytics, not only to gain real-time insights on their business but also to power smart apps that need to react in the moment. In this session, you will learn how Kafka and SingleStore enable modern, yet simple data architecture to analyze both fast paced incoming data as well as large historical datasets. In particular, you will understand why SingleStore is well suited process data streams coming from Kafka.
Exposing and Controlling Kafka Event Streaming with Kong Konnect Enterprise |...HostedbyConfluent
Event streaming allows companies to build more scalable and loosely coupled real-time applications supporting massive concurrency demands and simplifying the construction of services.
At the same time, API management provides capabilities to securely control the upstream services consumption, including the event processing infrastructure.
This session shows how Kong Konnect Enterprise can complement Kafka Event Streaming, exposing it to new and external consumers while applying specific and critical policies to control its consumption, including API key, OAuth/OIDC and others for authentication, rate limiting, caching, log processing, etc.
Understanding Kafka Produce and Fetch api calls for high throughtput applicat...HostedbyConfluent
The data team at Cloudflare uses Kafka to process tens of petabytes a day. All this data is moved using the 2 foundational Kafka api calls: Produce (api key 0) and Fetch (api key 1). Understanding the structure of these calls (and of the underlying RecordSet structure) is key to building high throughput clients.
The talk describes the basics of the Kafka wire protocol (api keys, correlation id), and the structure of the Produce and Fetch calls. It shows how the asynchronous nature of the wire protocol can combine with the structure of the Produce and Fetch calls to increase latency and reduce client throughput; a solution is offered through use of synchronous single-partition calls.
The RecordSet structure, which is used to encode and store sets (batches) of records is described, and its implications on Fetch requests are discussed. The relationship between Fetch api calls and ""consume"" operations is discussed, as is the impact of offset alignment to RecordSet boundaries.
Keeping Analytics Data Fresh in a Streaming Architecture | John Neal, QlikHostedbyConfluent
Qlik is an industry leader across its solution stack, both on the Data Integration side of things with Qlik Replicate (real-time CDC) and Qlik Compose (data warehouse and data lake automation), and on the Analytics side with Qlik Sense. These two “sides” of Qlik are coming together more frequently these days as the need for “always fresh” data increases across organizations.
When real-time streaming applications are the topic du jour, those companies are looking to Apache Kafka to provide the architectural backbone those applications require. Those same companies turn to Qlik Replicate to put the data from their enterprise database systems into motion at scale, whether that data resides in “legacy” mainframe databases; traditional relational databases such as Oracle, MySQL, or SQL Server; or applications such as SAP and SalesForce.
In this session we will look in depth at how Qlik Replicate can be used to continuously stream changes from a source database into Apache Kafka. From there, we will explore how a purpose-built consumer can be used to provide the bridge between Apache Kafka and an analytics application such as Qlik Sense.
5 lessons learned for successful migration to Confluent cloud | Natan Silinit...HostedbyConfluent
Confluent Cloud makes Devops engineers lives a lot more easier.
Yet moving 1500 microservices, 10K topics and 100K partitions to a multi-cluster Confluent cloud can be a challenge.
In this talk you will hear about 5 lessons that Wix has learned in order to successfully meet this challenge.
These lessons include:
1. Automation, Automation, Automation - all the process has to be completely automated at such scale
2. Prefer a gradual approach - E.g. migrate topics in small chunks and not all at once. Reduces risks if things go bad
3. Cleanup first - avoid migrating unused topics or topics with too many unnecessary partitions
Distributed Data Storage & Streaming for Real-time Decisioning Using Kafka, S...HostedbyConfluent
Real-time connectivity of databases and systems is critical in enterprises adopting digital transformation to support super-fast decisioning to drive applications like fraud detection, digital payments, recommendation engines. This talk will focus on the many functions that database streaming serves with Kafka, Spark and Aerospike. We will explore how to eliminate the wall between transaction processing and analytics by synthesizing streaming data with system of record data, to gain key insights in real-time.
RightScale Webinar: So you want to move to the cloud... but you’re not sure what that means, or where you would even start. Or you want to get your feet wet with a proof-of-concept project before you bring out the big guns. We asked Brian Adler, our Professional Services Architect who works directly with customers on cloud projects every single day, to select five cloud projects that you can get started with (and complete!) quickly. In this webinar, Brian and Rafael Saavedra, our VP of Engineering, will walk you through those five projects and will help you demonstrate success in the cloud now.
