Building Cloud-Native App Series - Part 11 of 11
Microservices Architecture Series
Service Mesh - Observability
- Zipkin
- Prometheus
- Grafana
- Kiali
Apache Kafka Scalable Message Processing and more! Guido Schmutz
media streams and Internet of Things. Events have to be accepted quickly and reliably, they have to be distributed and analysed, often with many consumers or systems interested in all or part of the events. How can me make sure that all these event are accepted and forwarded in an efficient and reliable way? This is where Apache Kafaka comes into play, a distirbuted, highly-scalable messaging broker, build for exchanging huge amount of messages between a source and a target.
This session will start with an introduction into Apache and presents the role of Apache Kafka in a modern data / information architecture and the advantages it brings to the table. Additionally the Kafka ecosystem will be covered as well as the integration of Kafka in the Oracle Stack, with products such as Golden Gate, Service Bus and Oracle Stream Analytics all being able to act as a Kafka consumer or producer.
Building Cloud-Native App Series - Part 3 of 11
Microservices Architecture Series
AWS Kinesis Data Streams
AWS Kinesis Firehose
AWS Kinesis Data Analytics
Apache Flink - Analytics
Designing For Multicloud, CF Summit Frankfurt 2016Mark D'Cunha
Your carefully planned cloud strategy and technology architecture is useless, because multicloud changes everything. In this session, we will explore what multicloud means and why your business will force it upon you.
We provide examples of customers successfully using multicloud models, identify early patterns of usage and how to leverage them. You’ll learn about how Cloud Foundry provides unique capabilities to simplify and implement multicloud deployments. We’ll cover how you can use features like service brokers, service plans, asynchronous provisioning and arbitrary parameters to deploy muilticloud, while still maintaining a consistent experience for your application developers and IT operations staff.
Building Cloud-Native App Series - Part 2 of 11
Microservices Architecture Series
Event Sourcing & CQRS,
Kafka, Rabbit MQ
Case Studies (E-Commerce App, Movie Streaming, Ticket Booking, Restaurant, Hospital Management)
Partner Development Guide for Kafka Connectconfluent
This guide is intended to provide useful background to developers implementing Kafka Connect sources and sinks for their data stores. Visit www.confluent.io for more information.
Building Cloud-Native App Series - Part 11 of 11
Microservices Architecture Series
Service Mesh - Observability
- Zipkin
- Prometheus
- Grafana
- Kiali
Apache Kafka Scalable Message Processing and more! Guido Schmutz
media streams and Internet of Things. Events have to be accepted quickly and reliably, they have to be distributed and analysed, often with many consumers or systems interested in all or part of the events. How can me make sure that all these event are accepted and forwarded in an efficient and reliable way? This is where Apache Kafaka comes into play, a distirbuted, highly-scalable messaging broker, build for exchanging huge amount of messages between a source and a target.
This session will start with an introduction into Apache and presents the role of Apache Kafka in a modern data / information architecture and the advantages it brings to the table. Additionally the Kafka ecosystem will be covered as well as the integration of Kafka in the Oracle Stack, with products such as Golden Gate, Service Bus and Oracle Stream Analytics all being able to act as a Kafka consumer or producer.
Building Cloud-Native App Series - Part 3 of 11
Microservices Architecture Series
AWS Kinesis Data Streams
AWS Kinesis Firehose
AWS Kinesis Data Analytics
Apache Flink - Analytics
Designing For Multicloud, CF Summit Frankfurt 2016Mark D'Cunha
Your carefully planned cloud strategy and technology architecture is useless, because multicloud changes everything. In this session, we will explore what multicloud means and why your business will force it upon you.
We provide examples of customers successfully using multicloud models, identify early patterns of usage and how to leverage them. You’ll learn about how Cloud Foundry provides unique capabilities to simplify and implement multicloud deployments. We’ll cover how you can use features like service brokers, service plans, asynchronous provisioning and arbitrary parameters to deploy muilticloud, while still maintaining a consistent experience for your application developers and IT operations staff.
Building Cloud-Native App Series - Part 2 of 11
Microservices Architecture Series
Event Sourcing & CQRS,
Kafka, Rabbit MQ
Case Studies (E-Commerce App, Movie Streaming, Ticket Booking, Restaurant, Hospital Management)
Partner Development Guide for Kafka Connectconfluent
This guide is intended to provide useful background to developers implementing Kafka Connect sources and sinks for their data stores. Visit www.confluent.io for more information.
Apache Kafka - Scalable Message-Processing and more !Guido Schmutz
Independent of the source of data, the integration of event streams into an Enterprise Architecture gets more and more important in the world of sensors, social media streams and Internet of Things. Events have to be accepted quickly and reliably, they have to be distributed and analysed, often with many consumers or systems interested in all or part of the events. How can me make sure that all these event are accepted and forwarded in an efficient and reliable way? This is where Apache Kafaka comes into play, a distirbuted, highly-scalable messaging broker, build for exchanging huge amount of messages between a source and a target.
