This document provides an overview of microservices from Christian Posta, a chief architect at Red Hat. It discusses what microservices are, reasons for using them, common microservices patterns and frameworks, decomposing monolithic applications into microservices, and ensuring resilience between services. The presentation also covers using Kubernetes and OpenShift for microservices and demonstrates sample applications.
Mark Rittman, CTO of Rittman Mead, gave a keynote presentation on big data for Oracle developers and DBAs with a focus on Apache Spark, real-time analytics, and predictive analytics. He discussed how Hadoop can provide flexible, cheap storage for logs, feeds, and social data. He also explained several Hadoop processing frameworks like Apache Spark, Apache Tez, Cloudera Impala, and Apache Drill that provide faster alternatives to traditional MapReduce processing.
SQL Server on Linux will provide the SQL Server database engine running natively on Linux. It allows customers choice in deploying SQL Server on the platform of their choice, including Linux, Windows, and containers. The public preview of SQL Server on Linux is available now, with the general availability target for 2017. It brings the full power of SQL Server to Linux, including features like In-Memory OLTP, Always Encrypted, and PolyBase.
Lance Olson. Cortana Analytics is a fully managed big data and advanced analytics suite that helps you transform your data into intelligent action. Come to this two-part session to learn how you can do "big data" processing and storage in Cortana Analytics. In the first part, we will provide an overview of the processing and storage services. We will then talk about the patterns and use cases which make up most big data solutions. In the second part, we will go hands-on, showing you how to get started today with writing batch/interactive queries, real-time stream processing, or NoSQL transactions all over the same repository of data. Crunch petabytes of data by scaling out your computation power to any sized cluster. Store any amount of unstructured data in its native format with no limits to file or account size. All of this can be done with no hardware to acquire or maintain and minimal time to setup giving you the value of "big data" within minutes. Go to https://channel9.msdn.com/ to find the recording of this session.
The Microsoft Analytics Platform System (APS) is a turnkey appliance that provides a modern data warehouse with the ability to handle both relational and non-relational data. It uses a massively parallel processing (MPP) architecture with multiple CPUs running queries in parallel. The APS includes an integrated Hadoop distribution called HDInsight that allows users to query Hadoop data using T-SQL with PolyBase. This provides a single query interface and allows users to leverage existing SQL skills. The APS appliance is pre-configured with software and hardware optimized to deliver high performance at scale for data warehousing workloads.
You have a legacy system that no longer meet the demands of your current data needs, and replacing it isn’t an option. But don’t panic: Modernizing your traditional enterprise data warehouse is easier than you may think.
Big Data tools are becoming a critical part of enterprise architectures and as such securing the data, at rest, and in motion is a necessity. More so, when you’re implementing these solutions in the cloud and the data doesn't reside within the confines of your trusted data center. Also, there is a fine balance between implementing enterprise-grade security and negotiating utmost performance given the overheads of encryption and/or identity management. This session is designed to tackle these challenges head on and explain the various options available in the cloud. The focal points are the implementation of tools like Ranger and Knox for cloud deployments, but we also pay attention to the security features offered in the cloud that complement this process and secure the data in unprecedented ways. Cloud Security + OSS Security tools are a deadly combination, when it comes to securing your Data Lake.
Cortana Analytics Suite is a fully managed big data and advanced analytics suite that transforms your data into intelligent action. It is comprised of data storage, information management, machine learning, and business intelligence software in a single convenient monthly subscription. This presentation will cover all the products involved, how they work together, and use cases.
Watch the on-demand recording here: https://event.on24.com/wcc/r/1632072/803744C924E8BFD688BD117C6B4B949B Evolution of Big Data and the Role of Analytics | Hybrid Data Management IBM, Driving the future Hybrid Data Warehouse with IBM Integrated Analytics System.
Using Databricks, McGraw-Hill securely transformed itself from a collection of data silos with limited access to data and minimal collaboration to an organization with democratized access to data and machine learning. This ultimately enables its data teams to rapidly identify usage patterns predicting student performance, so they can make timely enhancements to the software that proactively guide at-risk students through the course material. Join our webinar to learn: - How a cloud-based unified analytics platform can help your company perform analytics faster, at lower cost. - How to mitigate challenges presented by data silos so data science teams can collaborate effectively. - How to implement data analytics infrastructure to put models into production quickly
This session will focus on how to get from 'Minimum Viable Product' (MVP) to scale. It will also explain how to deal with unpredictable demand and how to build a scalable business. Attend this session to learn how to: Scale web servers and app services with Elastic Load Balancing and Auto Scaling on Amazon EC2 Scale your storage on Amazon S3 and S3 Reduced Redundancy Storage Scale your database with Amazon DynamoDB, Amazon RDS, and Amazon ElastiCache Scale your customer base by reaching customers globally in minutes with Amazon CloudFront
A modern data warehouse lets you bring together all your data at any scale easily, and to get insights through analytical dashboards, operational reports, or advanced analytics for all your users.