Low-latency real-time data processing at giga-scale with Kafka | John DesJard...HostedbyConfluent
Data volumes continue to grow, demanding new, more scalable solutions for low-latency data processing. Previously, the default approach to deploying such systems was to throw a ton of hardware at the problem. However, that is no longer necessary, as newer technologies showcase a level of efficiency that enables smaller, more manageable clusters while handling extreme workloads. Processing billions of events per second on Kafka can now be done with a modest investment in compute resources. In this session, you will learn how to architect and build the fastest data processing applications that scale linearly, and combine streaming data and reference data data-in-motion and data-at-rest with machine learning. We will take you through the end-to-end framework and example application, built on the Hazelcast Platform, an open source software engine designed for ultra-fast performance. We will also show how you can leverage SQL to further explore the operational data in the solution including querying Kafka topics and key-value data on the in-memory data store. Attendees will also get access to the Github sample application shown.
A Look into the Mirror: Patterns and Best Practices for MirrorMaker2 | Cliff ...HostedbyConfluent
From migrations between Apache Kafka clusters to multi-region deployments across datacenters, the introduction of MirrorMaker2 has expanded the possibilities for Apache Kafka deployments and use cases. In this session you will learn about patterns, best practices, and learnings compiled from running MirrorMaker2 in production at every scale.
Kafka error handling patterns and best practices | Hemant Desale and Aruna Ka...HostedbyConfluent
Transaction Banking from Goldman Sachs is a high volume, latency sensitive digital banking platform offering. We have chosen an event driven architecture to build highly decoupled and independent microservices in a cloud native manner and are designed to meet the objectives of Security, Availability Latency and Scalability. Kafka was a natural choice – to decouple producers and consumers and to scale easily for high volume processing. However, there are certain aspects that require careful consideration – handling errors and partial failures, managing downtime of consumers, secure communication between brokers and producers / consumers. In this session, we will present the patterns and best practices that helped us build robust event driven applications. We will also present our solution approach that has been reused across multiple application domains. We hope that by sharing our experience, we can establish a reference implementation that application developers can benefit from.
Building Scalable Real-Time Data Pipelines with the Couchbase Kafka Connector...HostedbyConfluent
Many organizations use Apache Kafka to facilitate the flow of data between multiple applications or data sources. Thanks to Kafka’s distributed architecture, it is easy to set up a scalable and reliable broker, but doing the same with producers or consumers is quite often a fine art. This session provides a quick overview of Couchbase, describes the Couchbase Kafka Connector, and showcases a demo of how it can be used as both a source and a sink for building real-time data processing pipelines for mission-critical applications.
Supercharge Your Real-time Event Processing with Neo4j's Streams Kafka Connec...HostedbyConfluent
Do your event streams use connected-data domains such as fraud detection, live logistics routing, or predicting network outages? How can you maintain the analysis and leverage those connections real-time?
Graph databases differ from traditional, tabular ones in that they treat connections between data as first class citizens. This means they are optimized for detecting and understanding these relationships – providing insight at speed and at scale.
By combining event streams from Kafka along with the power of the Neo4j graph database for interrogating and investigating connections, you make real-time, event-driven intelligent insight a reality.
Neo4j Streams integrates Neo4j with Apache Kafka event streams, to serve as a source of data, for instance Change Data Capture or a sink to ingest any kind of Kafka event into your graph. In this session we’ll show you how to get up and running with Neo4j Streams to show you how to sink and source between graphs and streams.
Streaming Data Analytics with ksqlDB and Superset | Robert Stolz, PresetHostedbyConfluent
Streaming data systems have been growing rapidly in importance to the modern data stack. Kafka’s kSQL provides an interface for analytic tools that speak SQL. Apache Superset, the most popular modern open-source visualization and analytics solution, plugs into nearly any data source that speaks SQL, including Kafka. Here, we review and compare methods for connecting Kafka to Superset to enable streaming analytics use cases including anomaly detection, operational monitoring, and online data integration.
Kafka Excellence at Scale – Cloud, Kubernetes, Infrastructure as Code (Vik Wa...HostedbyConfluent
Cloud is changing the world; Kubernetes is changing the world; real-time event streaming is changing the world. In this talk we explore some of best practices to synergistically combine the power of these paradigm shifts to achieve a much greater return on your Kafka investments. From declarative deployments, zero-downtime upgrades, elastic scaling to self-healing and automated governance, learn how you can bring the next level of speed, agility, resilience, and security to your Kafka implementations.
Death of the dumb pipes: Using Apache Kafka® for Integration projectsHostedbyConfluent
Guru Sattanathan, Confluent, Senior Solutions Engineer
Enterprise Integration technologies (aka Middleware) are the key enablers when it comes to Real-time data flows or Event Driven Architecture. Starting from real-time payments, e-commerce, travel booking systems, etc, everything is powered by a middleware underneath. It did transform a lot of things but with caveats!
Are ESB’s & MQ’s enough for today’s integration needs? Do you know their technical debts?
If you are someone looking at integrating your applications or an Integration Architect this session is for you. It's time to refresh yourself and see how organizations are building integrations today.
