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.
GraalVM is a high-performance, polyglot VM that can run programs in different languages. It addresses issues with the JVM like performance, startup times, updates, and legacy code. GraalVM uses an optimizing compiler called Graal that can make programs 2-5 times faster than the default C2 compiler through optimizations like inlining and partial escape analysis. Programs can also be compiled to native using SubstrateVM for faster startup times and lower memory footprint, but with less dynamic behavior. Quarkus addresses this by allowing the use of JVM frameworks like Spring and Hibernate within a GraalVM native environment.
The introduction covers the following
1. What are Microservices and why should be use this paradigm?
2. 12 factor apps and how Microservices make it easier to create them
3. Characteristics of Microservices
Note: Please download the slides to view animations.
There are quite many talks about Quarkus, explaining basic development mechanics and advertising extremely small memory footprint and slim deployment artifacts. However in all those talks audience has just to "believe", almost nobody explains, how does Quarkus achieve it, what tools and approaches work under the hood. I'm going to provide a balanced explanation, giving knowledge of how it works behind the scenes, but not going into long complex theoretical stories, which make people sleep during the talk.
1. Docker EE will include an unmodified Kubernetes distribution to provide orchestration capabilities alongside Docker Swarm.
2. When running mixed workloads across orchestrators, resource contention is a risk and it is recommended to separate workloads by orchestrator on each node for now.
3. Docker EE aims to address the shortcomings of running mixed workloads to better support this in the future.
D. Andreadis, Red Hat: Concepts and technical overview of QuarkusUni Systems S.M.S.A.
Dimitris Andreadis, Director of Engineering and Manager of the Quarkus Team at Red Hat, discusses the History, Concepts and Technical Overview of Quarkus framework. The webinar was delivered on June 25, 2020
Quarkus offers a great development experience. In this session, I’ll introduce you to the power of Quarkus Live Coding and tools that are useful to developers for debugging, deploying, and testing Quarkus applications.
Build and Deploy Cloud Native Camel Quarkus routes with Tekton and KnativeOmar Al-Safi
In this talk, we will leverage all cloud native stacks and tools to build Camel Quarkus routes natively using GraalVM native-image on Tekton pipeline and deploy these routes to Kubernetes cluster with Knative installed. We will dive into the following topics in the talk: - Introduction to Camel - Introduction to Camel Quarkus - Introduction to GraalVM Native Image - Introduction to Tekon - Introduction to Knative - Demo shows how to deploy end to end a Camel Quarkus route which include the following steps: - Look at whole deployment pipeline for Cloud Native Camel Quarkus routes - Build Camel Quarkus routes with GraalVM native-image on Tekton pipeline. - Deploy Camel Quarkus routes to Kubernetes cluster with Knative Targeted Audience: Users with basic Camel knowledge
Empowering Your Java Applications with Quarkus. A New Era of Fast, Efficient,...Ivelin Yanev
In this informative presentation, we delve into the exciting world of Quarkus, a cutting-edge Java framework that has been revolutionizing the way we build and deploy Java applications. Quarkus is much more than just another framework; it represents a new era in Java development, characterized by speed, efficiency, and a cloud-native approach
1) Event-driven microservices involve microservices communicating primarily through events published to an event backbone. This loosely couples microservices and allows for eventual data consistency.
2) Apache Kafka is an open-source streaming platform that can be used to build an event backbone, allowing microservices to reliably publish and subscribe to events. It supports streaming, storage, and processing of event data.
3) Common patterns for event-driven microservices include database per service for independent data ownership, sagas for coordinated multi-step processes, event sourcing to capture all state changes, and CQRS to separate reads from writes.
We start with an introduction to what Apache Camel is, and how you can use Camel to make integration much easier. Allowing you to focus on your business logic, rather than low level messaging protocols, and transports. You will also hear what other features Camel provides out of the box, which can make integration much easier for you.
We look into web console tooling that allows you to get insight into your running Apache Camel applications, which has among others visual route diagrams with tracing/debugging and profiling capabilities. In addition to the web tooling we will also show you other tools in the making.
1. The document provides requirements and suggestions for hands-on development with Quarkus, including using Java 8 or 11 for just VM development, GraalVM 19.2.1 for native development, and ideas for projects like enabling favorite frameworks or following guides.