This session will start with an introduction into Apache and presents the role of Apache Kafka in a modern data / information architecture and the advantages it brings to the table. Additionally the Kafka ecosystem will be covered as well as the integration of Kafka in the Oracle Stack, with products such as Golden Gate, Service Bus and Oracle Stream Analytics all being able to act as a Kafka consumer or producer.
Making Kafka Cloud Native | Jay Kreps, Co-Founder & CEO, ConfluentHostedbyConfluent
A talk discussing the rise of Apache Kafka and data in motion plus the impact of cloud native data systems. This talk will cover how Kafka needs to evolve to keep up with the future of cloud, what this means for distributed systems engineers, and what work is being done to truly make Kafka Cloud Native
Event Streaming with Kafka Streams and Spring Cloud Stream | Soby Chacko, VMwareHostedbyConfluent
Spring Cloud Stream is a framework built on top of the foundations of Spring Boot, the foremost JVM framework for developing microservice applications. It brings the familiar patterns and philosophies that Spring has championed for years through its programming model by allowing developers to focus primarily on the business logic of their applications. Kafka Streams is a powerful stream processing library built on top of Apache Kafka and attracts many developers because of its simplicity and deployment models as microservice applications. By developing Kafka Streams applications using Spring Cloud Stream, application developers get the best of both worlds - simpler stream processing execution models of Kafka Streams and battle-tested microservices foundations of Spring Boot via Spring Cloud Stream. This talk will explore: The integration points and various capabilities of Spring Cloud Stream touchpoints with Kafka Streams How to build event streaming applications using Spring’s programming model built on top of Kafka Streams, including a demo of a stateful application using Kafka Streams and Spring Cloud Stream’s functional support How to use interactive queries to expose materialized views from the state stores in the application How this Kafka Streams application can run as part of a data pipeline using Spring Cloud Data Flow in Kubernetes
Building Cloud-Native App Series - Part 1 of 11
Microservices Architecture Series
Design Thinking, Lean Startup, Agile (Kanban, Scrum),
User Stories, Domain-Driven Design
Redis and Kafka - Advanced Microservices Design Patterns SimplifiedAllen Terleto
The adoption and popularity of the microservices architecture continues to grow across a spectrum of enterprises in every industry. Although a consensus on an implementation standard has yet to be reached, advanced design patterns and lessons learned about the complexities and pitfalls of deploying microservices at scale have been established by thought leaders and the development community. With Redis and Kafka becoming de facto standards across most microservices architectures, we will discuss how their combination can be used to simplify the implementation of event-driven design patterns that will provide real-time performance, scalability, resiliency, traceability to ensure compliance, observability, reduced technology sprawl, and scale to thousands of services. In this discussion, we will decompose a real-time event-driven payment-processing microservices workflow to explore capturing telemetry data, event sourcing, CQRS, orchestrated SAGA workflows, inter-service communication, state machines, and more.
Modern Cloud-Native Streaming Platforms: Event Streaming Microservices with K...confluent
Microservices, events, containers, and orchestrators are dominating our vernacular today. As operations teams adapt to support these technologies in production, cloud-native platforms like Cloud Foundry and Kubernetes have quickly risen to serve as force multipliers of automation, productivity and value. Kafka is providing developers a critically important component as they build and modernize applications to cloud-native architecture. This talk will explore:
• Why cloud-native platforms and why run Kafka on Kubernetes?
• What kind of workloads are best suited for this combination?
• Tips to determine the path forward for legacy monoliths in your application portfolio
• Running Kafka as a Streaming Platform on Container Orchestration
Spark (Structured) Streaming vs. Kafka Streams - two stream processing platfo...Guido Schmutz
Independent of the source of data, the integration and analysis of event streams gets more important in the world of sensors, social media streams and Internet of Things. Events have to be accepted quickly and reliably, they have to be distributed and analyzed, often with many consumers or systems interested in all or part of the events. In this session we compare two popular Streaming Analytics solutions: Spark Streaming and Kafka Streams.
Spark is fast and general engine for large-scale data processing and has been designed to provide a more efficient alternative to Hadoop MapReduce. Spark Streaming brings Spark's language-integrated API to stream processing, letting you write streaming applications the same way you write batch jobs. It supports both Java and Scala.
Kafka Streams is the stream processing solution which is part of Kafka. It is provided as a Java library and by that can be easily integrated with any Java application.