In this session, we will go in this order:
-Recap on Enterprise Integration technologies
-What are the key flaws & What needs improvement?
-What is Apache Kafka?
-Rethinking Integration using Apache Kafka
https://www.meetup.com/KafkaMelbourne/events/280590162/
Building a Modern, Scalable Cyber Intelligence Platform with Apache Kafka | J...HostedbyConfluent
As cyber threats continuously grow in sophistication and frequency, companies need to quickly acclimate to effectively detect, respond, and protect their environments. At Intel, we’ve addressed this need by implementing a modern, scalable Cyber Intelligence Platform (CIP) based on Splunk and Apache Kafka. We believe that CIP positions us for the best defense against cyber threats well into the future.
Our CIP ingests tens of terabytes of data each day and transforms it into actionable insights through streams processing, context-smart applications, and advanced analytics techniques. Kafka serves as a massive data pipeline within the platform. It achieves economies of scale by acquiring data once and consuming it many times. It reduces technical debt by eliminating custom point-to-point connections for producing and consuming data. At the same time, it provides the ability to operate on data in-stream, enabling us to reduce Mean Time to Detect (MTTD) and Mean Time to Respond (MTTR). Faster detection and response ultimately lead to better prevention.
In our session, we’ll discuss the details described in the IT@Intel white paper that was published in Nov 2020 with same title. We’ll share some stream processing techniques, such as filtering and enriching in Kafka to deliver contextually rich data to Splunk and many of our security controls.
Event-driven Applications with Kafka, Micronaut, and AWS Lambda | Dave Klein,...HostedbyConfluent
One of the great things about running applications in the cloud is that you only pay for the resources that you use. But that also makes it more important than ever for our applications to be resource-efficient. This becomes even more critical when we use serverless functions.
Micronaut is an application framework that provides dependency injection, developer productivity features, and excellent support for Apache Kafka. By performing dependency injection, AOP, and other productivity-enhancing magic at compile time, Micronaut allows us to build smaller, more efficient microservices and serverless functions.
In this session, we'll explore the ways that Apache Kafka and Micronaut work together to enable us to build fast, efficient, event-driven applications. Then we'll see it in action, using the AWS Lambda Sink Connector for Confluent Cloud.
The Road Most Traveled: A Kafka Story | Heikki Nousiainen, AivenHostedbyConfluent
When moving to a cloud native architecture Moogsoft knew they needed more scale than Rabbit could provide. Moogsoft moved into Kafka which is known for quick writing and driving heavy event driven workloads on top of niceties such as replayability. Choosing the tool was easy, finding a vendor that ticked all their boxes was not. They needed to ensure scalability, upgradability, builds via existing IAC pipelines, and observability via existing tools. When Moogsoft found Aiven, they were impressed with their offering and ability to scale on demand. During this presentation we will explore how Moogsoft used Aiven for Kafka to manage and scale their data in the cloud.
Guaranteed Event Delivery with Kafka and NodeJS | Amitesh Madhur, NutanixHostedbyConfluent
The business systems of an organization are a continuous source of events. Each system also needs to know about events happening in the other systems. Exchanging these events through direct API calls creates a web of inter-dependencies, is fragile and fails to scale. We examine how this problem can be solved through the use of right integration patterns implemented as a light-weight event hub that leverages the power of Kafka and Confluent to operate at enterprise scale. We demonstrate how JavaScript with its event-driven programming model can be a good fit for implementing an event hub that ensures guaranteed message delivery in the face of failures within the individual subscriber systems.
Many organizations having large engineering teams skilled in NodeJS and a multitude of NodeJs applications. We show how these teams can easily leverage the power of Kafka and scale their applications with the right architectural building blocks. We also offer insights from our own experience of building NodeJS based Kafka applications.
Feed Your SIEM Smart with Kafka Connect (Vitalii Rudenskyi, McKesson Corp) Ka...HostedbyConfluent
SIEM platforms are essential to the new cybersecurity paradigm and data collection layer is a very important piece of it.
When you deliver a new platform, you can easily get lost in a variety of different vendors and solutions, too many challenges are facing. What if I change vendors, will I keep my data? How to feed multiple tools with the same data? How to collect data from custom apps and services? How to pay less for an expensive platform? How to keep data without a huge cost?
Join us if you are looking for the answers. In this session, you will learn how we replaced the vendor-provided data collection layer with kafka connect and the lessons we learnt. After the talk you will know:
- architecture and real-life examples of the flexible and highly available data collection platform
- custom connectors that do most of the work for us and how to extend the connectors to consume new data, we made them open sourced
- easy way to receive data from thousands of servers and many cloud services
- how to archive data at low cost
You will leave armed with a set of free tools and recipes to build a truly vendor-agnostic data collection platform. It will allow you to take you SIEM costs under control. You will feed your analytics tools with what they need and archive the rest at low cost. You will feed your SIEM smart!