In essence, a data lake is commodity distributed file system that acts as a repository to hold raw data file extracts of all the enterprise source systems, so that it can serve the data management and analytics needs of the business. A data lake system provides means to ingest data, perform scalable big data processing, and serve information, in addition to manage, monitor and secure the it environment. In these slide, we discuss building data lakes using Azure Data Factory and Data Lake Analytics. We delve into the architecture if the data lake and explore its various components. We also describe the various data ingestion scenarios and considerations. We introduce the Azure Data Lake Store, then we discuss how to build Azure Data Factory pipeline to ingest the data lake. After that, we move into big data processing using Data Lake Analytics, and we delve into U-SQL.
In 2017, IBM and Hortonworks formed a strategic partnership to deliver data science and machine learning capabilities to customers, releasing a combined solution that includes the #1 open source platform for Hadoop—Hortonworks Data Platform. Now, the end of support date for IBM BigInsights is fast approaching, on 30 June 2019. In this webinar, we will explain why now is the time to make the move from IBM BigInsights, and how IBM & Hortonworks will support you as you do.
Take Data Management to the next level: Connect Analytics and Machine Learning in a single governed platform consisting of a curated protable open source stack. Run this platform on-prem, hybrid or multicloud, reuse code and models avoid lock-in.
Data science holds tremendous potential for organizations to uncover new insights and drivers of revenue and profitability. Big Data has brought the promise of doing data science at scale to enterprises, however this promise also comes with challenges for data scientists to continuously learn and collaborate. Data Scientists have many tools at their disposal such as notebooks like Juypter and Apache Zeppelin & IDEs such as RStudio with languages like R, Python, Scala and frameworks like Apache Spark. Given all the choices how do you best collaborate to build your model and then work through the development lifecycle to deploy it from test into production ? In this session learn the attributes of a modern data science platform that empowers data scientists to build models using all the data in their data lake and foster continuous learning and collaboration. We will show a demo of DSX with HDP with the focus on integration, security and model deployment and management. Speakers: Sriram Srinivasan, Senior Technical Staff Member, Analytics Platform Architect, IBM Vikram Murali, Program Director, Data Science and Machine Learning, IBM
Fast Data is the application of big data analytics to large data sets, in real-time or near real-time, to solve a problem or create business value.
What's the origin of Big Data? What are the real life usage scenarios where Hadoop has been successfully adopted? How do you get started within your organizations?
We consider a microservices architecture to achieve an end goal, not because it's "the cool thing to do". Every organization looking to adopt this architecture must realize (and adhere) to a set of foundational principles. Guided by those principles, we can correctly choose the technology to help support a microservices architecture and meet our end goals. This talk explains those core principles and gives you the tools needed for your microservices journey.
A presentation on why or why not microservices, why a platform is important, discovering how to break down a monolith and some of the challenges you'll face (data, transactions, boundaries, etc). Last section is on Istio and service mesh introductions. Follow on twitter @christianposta for updates and more details
The document discusses Christian Posta's journey with microservices architectures. It begins by explaining why organizations are moving to microservices and defines microservices. It then covers related topics like cloud platforms, container technologies like Kubernetes and OpenShift, benefits and drawbacks of microservices, and tools for developing microservices like Docker, Kubernetes, OpenShift, and Camel.
Christian Posta is a principal middleware specialist and architect who has worked with large microservices architectures. He discusses why companies are moving to microservices and cloud platforms like Kubernetes and OpenShift. He covers characteristics of microservices like small autonomous teams and decentralized decision making. Posta also discusses breaking applications into independent services, shedding dependencies between teams, and using contracts and APIs for communication between services.
As companies move to become digital, we can get sidetracked and distracted by some of the changes in the technology landscape. Ideally we will be harnessing technology to solve the problems we have and leverage it to deliver software faster and safer. In this talk, I'll we'll take a look at some new technology trends in the open-source communities and when and how to use them.