Should you use traditional REST APIs to bind services together? Or is it better to use a richer, more loosely-coupled protocol? This talk will dig into how we piece services together in event driven systems, how we use a distributed log (event hub) to create a central, persistent history of events and what benefits we achieve from doing so. Apache Kafka is a perfect match for building such an asynchronous, loosely-coupled event-driven backbone. Events trigger processing logic, which can be implemented in a more traditional as well as in a stream processing fashion. The talk will show the difference between a request-driven and event-driven communication and show when to use which. It highlights how the modern stream processing systems can be used to
hold state both internally as well as in a database and how this state can be used to further increase independence of other services, the primary goal of a Microservices architecture.
Webinar | Better Together: Apache Cassandra and Apache KafkaDataStax
In this webinar, you’ll also be introduced to DataStax Apache Kafka Connector, and get a brief demonstration of this groundbreaking technology. You’ll directly experience how this tool can help you stream data from Kafka topics into DataStax Enterprise versions of Cassandra. The future of your organization won’t wait. Register now to reserve your spot in this exciting new webinar.
Youtube: https://youtu.be/HmkNb8twUNk
Lessons Learned Building a Connector Using Kafka Connect (Katherine Stanley &...confluent
While many companies are embracing Apache Kafka as their core event streaming platform they may still have events they want to unlock in other systems. Kafka Connect provides a common API for developers to do just that and the number of open-source connectors available is growing rapidly. The IBM MQ sink and source connectors allow you to flow messages between your Apache Kafka cluster and your IBM MQ queues. In this session I will share our lessons learned and top tips for building a Kafka Connect connector. I’ll explain how a connector is structured, how the framework calls it and some of the things to consider when providing configuration options. The more Kafka Connect connectors the community creates the better, as it will enable everyone to unlock the events in their existing systems.
Lessons Learned Building a Connector Using Kafka Connect (Katherine Stanley &...confluent
While many companies are embracing Apache Kafka as their core event streaming platform they may still have events they want to unlock in other systems. Kafka Connect provides a common API for developers to do just that and the number of open-source connectors available is growing rapidly. The IBM MQ sink and source connectors allow you to flow messages between your Apache Kafka cluster and your IBM MQ queues. In this session we will share our lessons learned and top tips for building a Kafka Connect connector. We'll explain how a connector is structured, how the framework calls it and some of the things to consider when providing configuration options. The more Kafka Connect connectors the community creates the better, as it will enable everyone to unlock the events in their existing systems.
Apache Kafka - Scalable Message-Processing and more !Guido Schmutz
Independent of the source of data, the integration of event streams into an Enterprise Architecture gets more and more important in the world of sensors, social media streams and Internet of Things. Events have to be accepted quickly and reliably, they have to be distributed and analysed, often with many consumers or systems interested in all or part of the events. How can me make sure that all these event are accepted and forwarded in an efficient and reliable way? This is where Apache Kafaka comes into play, a distirbuted, highly-scalable messaging broker, build for exchanging huge amount of messages between a source and a target.
This session will start with an introduction into Apache and presents the role of Apache Kafka in a modern data / information architecture and the advantages it brings to the table. Additionally the Kafka ecosystem will be covered as well as the integration of Kafka in the Oracle Stack, with products such as Golden Gate, Service Bus and Oracle Stream Analytics all being able to act as a Kafka consumer or producer.
Making Kafka Cloud Native | Jay Kreps, Co-Founder & CEO, ConfluentHostedbyConfluent
A talk discussing the rise of Apache Kafka and data in motion plus the impact of cloud native data systems. This talk will cover how Kafka needs to evolve to keep up with the future of cloud, what this means for distributed systems engineers, and what work is being done to truly make Kafka Cloud Native
Event Streaming with Kafka Streams and Spring Cloud Stream | Soby Chacko, VMwareHostedbyConfluent
Spring Cloud Stream is a framework built on top of the foundations of Spring Boot, the foremost JVM framework for developing microservice applications. It brings the familiar patterns and philosophies that Spring has championed for years through its programming model by allowing developers to focus primarily on the business logic of their applications. Kafka Streams is a powerful stream processing library built on top of Apache Kafka and attracts many developers because of its simplicity and deployment models as microservice applications. By developing Kafka Streams applications using Spring Cloud Stream, application developers get the best of both worlds - simpler stream processing execution models of Kafka Streams and battle-tested microservices foundations of Spring Boot via Spring Cloud Stream. This talk will explore: The integration points and various capabilities of Spring Cloud Stream touchpoints with Kafka Streams How to build event streaming applications using Spring’s programming model built on top of Kafka Streams, including a demo of a stateful application using Kafka Streams and Spring Cloud Stream’s functional support How to use interactive queries to expose materialized views from the state stores in the application How this Kafka Streams application can run as part of a data pipeline using Spring Cloud Data Flow in Kubernetes
Building Cloud-Native App Series - Part 1 of 11
Microservices Architecture Series
Design Thinking, Lean Startup, Agile (Kanban, Scrum),
User Stories, Domain-Driven Design
Redis and Kafka - Advanced Microservices Design Patterns SimplifiedAllen Terleto
The adoption and popularity of the microservices architecture continues to grow across a spectrum of enterprises in every industry. Although a consensus on an implementation standard has yet to be reached, advanced design patterns and lessons learned about the complexities and pitfalls of deploying microservices at scale have been established by thought leaders and the development community. With Redis and Kafka becoming de facto standards across most microservices architectures, we will discuss how their combination can be used to simplify the implementation of event-driven design patterns that will provide real-time performance, scalability, resiliency, traceability to ensure compliance, observability, reduced technology sprawl, and scale to thousands of services. In this discussion, we will decompose a real-time event-driven payment-processing microservices workflow to explore capturing telemetry data, event sourcing, CQRS, orchestrated SAGA workflows, inter-service communication, state machines, and more.