How Confluent Completes the Event Streaming Platform (Addison Huddy & Dan Ros...HostedbyConfluent
Apache Kafka fundamentally changes how organizations build and deploy a universal data pipeline that is scalable, reliable, and durable enough to meet the needs of digital-first organizations. However, as powerful as Kafka is today, it’s not an event-streaming platform - and getting it there on your own is a long, complicated, and expensive process. Earlier this year Confluent announced Project Metamorphosis - our plan to bring the best characteristics of cloud native systems to Apache Kafka. Since May we’ve begun transforming Confluent Cloud and Confluent Platform to do just that.
Join two of our Product Managers, Dan Rosanova and Addison Huddy to: Learn how we’ve evolved Confluent Cloud with the first phase of Project Metamorphosis releases
See how Confluent Platform 6.0 brings these transformational, cloud-like qualities to self-managed Kafka
Get a sneak peak of our next Metamorphosis theme and how it impacts your Kafka and event-streaming strategy.
SingleStore & Kafka: Better Together to Power Modern Real-Time Data Architect...HostedbyConfluent
To remain competitive, organizations need to democratize access to fast analytics, not only to gain real-time insights on their business but also to power smart apps that need to react in the moment. In this session, you will learn how Kafka and SingleStore enable modern, yet simple data architecture to analyze both fast paced incoming data as well as large historical datasets. In particular, you will understand why SingleStore is well suited process data streams coming from Kafka.
Exposing and Controlling Kafka Event Streaming with Kong Konnect Enterprise |...HostedbyConfluent
Event streaming allows companies to build more scalable and loosely coupled real-time applications supporting massive concurrency demands and simplifying the construction of services.
At the same time, API management provides capabilities to securely control the upstream services consumption, including the event processing infrastructure.
This session shows how Kong Konnect Enterprise can complement Kafka Event Streaming, exposing it to new and external consumers while applying specific and critical policies to control its consumption, including API key, OAuth/OIDC and others for authentication, rate limiting, caching, log processing, etc.
Understanding Kafka Produce and Fetch api calls for high throughtput applicat...HostedbyConfluent
The data team at Cloudflare uses Kafka to process tens of petabytes a day. All this data is moved using the 2 foundational Kafka api calls: Produce (api key 0) and Fetch (api key 1). Understanding the structure of these calls (and of the underlying RecordSet structure) is key to building high throughput clients.
The talk describes the basics of the Kafka wire protocol (api keys, correlation id), and the structure of the Produce and Fetch calls. It shows how the asynchronous nature of the wire protocol can combine with the structure of the Produce and Fetch calls to increase latency and reduce client throughput; a solution is offered through use of synchronous single-partition calls.
The RecordSet structure, which is used to encode and store sets (batches) of records is described, and its implications on Fetch requests are discussed. The relationship between Fetch api calls and ""consume"" operations is discussed, as is the impact of offset alignment to RecordSet boundaries.
Keeping Analytics Data Fresh in a Streaming Architecture | John Neal, QlikHostedbyConfluent
Qlik is an industry leader across its solution stack, both on the Data Integration side of things with Qlik Replicate (real-time CDC) and Qlik Compose (data warehouse and data lake automation), and on the Analytics side with Qlik Sense. These two “sides” of Qlik are coming together more frequently these days as the need for “always fresh” data increases across organizations.
When real-time streaming applications are the topic du jour, those companies are looking to Apache Kafka to provide the architectural backbone those applications require. Those same companies turn to Qlik Replicate to put the data from their enterprise database systems into motion at scale, whether that data resides in “legacy” mainframe databases; traditional relational databases such as Oracle, MySQL, or SQL Server; or applications such as SAP and SalesForce.
In this session we will look in depth at how Qlik Replicate can be used to continuously stream changes from a source database into Apache Kafka. From there, we will explore how a purpose-built consumer can be used to provide the bridge between Apache Kafka and an analytics application such as Qlik Sense.
5 lessons learned for successful migration to Confluent cloud | Natan Silinit...HostedbyConfluent
Confluent Cloud makes Devops engineers lives a lot more easier.
Yet moving 1500 microservices, 10K topics and 100K partitions to a multi-cluster Confluent cloud can be a challenge.
In this talk you will hear about 5 lessons that Wix has learned in order to successfully meet this challenge.