10 yrs ago, SOA promised a lot of the same things Microservices promise use today. So where did we go wrong? What makes microservices different? In this talk, we discussed from an architectural view how we went sideways with SOA, why we must embrace things like Domain Driven Design and scaled-out architectures, and how microservices can be built with enterprises in mind. We also cover a step-by-step, in-depth tutorial that covers these concepts.
This document summarizes one organization's journey from a monolithic application architecture to a microservices architecture. It describes some of the pains of maintaining a monolithic application. It then discusses strategies for breaking the monolith into independently deployable microservices at low risk, including identifying module boundaries, deploying and releasing services independently, virtualizing data integration, and using traffic mirroring. The goal is to increase development velocity while lowering risk.
When building microservices, you must solve for a number of critical functions, but the process can be incredibly complex and expensive to maintain. Christian Posta offers an overview of Envoy Proxy and Istio.io Service Mesh, explaining how they solve application networking problems more elegantly by pushing these concerns down to the infrastructure layer and demonstrating how it all works.
Cloud-native describes a way of building applications on a cloud platform to iteratively discover and deliver business value. We now have access to a lot of similar technology that the large internet companies pioneered and used to their advantage to dominate their respective markets. What challenges arise when we start building applications to take advantage of this new technology? In this mini-conference, we'll cover what it means to build applications with microservices, how cloud-native integration and concepts like service mesh have evolved to solve some of those problems, and how the next iteration of application development with Functions as a Service (FaaS) and serverless computing fit into this landscape. You'll hear from industry experts Burr Sutter and Christian Posta who recently authored a book Introducing Istio Service Mesh for Microservices about these topics. Attendees should come away from this mini-conference with the following: Understanding of what cloud-native means and how to use it to influence positive business outcomes How integration has evolved to create, connect and manage cloud-native APIs How service-mesh technology like Istio can solve the challenges introduced with cloud-native applications How the next iteration of applications deliver with FaaS and serverless computing fits in with a world of monoliths, microservices, and APIs These talks will be of value for developers, architects, operators, platform directors, and technology leaders. After the presentations, please stay and join Christian, Burr and your peers for networking, food and drinks. All attendees will also receive a copy of Christian and Burr's new book: Introducing Istio Service Mesh for Microservices.
SpringOne Platform 2016 Speakers: Christopher Tretina; Director, Comcast & Vipul Savjani; Director of PaaS, Accenture Comcast is embarking on a multi-year application modernization and transformation journey to achieve application resiliency, velocity and cost optimization at enterprise scale. We will discuss how we are addressing significant technical architecture, engineering, and delivery challenges faced in transformation of Comcast’s Enterprise Services Platform (ESP) from SOA architecture to Cloud-Native architecture using Microservices, DevOps, and PaaS.
Cloud-native describes a way of building applications on a cloud platform to iteratively discover and deliver business value. We now have access to a lot of similar technology that the large internet companies pioneered and used to their advantage to dominate their respective markets. What challenges arise when we start building applications to take advantage of this new technology? In this talk we'll explore the role of service meshes when building distributed systems, why they make sense, and where they don't make sense. We will look at a class of problem that crops up that service mesh cannot solve, but that frameworks and even new programming languages like Ballerina are aiming to solve
This document discusses transitioning from monolithic applications to microservices and serverless architectures. It begins by defining technical debt and explaining how microservices can help pay it down incrementally. It then covers different architectural styles like monoliths and microservices. The rest of the document discusses moving to cloud infrastructure, breaking apart monolithic applications into independent services, communication between services, leveraging third-party services, and security considerations for microservices.
The document discusses microservices for Java developers. It introduces Christian Posta, a principal middleware specialist and architect who works with large microservices and is a blogger and speaker on topics like DevOps, integration, and microservices. It then discusses how creating value through software is about speed, iteration, and continuous improvement. It covers concepts like distributed configuration, service discovery, load balancing, circuit breakers, and versioning/routing that are important for microservices. Finally, it mentions container cluster management with Kubernetes and technologies like Kubernetes, OpenShift, and Fabric8 that can help with microservices development.
This document discusses microservices architectures and emerging technologies to support them. It introduces Envoy proxy as a sidecar proxy that implements common microservices patterns like circuit breaking and load balancing. It then introduces Istio as a control plane that manages Envoy proxies and provides higher-level capabilities like traffic management, security, and observability across microservices. The presentation argues that 2018 will be the year of service meshes, with Istio being a prominent example for managing microservices communication using Envoy proxies.