Modern Cloud-Native Streaming Platforms: Event Streaming Microservices with K...confluent
Microservices, events, containers, and orchestrators are dominating our vernacular today. As operations teams adapt to support these technologies in production, cloud-native platforms like Cloud Foundry and Kubernetes have quickly risen to serve as force multipliers of automation, productivity and value. Kafka is providing developers a critically important component as they build and modernize applications to cloud-native architecture. This talk will explore:
• Why cloud-native platforms and why run Kafka on Kubernetes?
• What kind of workloads are best suited for this combination?
• Tips to determine the path forward for legacy monoliths in your application portfolio
• Running Kafka as a Streaming Platform on Container Orchestration
Spark (Structured) Streaming vs. Kafka Streams - two stream processing platfo...Guido Schmutz
Independent of the source of data, the integration and analysis of event streams gets more important in the world of sensors, social media streams and Internet of Things. Events have to be accepted quickly and reliably, they have to be distributed and analyzed, often with many consumers or systems interested in all or part of the events. In this session we compare two popular Streaming Analytics solutions: Spark Streaming and Kafka Streams.
Spark is fast and general engine for large-scale data processing and has been designed to provide a more efficient alternative to Hadoop MapReduce. Spark Streaming brings Spark's language-integrated API to stream processing, letting you write streaming applications the same way you write batch jobs. It supports both Java and Scala.
Kafka Streams is the stream processing solution which is part of Kafka. It is provided as a Java library and by that can be easily integrated with any Java application.
Should you use traditional REST APIs to bind services together? Or is it better to use a richer, more loosely-coupled protocol? This talk will dig into how we piece services together in event driven systems, how we use a distributed log (event hub) to create a central, persistent history of events and what benefits we achieve from doing so. Apache Kafka is a perfect match for building such an asynchronous, loosely-coupled event-driven backbone. Events trigger processing logic, which can be implemented in a more traditional as well as in a stream processing fashion. The talk will show the difference between a request-driven and event-driven communication and show when to use which. It highlights how the modern stream processing systems can be used to
hold state both internally as well as in a database and how this state can be used to further increase independence of other services, the primary goal of a Microservices architecture.
Webinar | Better Together: Apache Cassandra and Apache KafkaDataStax
In this webinar, you’ll also be introduced to DataStax Apache Kafka Connector, and get a brief demonstration of this groundbreaking technology. You’ll directly experience how this tool can help you stream data from Kafka topics into DataStax Enterprise versions of Cassandra. The future of your organization won’t wait. Register now to reserve your spot in this exciting new webinar.
Youtube: https://youtu.be/HmkNb8twUNk
Lessons Learned Building a Connector Using Kafka Connect (Katherine Stanley &...confluent
While many companies are embracing Apache Kafka as their core event streaming platform they may still have events they want to unlock in other systems. Kafka Connect provides a common API for developers to do just that and the number of open-source connectors available is growing rapidly. The IBM MQ sink and source connectors allow you to flow messages between your Apache Kafka cluster and your IBM MQ queues. In this session I will share our lessons learned and top tips for building a Kafka Connect connector. I’ll explain how a connector is structured, how the framework calls it and some of the things to consider when providing configuration options. The more Kafka Connect connectors the community creates the better, as it will enable everyone to unlock the events in their existing systems.
Lessons Learned Building a Connector Using Kafka Connect (Katherine Stanley &...confluent
While many companies are embracing Apache Kafka as their core event streaming platform they may still have events they want to unlock in other systems. Kafka Connect provides a common API for developers to do just that and the number of open-source connectors available is growing rapidly. The IBM MQ sink and source connectors allow you to flow messages between your Apache Kafka cluster and your IBM MQ queues. In this session we will share our lessons learned and top tips for building a Kafka Connect connector. We'll explain how a connector is structured, how the framework calls it and some of the things to consider when providing configuration options. The more Kafka Connect connectors the community creates the better, as it will enable everyone to unlock the events in their existing systems.