These lessons include:
1. Automation, Automation, Automation - all the process has to be completely automated at such scale
2. Prefer a gradual approach - E.g. migrate topics in small chunks and not all at once. Reduces risks if things go bad
3. Cleanup first - avoid migrating unused topics or topics with too many unnecessary partitions
Distributed Data Storage & Streaming for Real-time Decisioning Using Kafka, S...HostedbyConfluent
Real-time connectivity of databases and systems is critical in enterprises adopting digital transformation to support super-fast decisioning to drive applications like fraud detection, digital payments, recommendation engines. This talk will focus on the many functions that database streaming serves with Kafka, Spark and Aerospike. We will explore how to eliminate the wall between transaction processing and analytics by synthesizing streaming data with system of record data, to gain key insights in real-time.
RightScale Webinar: So you want to move to the cloud... but you’re not sure what that means, or where you would even start. Or you want to get your feet wet with a proof-of-concept project before you bring out the big guns. We asked Brian Adler, our Professional Services Architect who works directly with customers on cloud projects every single day, to select five cloud projects that you can get started with (and complete!) quickly. In this webinar, Brian and Rafael Saavedra, our VP of Engineering, will walk you through those five projects and will help you demonstrate success in the cloud now.
This talk covers the Vault 8 team's journey at Capital One where we investigated a wide variety of stream processing solutions to build a next generation real-time decisioning platform to power Capital One's infrastructure.
The result of our analysis showed Apache Storm, Apache Flink, and Apache Apex as prime contenders for our use case with Apache Apex ultimately proving to be the solution of choice based on its present readiness for enterprise deployment and its excellent performance.
Oracle RAC and Your Way to the Cloud by Angelo PruscinoMarkus Michalewicz
Angelo Pruscino, SVP Oracle RAC Development, presents the future of Oracle RAC, including some upcoming technologies and their relevance for the (private) database cloud as part of his Keynote during the DOAG 2014 conference.
Geographically Distributed Multi-Master MySQL ClustersContinuent
Global data access can greatly expand the reach of your business. Continuent's multi-site multi-master (MSMM) solutions enable applications to accept write traffic in multiple locations across on-premises and vCloud Air.
As an example, this includes the following real-world, business-critical use cases:
- Improve performance for globally distributed users registering hardware devices by permitting updates on the geographically closest site
- Ensure availability of credit card processing by spreading transaction processing across two or more sites. Users can still process credit card transactions if a single site is unavailable to them for any reason, including end-user Internet routing problems
- Enable business continuity by using multi-master updates on different hosting providers for service scalability, personalization and software upgrades of GPS devices.
Individual Continuent clusters already provide excellent single-site database availability and performance. In this webinar we review the benefits of combining multiple Continuent clusters into a global multi-site multi-master (MSMM) topology for:
- Optimizing your installation for MSMM
- Optimizing your application for MSMM
- Monitoring and administration
- Failover and recovery of individual servers or entire locations.
Capital One's Next Generation Decision in less than 2 msApache Apex
Slide deck for Capital One's talk on using Apache Apex for their next generation decisioning platform, achieving an ultra-low latency of under 2 ms for decision making, and handling 2,000 events burst at a net rate of 70,000 events/sec.
Sneak Peek into the New ChangeMan ZMF ReleaseNavita Sood
Mainframe Virtual User Group January 28 2016
Peek behind the Serena development curtain and check out the latest features of our new release, ChangeMan ZMF 8.1.1. Last year, we delivered ChangeMan ZMF version 8 which provided innovative release management, unmatched development support, and superior scalability and extendibility.
Features included:
High level language exits (HLLX)
Improved usability with a completely CUA compliant user interface
The ability to develop, deploy, and release changes from Eclipse
Sneak Peek into the New ChangeMan ZMF ReleaseSerena Software
Mainframe Virtual User Group January 28 2016
Peek behind the Serena development curtain and check out the latest features of our new release, ChangeMan ZMF 8.1.1. Last year, we delivered ChangeMan ZMF version 8 which provided innovative release management, unmatched development support, and superior scalability and extendibility.
If you need to build highly performant, mission critical ,microservice-based system following DevOps best practices, you should definitely check Service Fabric!
Service Fabric is one of the most interesting services Azure offers today. It provide unique capabilities outperforming competitor products.
We are seeing global companies start to use Service Fabric for their mission critical solutions.
In this talk we explore the current state of Service Fabric and dive deeper to highlight best practices and design patterns.
We will cover the following topics:
• Service Fabric Core Concepts
• Cluster Planning and Management
• Stateless Services
• Stateful Services
• Actor Model
• Availability and reliability
• Scalability and perfromance
• Diganostics and Monitoring
• Containers
• Testing
• IoT
Live broadcast on https://www.youtube.com/watch?v=Zuxfhpab6xo
Transforming Data Streams with Kafka Connect: An Introduction to Single Messa...HostedbyConfluent
"In this talk, attendees will be provided with an introduction to Kafka Connect and the basics of Single Message Transforms (SMTs) and how they can be used to transform data streams in a simple and efficient way. SMTs are a powerful feature of Kafka Connect that allow custom logic to be applied to individual messages as they pass through the data pipeline. The session will explain how SMTs work, the types of transformations they can be used for, and how they can be applied in a modular and composable way.