A quick overview of application networking and microservice resilience and how a service mesh like Istio.io can help alleviate some of this pain.
Personal customer experiences are and will be more and more vital. People to people, but also people to machine. Today, there are several providers of the same services, and the new ones are faster, more flexible, and more personalized in their communications with their customers & users. How do we ensure that we provide the right information to our employees as well as to our customers so they can better serve and increase customer satisfaction? This webinar will focus on how you as an organization will have to restructure, rethink and redesign your technological platform to support increasing employee- and customer demands. Key takeaways: Holistic understanding of how to make a successful cloud transition Learn why modern organizations excel in customer treatment, productivity, flexibility, and agility High-level architecture and how and why DevOps changes organizations
More and more organizations are turning to DevOps as a way of working together to improve the efficiency and quality of software delivery and start adding more value to the business. But what exactly is DevOps and what does it mean for you and your organization? Join Microsoft Data Platform MVP Kendra Little to discover: • What is DevOps and what benefits can it offer your organization? • Who in your organization should be involved in DevOps? • Why should your organization adopt DevOps? • How can your organization start implementing DevOps?
I Love APIs 2015 Chris Munns, Amazon @chrismunns http://www.amazon.com/ As computing costs decreased and computing power grew over time, so increased the complexity of the problems computers were called to solve and complexity of software. Enterprise applications quickly went through the stage of monolithic applications to client-server to multiple tier and beyond – to the land of massively distributed architectures. We arrived at the point where enterprise software is well beyond the capability of a single person or even a reasonably practical group of people to understand and control. Are microsevices the answer? Join Chris Munns to learn about how microservices are scaled at Amazon.
This document summarizes a presentation about DevOps practices at Trend Micro. It discusses: - How Trend Micro moved infrastructure to AWS to relieve operations staff and enable more flexible scaling. This allowed faster development cycles through continuous integration and continuous delivery. - They use AWS services like CloudFormation, OpsWorks, CodePipeline and CloudWatch to automate infrastructure provisioning and application deployments. Infrastructure and applications are defined through templates. - Lessons learned include fully utilizing CloudFormation to manage resources, parameterizing templates, and being aware of limits when automating at scale with services like OpsWorks.
We explain the history of our agile organization with a focus on the latest round of evolution of our Product and Engineering organization, moving from business-oriented feature teams to mission teams.
In 2022 we heard your GitOps questions at meetups and gatherings, big stages and local panels and one question was often top of mind: how do I get started? The benefits of GitOps are calling your name, but getting started isn’t that straightforward. Red Hat is excited to kick off 2023 with a DevNation TechTalk, focused on GitOps to help you sift through your questions. At DevNation you’ll hear from passionate GitOps practitioners about the pitfalls to avoid and hurdles to jump while kicking off or evolving your GitOps practices. This event is aimed at audiences that are new to GitOps or early in their practice development within a cloud native environment. During this live session you’ll learn: Upcoming updates and key milestones in the ArgoCD roadmap and how Red Hat will support them How to simplify the delivery GitOps across multi-cloud environments GitOps best practices from experts at: PostNord Strålfors: Filip Jansson Arbetsförmedlingen: Misho Kmetovski & Richard Hermansson Swiss Railways (SBB): Manuel Wallrapp & Thomas Bruederli Plus stick around for an “Ask me Anything” segment to ask any outstanding questions live.
Modern cloud-native applications are incredibly complex systems. Keeping the systems healthy and meeting SLAs for our customers is crucial for long-term success. In this session, we will dive into the three pillars of observability - metrics, logs, tracing - the foundation of successful troubleshooting in distributed systems. You'll learn the gotchas and pitfalls of rolling out the OpenTelemetry stack on Kubernetes to effectively collect all your signals without worrying about a vendor lock in. Additionally we will replace parts of the Prometheus stack to scrape metrics with OpenTelemetry collector and operator.
GitHub plays a key role in the everyday work of thousands of developers and is a central piece of the open-source software ecosystem. Even though it is getting better and better every day, it still misses some key features that we need. If you want a better way of reviewing PRs, navigating through the code or better yet - writing the code without leaving the browser - this talk is for you! This talk will be demo driven, and as the title suggests, we will start with the aesthetic revamp. But we definitely won’t stop there! You will also learn a few cool things about interacting with GitHub through the command line. So not only your UI will be officially revamped, but you will also gain a productivity boost.