Containerize Legacy .NET Framework Web Apps for Cloud MigrationAmazon Web Services
In this session, we cover how to leverage Docker for Windows and the Amazon Elastic Container Service (Amazon ECS) as an effective solution for migrating legacy .NET applications to the cloud.We use Microsoft Visual Studio to demonstrate how to containerize a legacy .NET app including the Docker build and deployment process.We also cover how to deploy the container to Amazon ECS using the Amazon EC2 Container Registry (Amazon ECR) service to host the Docker image.
Simplify Cloud Applications using Spring CloudRamnivas Laddad
Developing an application to a cloud platform involves working with deployed application's environment and connecting to services. Spring Cloud, a new project, simplifies these tasks in a variety of cloud platforms including Cloud Foundry and Heroku. Spring Cloud makes it possible to deploy the same artifact (a war or a jar) to multiple cloud environments. It supports multiple clouds through the concept of Cloud Connector and provides out of the box implementation for Cloud Foundry and Heroku. Spring Cloud is designed for extension, making it simple to create a cloud connector for other cloud platforms. Spring Cloud also supports connecting to multiple services through the concept of service connectors. Out of the box, it provides support for many common services, but also makes it easy to extend it to other services. While Spring Cloud can be used by applications using any JVM language and framework, it further simplifies Spring applications through Java and XML-based configuration. In this talk, we will introduce the Spring Cloud project, show how you can simplify configuring applications for cloud deployment, discuss its extensibility mechanism, and put it to good use by showing practical examples from the field.
JSpring Virtual 2020 - Reacting to an event-driven worldGrace Jansen
We now live in a world with data at its heart. The amount of data being produced every day is growing exponentially and a large amount of this data is in the form of events. Whether it be updates from sensors, clicks on a website or even tweets, applications are bombarded with a never-ending stream of new events. So, how can we architect our applications to be more reactive and resilient to these fluctuating loads and better manage our thirst for data? In this session explore how Kafka and Reactive application architecture can be combined in applications to better handle our modern data needs.
Following simple patterns of good application design can allow you to scale your application for your customers easily. We'll dive into the 12 factor application design and demo how this applies to containers and deployments on Amazon ECS and Fargate. We'll take a look at tooling that can be used to simplify your work flow and help you adopt the principles of the 12 factor application.
Following simple patterns of good application design can allow you to scale your application for your customers easily. We'll dive into the 12 factor application design and demo how this applies to containers and deployments on Amazon ECS and Fargate. We'll take a look at tooling that can be used to simplfy your work flow and help you adopt the principles of the 12 factor application.
Virtual Meetup Sweden - Reacting to an event driven worldGrace Jansen
We now live in a world with data at its heart. The amount of data being produced every day is growing exponentially and a large amount of this data is in the form of events. Whether it be updates from sensors, clicks on a website or even tweets, applications are bombarded with a never-ending stream of new events. So, how can we architect our applications to be more reactive and resilient to these fluctuating loads and better manage our thirst for data? In this session explore how Kafka and Reactive application architecture can be combined in applications to better handle our modern data needs.
How do you break a monolithic application into microservices? Learn how AWS delivers the integrated building blocks to support the move to containerized microservices for any application architecture, regardless of scale, load, or complexity. Learn more about the newly released AWS App Mesh and how it makes it easy to monitor and control containerized microservices. We will explore different options for running containers on AWS, such as AWS Fargate (serverless containers), EKS, and ECS.
JLove conference 2020 - Reacting to an Event-Driven WorldGrace Jansen
We now live in a world with data at its heart. The amount of data being produced every day is growing exponentially and a large amount of this data is in the form of events. Whether it be updates from sensors, clicks on a website or even tweets, applications are bombarded with a never-ending stream of new events. So, how can we architect our applications to be more reactive and resilient to these fluctuating loads and better manage our thirst for data? In this session explore how Kafka and Reactive application architecture can be combined in applications to better handle our modern data needs.
Jfokus - Reacting to an event-driven worldGrace Jansen
We now live in a world with data at its heart. The amount of data being produced every day is growing exponentially and a large amount of this data is in the form of events. Whether it be updates from sensors, clicks on a website or even tweets, applications are bombarded with a never-ending stream of new events. So, how can we architect our applications to be more reactive and resilient to these fluctuating loads and better manage our thirst for data? In this session explore how Kafka and Reactive application architecture can be combined in applications to better handle our modern data needs.
DevNexus - Reacting to an event driven worldGrace Jansen
We now live in a world with data at its heart. The amount of data being produced every day is growing exponentially and a large amount of this data is in the form of events. Whether it be updates from sensors, clicks on a website or even tweets, applications are bombarded with a never-ending stream of new events. So, how can we architect our applications to be more reactive and resilient to these fluctuating loads and better manage our thirst for data? In this session explore how Kafka and Reactive application architecture can be combined in applications to better handle our modern data needs.