Further, the session will discuss where SMTs fit in with Kafka Connect and when they should be used. Examples will be provided of how SMTs can be used to solve common data integration challenges, such as data enrichment, filtering, and restructuring. Attendees will also learn about the limitations of SMTs and when it might be more appropriate to use other tools or frameworks.
Additionally, an overview of the alternatives to SMTs, such as Kafka Streams and KSQL, will be provided. This will help attendees make an informed decision about which approach is best for their specific use case.
Whether attendees are developers, data engineers, or data scientists, this talk will provide valuable insights into how Kafka Connect and SMTs can help streamline data processing workflows. Attendees will come away with a better understanding of how these tools work and how they can be used to solve common data integration challenges."
"While Apache Kafka lacks native support for topic renaming, there are scenarios where renaming topics becomes necessary. This presentation will delve into the utilization of MirrorMaker 2.0 as a solution for renaming Kafka topics. It will illustrate how MirrorMaker 2.0 can efficiently facilitate the migration of messages from the old topic to the new one and how Kafka Connect Metrics can be employed to monitor the mirroring progress. The discussion will encompass the complexity of renaming Kafka topics, addressing certain limitations, and exploring potential workarounds when using MirrorMaker 2.0 for this purpose. Despite not being originally designed for topic renaming, MirrorMaker 2.0 has a suitable solution for renaming Kafka topics.
Blog Post : https://engineering.hellofresh.com/renaming-a-kafka-topic-d6ff3aaf3f03"
Evolution of NRT Data Ingestion Pipeline at TrendyolHostedbyConfluent
"Trendyol, Turkey's leading e-commerce company, is committed to positively impacting the lives of millions of customers. Our decision-making processes are entirely driven by data. As a data warehouse team, our primary goal is to provide accurate and up-to-date data, enabling the extraction of valuable business insights.
We utilize the benefits provided by Kafka and Kafka Connect to facilitate the transfer of data from the source to our analytical environment. We recently transitioned our Kafka Connect clusters from on-premise VMs to Kubernetes. This shift was driven by our desire to effectively manage rapid growth(marked by a growing number of producers, consumers, and daily messages), ensuring proper monitoring and consistency. Consistency is crucial, especially in instances where we employ Single Message Transforms to manipulate records like filtering based on their keys or converting a JSON Object into a JSON string.
Monitoring our cluster's health is key and we achieve this through Grafana dashboards and alerts generated through kube-state-metrics. Additionally, Kafka Connect's JMX metrics, coupled with NewRelic, are employed for comprehensive monitoring.
The session will aim to explain our approach to NRT data ingestion, outlining the role of Kafka and Kafka Connect, our transition journey to K8s, and methods employed to monitor the health of our clusters."
Ensuring Kafka Service Resilience: A Dive into Health-Checking TechniquesHostedbyConfluent
"Join our lightning talk to delve into the strategies vital for maintaining a resilient Kafka service.
While proactive monitoring is key for issue prevention, failures will still occur. Rapid detection tools will enable you to identify and resolve problems before they impact end-users. This session explores the techniques employed by Kafka cloud providers for this detection, many of which are also applicable if you are managing independent Kafka clusters or applications.
The talk focuses on health-checking, a powerful tool that encompasses an application and its monitoring to validate Kafka environment availability. The session navigates through Kafka health-check methods, sharing best practices, identifying common pitfalls, and highlighting the monitoring of critical performance metrics like throughput and latency for early issue detection.
Attendees will gain valuable insights into the art of health-checking their Kafka environment, equipping them with the tools to identify and address issues before they escalate into critical problems. We invite all Kafka enthusiasts to join us in this talk to foster a deeper understanding of Kafka health-checking and ensure the continued smooth operation of your Kafka environment."
Exactly-once Stream Processing with Arroyo and KafkaHostedbyConfluent
"Stream processing systems traditionally gave their users the choice between at least once processing and at most once processing: accepting duplicate data or missing data. But ideally we would provide exactly-once processing, where every event in the input data is represented exactly once in the output.
Kafka provides a transaction API that enables exactly-once when using Kafka as your source and sink. But this API has turned out to not be well suited for use by high level streaming systems, requiring various work arounds to still provide transactional processing.
In this talk, I’ll cover how the transaction API works, and how systems like Arroyo and Flink have used it to build exactly-once support, and how improvements to the transactional API will enable better end-to-end support for consistent stream processing."
"In this talk, we will explore the exciting world of IoT and computer vision by presenting a unique project: Fish Plays Pokemon. Using an ESP Eye camera connected to an ESP32 and other IoT devices, to monitor fish's movements in an aquarium.