The Quarkus Quinoa extension takes care of all the web UI build/wiring/dev-mode hassles and lets you focus on your web application logic. In this tech talk, we’ll bring a shopping list app to life with Quarkus, Hibernate as a backend, and React as a frontend. Quinoa will be the glue that makes it all work seamlessly from dev to production.
This document discusses using metrics to monitor Quarkus applications. It recommends metrics like throughput, memory usage, queue time, average response time, and error rates. It explains how Quarkus supports Micrometer for instrumenting applications with metrics and integrating with monitoring systems. The document includes a demo of adding metrics to code. It provides tips for using annotations and tags to gain more insights from metrics. Source code examples are linked.
This talk will teach you how to redesign an event-driven autoscaling architecture for cloud-native microservices by utilizing Apache Kafka, Knative, and KEDA infrastructure. You will also learn how to deploy serverless applications (Quarkus) using a Knative service. Finally, KEDA will enable you to autoscale Knative Eventing components (KafkaSource) through events consumption over standard resources (CPU, memory).
Loom is among the most highly anticipated projects in the Java world. It promises to address concurrency and Java execution model issues by providing virtual threads. Thus, there is no need to write concurrent programs using asynchronous or reactive APIs; it will be possible to use the traditional imperative model and let Loom handle the rest. The JVM will execute the program and leverage non-blocking APIs automatically! Sounds good, doesn't it? How does it work, though? Are there any hidden costs? What is Loom going to change in modern Java frameworks? We will answer these questions in this talk. Starting with the integration of Loom in Quarkus, we will compare the different approaches we considered, discuss their respective pros and cons, and show how Loom might change the Java world.
Quarkus Renarde 🦊♥ is a new Web framework based on Quarkus. This framework focuses not on microservices but web applications and makes Quarkus even easier to use for web apps: - Endpoints based on convention, even easier than RESTEasy Reactive and JAX-RS - Server-side templating with Qute - Validation with Hibernate Validation - Data with Hibernate ORM or Reactive with Panache - Simple authentication with OpenID Connect or WebAuthn Quarkus Renarde 🦊♥ can deliver all this while still providing the joy of developing with Quarkus, with live reload, continuous testing, the Dev, and more.
This document summarizes a talk about running containers without Docker. It discusses alternatives like Podman and Buildah that can replace Docker functionality. The talk demonstrates installing and using Podman to run containers, Buildah to build images from Dockerfiles, and Skopeo to copy images between registries. The presentation encourages understanding containers beyond just Docker and knowing other tools in the ecosystem.
Hybrid-cloud and multi-cloud patterns are the next application deployment architectures, and Kubernetes is the de facto container orchestration engine. 50% of production Kubernetes workloads involve some form of microservices applications. How can we manage this inter-cluster application connectivity? Meet Skupper: an open-source project that solves multi-cloud communication for Kubernetes. In this Tech Talk, you will briefly learn about Skupper and watch a live demo of an e-commerce application with 10 microservices spanning three OpenShift clusters running on three different public cloud providers.
In this workshop, you’ll learn an easy way to incorporate data science and AI/ML into an OpenShift development workflow. As an example, you’ll use an object detection model to detect ‘dog(s)’ in an image. You will: Use Jupyter Notebooks and TensorFlow to explore a pre-trained object detection model Serve the model in a REST API as a Flask App Use Source-to-Image (S2I) to build and deploy the Flask app Explore Kafka streams from Notebooks Deploy a Kafka consumer with the same object detection model You’ll be able to do all of this without having to install anything on your own computer, thanks to Red Hat OpenShift Data Science and Red Hat OpenShift Streams for Apache Kafka. Note: Beginner data handling and Python skills are required for this workshop.
DevOps solved the conflict between development and operations, but other essential aspects of the delivery lifecycle—security, compliance, and audit—were left out. DevSecOps is an excellent reminder that security must be DevOps’d, but compliance and audit are still missing. There’s no need for a new DevSecAuditComplianceOps buzzword; instead, let’s talk about continuous authorization, which applies Zero Trust principles to continuous monitoring. In this tech talk, Bill Bensing will discuss practical ways to start with continuous authorization for the software delivery lifecycle using Ploigos.