PartnerSkillUp_Enable a Streaming CDC SolutionTimothy Spann
PartnerSkillUp_Enable a Streaming CDC Solution
Tim Spann
Principal Developer Advocate in Data In Motion for Cloudera, Global
https://attend.cloudera.com/skillupseriesseptember14
Streaming Change Data Capture (CDC) Two Unique Ways
In this next session,
learn how to use Debezium with Flink, Kafka, and NiFi for Change Data Capture using two different mechanisms: Kafka Connect and Flink SQL.
With the virtual nature of today's world, streaming data is more critical than ever. Join Cloudera Chief Data-In-Motion Principal, Tim Spann, and Partner Solution Engineer, Salvador Alamazan as they look closely at key CDC use cases, discuss why Debezium is the best option for handling CDC and use examples to show you how to demonstrate value.
This is a must-attend experience!
Zoom Webinar
September 14, 2023
10:00am–11:00am EDT
FLaNK Stack
Apache NiFi
Apache Flink
Apache Kafka
Kafka Connect
Flink SQL
Cloudera DataFlow
Cloudera SQL Stream Builder
Cloudera Streams Messages Manager
Debezium
Postgresql
IBM DB2
Oracle DB
Running Kafka in Kubernetes: A Practical Guide (Katherine Stanley, IBM United...confluent
The rise of Apache Kafka as the de facto standard for event streaming has coincided with the rise of Kubernetes for cloud-native applications. While Kubernetes is a great choice for any distributed system, that doesn’t mean it is easy to deploy and maintain a Kafka cluster running on it. At IBM we have hands-on experience with running Kafka in Kubernetes and in this session I will share our top tips for a smooth ride. I will show an example deployment of Kafka on Kubernetes and step through the system to explain the common pitfalls and how to avoid them. This will include the Kubernetes objects to use, resource considerations and connecting applications to the cluster. Finally, I will discuss useful Kafka metrics to include in Kubernetes liveness and readiness probes.
Deploy and scale your first cloud application with Amazon Lightsail - CMP202 ...Amazon Web Services
In this session, learn how to deploy a two-tier LAMP stack web app using Amazon Lightsail, and learn how to scale your app with load balancers and snapshots. Also learn how to migrate your application so you can leverage Amazon EC2 and Amazon Relational Database Service (Amazon RDS). By the end of this session, you’ll understand the best practices for deploying applications on Lightsail, and you’ll know when it’s best to choose Lightsail, Amazon EC2, or Amazon RDS.
Webinar: Flink SQL in Action - Fabian HueskeVerverica
Stream processing is rapidly adopted by the enterprise. While in the past, stream processing frameworks mostly provided Java or Scala-based APIs, stream processing with SQL is recently gaining a lot of attention because it makes stream processing accessible to non-programmers and significantly reduces the effort to solve common tasks.
About three years ago, the Apache Flink community started adding SQL support to process static and streaming data in a unified fashion. Today, Flink SQL powers production systems at Alibaba, Huawei, Lyft, and Uber. In this talk, I will discuss the current state of Flink’s SQL support and explain the importance of Flink’s unified approach to process static and streaming data. Once the basics are covered, I will present common real-world use cases ranging from low-latency ETL to pattern detection and demonstrate how easily they can be addressed by Flink SQL.
Building a Critical Communications Platform Using Serverless TechnologiesAmazon Web Services
By adopting serverless technologies, one organization managed to both accelerate its internal development process and improve operational scalability. In this tech talk, we present optimization strategies for AWS Lambda, followed by the inner workings of a critical communications platform built on serverless technologies. We also share best practices relevant to the development environment and architecture, along with the lessons learned.
Any team that has made the jump from building monoliths to building microservices knows the complexities you must overcome to build a system that is functional and maintainable. Building a microservice architecture that is low latency and only communicates using REST APIs is even more tricky, with high latency for requests being a common concern. This talk explains how you can use events as the backbone of your microservice architecture and build an efficient, event-driven system. It covers how to get started with designing your microservice architecture and the key requirements any system needs to fulfil. It also introduces the different patterns you will encounter in event-driven architectures and the advantages and disadvantages of these choices. Finally it explains why Apache Kafka is a great choice for event-driven microservices.
IBM Message Hub is a new Bluemix service based on Apache Kafka for messaging in the cloud. It's ideal for linking together microservices to build a scalable, flexible application in the cloud. It's great for feeding data at speed into other services such as analytics. You can also use it to bridge securely from your enterprise MQ systems into the cloud.