This project showcases the power of IoT and computer vision, demonstrating how even a fish can play a popular video game. We will discuss the challenges we faced during development, including real-time processing, IoT device integration, and Kafka message consumption.
By the end of the talk, attendees will have a better understanding of how to combine IoT, computer vision, and the usage of a serverless cloud to create innovative projects. They will also learn how to integrate IoT devices with Kafka to simulate keyboard behavior, opening up endless possibilities for real-time interactions between the physical and digital worlds."
What is tiered storage and what is it good for? After this session you will know how to leverage the tiered storage feature to enable longer retention than the storage attached to brokers allows. You will get acquainted with the different configuration options and know what to expect when you enable the feature, like for example when will the first upload to the remote object storage take place.
Building a Self-Service Stream Processing Portal: How And WhyHostedbyConfluent
"Real-time 24/7 monitoring and verification of massive data is challenging – even more so for the world’s second largest manufacturer of memory chips and semiconductors. Tolerance levels are incredibly small, any small defect needs to be identified and dealt with immediately. The goal of semiconductor manufacturing is to improve yield and minimize unnecessary work.
However, even with real-time data collection, the data was not easy to manipulate by users and it took many days to enable stream processing requests – limiting its usefulness and value to the business.
You’ll hear why SK hynix switched to Confluent and how we developed a self-service stream process portal on top of it. Now users have an easy-to-use service to manipulate the data they want.
Results have been impressive, stream processing requests are available the same day – previously taking 5 days! We were also able to drive down costs by 10% as stream processing requests no longer require additional hardware.
What you’ll take away from our talk:
- What were the pain points in the previous environment
- How we transitioned to Confluent without service downtime
- Creating a self-service stream processing portal built on top of Connect and ksqlDB
- Use case of stream process portal"
From the Trenches: Improving Kafka Connect Source Connector Ingestion from 7 ...HostedbyConfluent
"Discover how default configurations might impact ingestion times, especially when dealing with large files. We'll explore a real-world scenario with a 20,000,000+ line file, assessing metrics and exploring the bottleneck in the default setup. Understand the intricacies of batch size calculations and how to optimize them based on your unique data characteristics.
Walk away with actionable insights as we showcase a practical example, turning a 7-hour ingestion process into a mere 30 minutes for over 30,000,000 records in a Kafka topic. Uncover metrics, configurations, and best practices to elevate the performance of your Kafka Connect CSV source connectors. Don't miss this opportunity to optimize your data pipeline and ensure smooth, efficient data flow."
Future with Zero Down-Time: End-to-end Resiliency with Chaos Engineering and ...HostedbyConfluent
"In order to meet the current and ever-increasing demand for near-zero RPO/RTO systems, a focus on resiliency is critical. While Kafka offers built-in resiliency features, a perfect blend of client and cluster resiliency is necessary in order to achieve a highly resilient Kafka client application.
At Fidelity Investments, Kafka is used for a variety of event streaming needs such as core brokerage trading platforms, log aggregation, communication platforms, and data migrations. In this lightening talk, we will discuss the governance framework that has enabled producers and consumers to achieve their SLAs during unprecedented failure scenarios. We will highlight how we automated resiliency tests through chaos engineering and tightly integrated observability dashboards for Kafka clients to analyze and optimize client configurations. And finally, we will summarize the chaos test suite and the ""test, test and test"" mantra that are helping Fidelity Investments reach its goal of a future with zero down-time."
Navigating Private Network Connectivity Options for Kafka ClustersHostedbyConfluent
"There are various strategies for securely connecting to Kafka clusters between different networks or over the public internet. Many cloud providers even offer endpoints that privately route traffic between networks and are not exposed to the internet. But, depending on your network setup and how you are running Kafka, these options ... might not be an option!
In this session, we’ll discuss how you can use SSH bastions or a self managed PrivateLink endpoint to establish connectivity to your Kafka clusters without exposing brokers directly to the internet. We explain the required network configuration, and show how we at Materialize have contributed to librdkafka to simplify these scenarios and avoid fragile workarounds."
Apache Flink: Building a Company-wide Self-service Streaming Data PlatformHostedbyConfluent
"In my talk, we will examine all the stages of building our self-service Streaming Data Platform based on Apache Flink and Kafka Connect, from the selection of a solution for stateful streaming data processing, right up to the successful design of a robust self-service platform, covering the challenges that we’ve met.
I will share our experience in providing non-Java developers with a company-wide self-service solution, which allows them to quickly and easily develop their streaming data pipelines.
Additionally, I will highlight specific business use cases that would not have been implemented without our platform.0 characters0 characters"
Explaining How Real-Time GenAI Works in a Noisy PubHostedbyConfluent
"Almost everyone has heard about large language models, and tens of millions of people have tried out OpenAI ChatGPT and Google Bard. However, the intricate architecture and underlying mathematics driving these remarkable systems remain elusive to many.