What's your favorite IDE? VS Code? IDEA? Eclipse? Visual Studio? The right IDE is fundamental to your productivity as a developer, but you might need something else to become more outstanding. Why don't we take a look at your terminal? Come to this session to learn eleven CLI tools that will boost your developer productivity.
We will dissect the world famous todo app that provides a REST API (which is the foundation of microservices) with data backed by Apache Cassandra. We will leverage the TODO MVC and the TODO backend projects with the back end that we will build with Quarkus and Cassandra. Attendees will get an overview of Cassandra, including the driver for Quarkus. Through live coding (that attendees can try out later) in a cloud-based environment, primarily in Quarkus and Cassandra, attendees will understand how to implement and connect the APIs to the backend and leverage the generic client(s)provided. After attending this session attendees will walk away with a good understanding of implementing microservices using Cassandra and Quarkus. They will also get a working knowledge of how Astra (Cassandra as a service) can be leveraged in other solutions.
Every software developer wants more productivity. What if the only commands you needed to deploy were "git commit" and "git push"? Join us as we walk you through a live demonstration of how you can ship your lovely application code from your local machine to a free OpenShift cluster, fully automated through GitHub Actions. By the end of this session, you'll have a sound understanding of building a GitHub Action workflow for your codebase that leverages OpenShift to deploy your application.
Since moving to a 6 monthly release cadence, the Java platform is evolving more dynamically than ever before. It can be quite a challenge to stay on top of all the changes and new features. In this talk we're going to explore the most important developments in the Java API: which classes have been added, and what has been removed? Join Duke, the Java mascot, for a trip to space and learn which exciting new APIs provided by the Java platform can help him with his journey: The Java Vector API for utilizing the SIMD capabilities of modern CPU architectures The Foreign Linker API for integrating with native code The JFR Event Streaming API for publishing JDK Flight Recorder Events We'll also take a look at some useful changes to the Java runtime, such as CDS archives for a faster spaceship..., uhm, application launch!
Did you know that OpenJDK comes with Java Flight Recorder (JFR), an embedded production time profiler? Cryostat provides easy and secure access to JFR across container boundaries so you can profile that performance bottleneck, or find that annoying bug. Join this session to learn about using Cryostat to profile Java applications in production on OpenShift.
This document discusses Apache Kafka and Red Hat OpenShift Streams for Apache Kafka. It begins with an overview of what Apache Kafka is and its common use cases. It then demonstrates how Red Hat OpenShift Streams provides a managed Apache Kafka cluster as a service, including a dedicated cluster, configuration management, metrics, monitoring and other features to provide a streamlined developer experience. It concludes with information on trying OpenShift Streams for Apache Kafka and additional resources.
With Kubernetes, implementing security policies can be challenging. First, developers, administrators, and security teams need to understand security policies in collaboration to have the best chance of successful adoption. Next, policy enforcement needs to integrate with developer workflows. Lastly, policies need to contain corrective action that is as close to the developer as possible. KubeLinter solves these problems by linting Kubernetes YAML files and Helm charts at the source: the developer. In this session, we will evaluate KubeLinter by moving through a hands-on demo of the application, showing a use case for local machines and CI pipeline integration, and chatting about how best to integrate it into your organization: KubeLinter, and its default checks How you can leverage the application in your day-to-day operations The open source StackRox community
Many modern video games are constantly evolving post-release. New maps, game modes, and game balancing adjustments are rolled out, often on a weekly basis. This continuous iteration to improve player engagement and satisfaction requires data-driven decision making based on events and telemetry captured during gameplay, and from community forums and discussions. In this session you will learn how OpenShift Streams for Apache Kafka and Kafka Streams can be used to analyze real-time events and telemetry reported by a game server, using a practical example that encourages audience participation. Specifically you’ll learn how to: Provision Kafka clusters on OpenShift Streams for Apache Kafka. Develop a Java application that uses Kafka Streams and Quarkus to process event data. Deploy the application locally, or on OpenShift and connect it to your OpenShift Streams for Apache Kafka Cluster.
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In this talk, we will explore strategies to optimize the success rate of storing and retaining new information. We will discuss scientifically proven ideal learning intervals and content structures. Additionally, we will examine how to create an environment that improves our focus while you remain in the “flow”. Lastly we will also address the influence of AI on learning capabilities. In the dynamic field of software development, this knowledge will empower you to accelerate your learning curve and support others in their learning journeys.