Effectively Managing a Hybrid Messaging EnvironmentAndrew Schofield
MQ has always made it easy to retain control over your messaging infrastructure, allowing infrastructure teams to safely serve the needs of many different and disparate applications on the same MQ network. However, the current trends towards allowing development teams more autonomy and control over the infrastructure needs could threaten this stability and is often a cause of tension between application and infrastructure teams. I discuss how to exploit the new and existing features and controls in MQ (such as the addition of MQ Light API and connectivity to IBM Message Hub) to ease these tensions and enable effective collaboration between teams.
Introducing IBM Message Hub: Cloud-scale messaging based on Apache KafkaAndrew Schofield
IBM Message Hub is a new Bluemix service for messaging in the cloud. It's ideal for linking together microservices to build a scalable, flexible application in the cloud. It's great for feeding data at speed into other services such as analytics. You can also use it to bridge securely from your enterprise MQ systems into the cloud.
IBM Message Hub service in Bluemix - Apache Kafka in a public cloudAndrew Schofield
This talk was presented at the Kafka Meetup London meeting on 20 January 2016. You can find more information about Message Hub here: http://ibm.biz/message-hub-bluemix-catalog
Come and learn how to easily connect IBM MessageSight to your enterprise systems to get the full benefits from the Internet of Things and Mobile. We'll cover connecting to IBM Integration Bus (IIB), MQ, Application Servers, and analytics with InfoSphere Streams.
An introduction to IBM MessagSight, IBM's gateway to the Internet of Things and Mobile Messaging. As the Internet of Things and M2M become more pervasive are you ready to engage and get the benefits? Do you want to get the benefits of rapid, reliable messaging in the mobile world? This session will cover an introduction to MessageSight, latest updates and an introduction to MQTT.
May Marketo Masterclass, London MUG May 22 2024.pdfAdele Miller
Can't make Adobe Summit in Vegas? No sweat because the EMEA Marketo Engage Champions are coming to London to share their Summit sessions, insights and more!
This is a MUG with a twist you don't want to miss.
Graspan: A Big Data System for Big Code AnalysisAftab Hussain
We built a disk-based parallel graph system, Graspan, that uses a novel edge-pair centric computation model to compute dynamic transitive closures on very large program graphs.
We implement context-sensitive pointer/alias and dataflow analyses on Graspan. An evaluation of these analyses on large codebases such as Linux shows that their Graspan implementations scale to millions of lines of code and are much simpler than their original implementations.
These analyses were used to augment the existing checkers; these augmented checkers found 132 new NULL pointer bugs and 1308 unnecessary NULL tests in Linux 4.4.0-rc5, PostgreSQL 8.3.9, and Apache httpd 2.2.18.
- Accepted in ASPLOS ‘17, Xi’an, China.
- Featured in the tutorial, Systemized Program Analyses: A Big Data Perspective on Static Analysis Scalability, ASPLOS ‘17.
- Invited for presentation at SoCal PLS ‘16.
- Invited for poster presentation at PLDI SRC ‘16.
Providing Globus Services to Users of JASMIN for Environmental Data AnalysisGlobus
JASMIN is the UK’s high-performance data analysis platform for environmental science, operated by STFC on behalf of the UK Natural Environment Research Council (NERC). In addition to its role in hosting the CEDA Archive (NERC’s long-term repository for climate, atmospheric science & Earth observation data in the UK), JASMIN provides a collaborative platform to a community of around 2,000 scientists in the UK and beyond, providing nearly 400 environmental science projects with working space, compute resources and tools to facilitate their work. High-performance data transfer into and out of JASMIN has always been a key feature, with many scientists bringing model outputs from supercomputers elsewhere in the UK, to analyse against observational or other model data in the CEDA Archive. A growing number of JASMIN users are now realising the benefits of using the Globus service to provide reliable and efficient data movement and other tasks in this and other contexts. Further use cases involve long-distance (intercontinental) transfers to and from JASMIN, and collecting results from a mobile atmospheric radar system, pushing data to JASMIN via a lightweight Globus deployment. We provide details of how Globus fits into our current infrastructure, our experience of the recent migration to GCSv5.4, and of our interest in developing use of the wider ecosystem of Globus services for the benefit of our user community.
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I ...Juraj Vysvader
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I didn't get rich from it but it did have 63K downloads (powered possible tens of thousands of websites).
Check out the webinar slides to learn more about how XfilesPro transforms Salesforce document management by leveraging its world-class applications. For more details, please connect with sales@xfilespro.com
If you want to watch the on-demand webinar, please click here: https://www.xfilespro.com/webinars/salesforce-document-management-2-0-smarter-faster-better/
Zoom is a comprehensive platform designed to connect individuals and teams efficiently. With its user-friendly interface and powerful features, Zoom has become a go-to solution for virtual communication and collaboration. It offers a range of tools, including virtual meetings, team chat, VoIP phone systems, online whiteboards, and AI companions, to streamline workflows and enhance productivity.