LLM's are fascinating - so let's grab a drink and find out how these systems are built and dive deep into their inner workings. In the length of time it to enjoy a round of drinks, you'll understand the inner workings of these models. We'll take our first sip of word vectors, enjoy the refreshing taste of the transformer, and drain a glass understanding how these models are trained on phenomenally large quantities of data.
Large language models for your streaming application - explained with a little maths and a lot of pub stories"
"Monitoring is a fundamental operation when running Kafka and Kafka applications in production. There are numerous metrics available when using Kafka, however the sheer number is overwhelming, making it challenging to know where to start and how to properly utilise them.
This session will introduce you to some of the key metrics that should be monitored and best practices in fine tuning your monitoring. We will delve into which metrics are the indicators for cluster’s availability and performance and are the most helpful when debugging client applications."
Kafka Streams relies on state restoration for maintaining standby tasks as failure recovery mechanism as well as for restoring the state after rebalance scenarios. When you are scaling up or down your application instances, it is necessary to know the current state of the restoration process for each active and standby task in order to prevent a long restoration process as much as possible. During this presentation, you will get an understanding of how KIP-869 provides valuable information about the current active task restoration after a rebalance and KIP-988 opens a window to the continuous process of standby restoration. When you encounter a situation in which you need to choose whether or not to scale up or down your application instances, both KIPs will be an invaluable ally for you.
Mastering Kafka Producer Configs: A Guide to Optimizing PerformanceHostedbyConfluent
"In this talk, we will dive into the world of Kafka producer configs and explore how to understand and optimize them for better performance. We will cover the different types of configs, their impact on performance, and how to tune them to achieve the best results. Whether you're new to Kafka or a seasoned pro, this session will provide valuable insights and practical tips for improving your Kafka producer performance.
- Introduction to Kafka producer internal and workflow
- Understanding the producer configs like linger.ms, batch.size, buffer.memory and their impact on performance
- Learning about producer configs like max.block.ms, delivery.timeout.ms, request.timeout.ms and retries to make producer more resilient.
- Discuss configs like enable.idempotence, max.in.flight.requests.per.connection and transaction related configs to achieve delivery guarantees.
- Q&A session with attendees to address specific questions and concerns."
Data Contracts Management: Schema Registry and BeyondHostedbyConfluent
"Data contracts are one of the hottest topics in the data management community. A data contract is a formal agreement between a data producer and its consumers, aimed at reducing data downtime and improving data quality. Schemas are an important part of data contracts, but they are not the only relevant element.
In this talk, we’ll:
1. see why data contracts are so important but also difficult to implement;
2. identify the characteristics of a well-designed data contract:
discuss the anatomy of a data contract, its main elements and, how to formally describe them;
3. show how to manage the lifecycle of a data contract leveraging Confluent Platform's services."
"In the realm of stateful stream processing, Apache Flink has emerged as a powerful and versatile platform. However, the conventional SQL-based approach often limits the full potential of Flink applications.
We will delve into the benefits of adopting a code-first approach, which provides developers with greater control over application logic, facilitates complex transformations, and enables more efficient handling of state and time. We will also discuss how the code-first approach can lead to more maintainable and testable code, ultimately improving the overall quality of your Flink applications.
Whether you're a seasoned Flink developer or just starting your journey, this talk will provide valuable insights into how a code-first approach can revolutionize your stream processing applications."
Debezium vs. the World: An Overview of the CDC EcosystemHostedbyConfluent
"Change Data Capture (CDC) has become a commodity in data engineering, much in part due to the ever-rising success of Debezium [1]. But is that all there is? In this lightning talk, we’ll outline the current state of the CDC ecosystem, and understand why adopting a Debezium alternative is still a hard sell. If you’ve ever wondered what else is out there, but can’t keep up with the sprawling of new tools in the ecosystem; we’ll wrap it up for you!
[1] https://debezium.io/"
Beyond Tiered Storage: Serverless Kafka with No Local DisksHostedbyConfluent
"Separation of compute and storage has become the de-facto standard in the data industry for batch processing.
The addition of tiered storage to open source Apache Kafka is the first step in bringing true separation of compute and storage to the streaming world.
In this talk, we'll discuss in technical detail how to take the concept of tiered storage to its logical extreme by building an Apache Kafka protocol compatible system that has zero local disks.
Eliminating all local disks in the system requires not only separating storage from compute, but also separating data from metadata. This is a monumental task that requires reimagining Kafka's architecture from the ground up, but the benefits are worth it.
This approach enables a stateless, elastic, and serverless deployment model that minimizes operational overhead and also drives inter-zone networking costs to almost zero."
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.