First Steps with Globus Compute Multi-User EndpointsGlobus
In this presentation we will share our experiences around getting started with the Globus Compute multi-user endpoint. Working with the Pharmacology group at the University of Auckland, we have previously written an application using Globus Compute that can offload computationally expensive steps in the researcher's workflows, which they wish to manage from their familiar Windows environments, onto the NeSI (New Zealand eScience Infrastructure) cluster. Some of the challenges we have encountered were that each researcher had to set up and manage their own single-user globus compute endpoint and that the workloads had varying resource requirements (CPUs, memory and wall time) between different runs. We hope that the multi-user endpoint will help to address these challenges and share an update on our progress here.
Code reviews are vital for ensuring good code quality. They serve as one of our last lines of defense against bugs and subpar code reaching production.
Yet, they often turn into annoying tasks riddled with frustration, hostility, unclear feedback and lack of standards. How can we improve this crucial process?
In this session we will cover:
- The Art of Effective Code Reviews
- Streamlining the Review Process
- Elevating Reviews with Automated Tools
By the end of this presentation, you'll have the knowledge on how to organize and improve your code review proces
Introducing Crescat - Event Management Software for Venues, Festivals and Eve...Crescat
Crescat is industry-trusted event management software, built by event professionals for event professionals. Founded in 2017, we have three key products tailored for the live event industry.
Crescat Event for concert promoters and event agencies. Crescat Venue for music venues, conference centers, wedding venues, concert halls and more. And Crescat Festival for festivals, conferences and complex events.
With a wide range of popular features such as event scheduling, shift management, volunteer and crew coordination, artist booking and much more, Crescat is designed for customisation and ease-of-use.
Over 125,000 events have been planned in Crescat and with hundreds of customers of all shapes and sizes, from boutique event agencies through to international concert promoters, Crescat is rigged for success. What's more, we highly value feedback from our users and we are constantly improving our software with updates, new features and improvements.
If you plan events, run a venue or produce festivals and you're looking for ways to make your life easier, then we have a solution for you. Try our software for free or schedule a no-obligation demo with one of our product specialists today at crescat.io
Software Engineering, Software Consulting, Tech Lead, Spring Boot, Spring Cloud, Spring Core, Spring JDBC, Spring Transaction, Spring MVC, OpenShift Cloud Platform, Kafka, REST, SOAP, LLD & HLD.
Atelier - Innover avec l’IA Générative et les graphes de connaissancesNeo4j
Atelier - Innover avec l’IA Générative et les graphes de connaissances
Allez au-delà du battage médiatique autour de l’IA et découvrez des techniques pratiques pour utiliser l’IA de manière responsable à travers les données de votre organisation. Explorez comment utiliser les graphes de connaissances pour augmenter la précision, la transparence et la capacité d’explication dans les systèmes d’IA générative. Vous partirez avec une expérience pratique combinant les relations entre les données et les LLM pour apporter du contexte spécifique à votre domaine et améliorer votre raisonnement.
Amenez votre ordinateur portable et nous vous guiderons sur la mise en place de votre propre pile d’IA générative, en vous fournissant des exemples pratiques et codés pour démarrer en quelques minutes.
Innovating Inference - Remote Triggering of Large Language Models on HPC Clus...Globus
Large Language Models (LLMs) are currently the center of attention in the tech world, particularly for their potential to advance research. In this presentation, we'll explore a straightforward and effective method for quickly initiating inference runs on supercomputers using the vLLM tool with Globus Compute, specifically on the Polaris system at ALCF. We'll begin by briefly discussing the popularity and applications of LLMs in various fields. Following this, we will introduce the vLLM tool, and explain how it integrates with Globus Compute to efficiently manage LLM operations on Polaris. Attendees will learn the practical aspects of setting up and remotely triggering LLMs from local machines, focusing on ease of use and efficiency. This talk is ideal for researchers and practitioners looking to leverage the power of LLMs in their work, offering a clear guide to harnessing supercomputing resources for quick and effective LLM inference.
Understanding Nidhi Software Pricing: A Quick Guide 🌟
Choosing the right software is vital for Nidhi companies to streamline operations. Our latest presentation covers Nidhi software pricing, key factors, costs, and negotiation tips.
📊 What You’ll Learn:
Key factors influencing Nidhi software price
Understanding the true cost beyond the initial price
Tips for negotiating the best deal
Affordable and customizable pricing options with Vector Nidhi Software
🔗 Learn more at: www.vectornidhisoftware.com/software-for-nidhi-company/
#NidhiSoftwarePrice #NidhiSoftware #VectorNidhi
Technology choices for Apache Kafka and Change Data Capture
1. Technology Choices for Kafka
and Change Data Capture
Kate Stanley and Andrew Schofield
Apache Kafka London Meetup October 2019
IBM Event StreamsApache Kafka