2. Ideas mentioned include getting started with Quarkus, following various guides, creating an ASCII banner from a PNG, and using Docker compose with Kafka.
3. Project length is estimated at 6-8 hours and developers are also encouraged to pursue their own ideas.
This document outlines the curriculum for an introduction to containerization presentation. It includes slides and hands-on exercises on installing Docker, building Docker images, running containers, viewing processes inside containers, and experimenting with resource isolation using cgroups and namespaces. Attendees will build a Docker image for a sample Flask application, run the container, view logs and processes, and push the image to Docker Hub. The presentation covers definitions of key containerization concepts and the benefits of using containers.
> 1, 2, 3 Quarkus!
Aurea MUNOZ HERNANDEZ
Quarkus est une stack pour écrire des applications Java pour le Cloud. En réduisant l’emprunte mémoire et le temps de démarrage, les applications Quarkus permettent en autre d’augmenter la densité de déploiement, le développement d’application serverless en Java, un meilleur comportement dans Kubernetes…
La première release publique de Quarkus a été faite en Mars 2019. Nous voilà 4 ans plus tard avec Quarkus 3.x. Entre temps, Quarkus a grandi, son écosystème s’est enrichi. Mais, Quarkus est resté fidèle à ses principes.
Cette présentation rappelle les points fondamentaux de Quarkus (build-time principle, reactive core, container-first) et explique leur évolution au cours de ces 4 dernières années ainsi que les nouveautés de Quarkus 3.x tels que la nouvelle dev ui, l’intégration d’Hibernate 6, le passage à Jakarta et à Flow, le support des threads virtuels, les différentes améliorations de l’expérience pour les développeurs, le support des architectures ARM…
The Java Virtual Machine (JVM) can deliver significantly better performance through the use of Just In Time compilation. However, each time you start an application it needs to repeat the same process of analysis and compilation. This session discusses Java with Co-ordinated Checkpoint at Restore. This is a way to freeze an application and start it again (potentially many times) from the same checkpoint.
Saturn 2018: Managing data consistency in a microservice architecture using S...Chris Richardson
A revised and extended version that I gave at Saturn 2018.
The services in a microservice architecture must be loosely coupled and so cannot share database tables. What’s more, two phase commit (a.k.a. a distributed transaction) is not a viable option for modern applications. Consequently, a microservices application must use the Saga pattern, which maintains data consistency using a series of local transactions.
In this presentation, you will learn how sagas work and how they differ from traditional transactions. We describe how to use sagas to develop business logic in a microservices application. You will learn effective techniques for orchestrating sagas and how to use messaging for reliability. We will describe the design of a saga framework for Java and show a sample application.
This document introduces Docker Compose, which allows defining and running multi-container Docker applications. It discusses that Docker Compose uses a YAML file to configure and run multi-service Docker apps. The 3 steps are to define services in a Dockerfile, define the app configuration in a Compose file, and run the containers with a single command. It also covers topics like networking, environment variables, and installing Docker Compose. Hands-on labs are provided to learn Compose through examples like WordPress.
This document provides an introduction to microservices, including:
- Microservices are small, independently deployable services that work together and are modeled around business domains.
- They allow for independent scaling, technology diversity, and enable resiliency through failure design.
- Implementing microservices requires automation, high cohesion, loose coupling, and stable APIs. Identifying service boundaries and designing for orchestration and data management are also important aspects of microservices design.
- Microservices are not an end goal but a means to solve problems of scale; they must be adopted judiciously based on an organization's needs.
Presented by Rags Srinivas, Developer Advocate/Architect at Datastax at Kubernetes Community Days, Washington DC, September 14, 2022.
Cassandra is designed for multi-region
● Partition tolerant
● Each node in the cluster maintains the full topology
● Nodes automatically route traffic to nearby neighbors
● Data is automatically and asynchronously replicated
● The cluster is homogenous
● Any node can service any client request
● Clients can be configured to automatically route traffic to the local datacenter
Kubernetes was not designed for multi-region
● Increased latencies
● The cost is higher consensus request latency from crossing data center boundaries
● Loss of connectivity to ectd could cause outages
● Services should route traffic to nearby endpoints
Apache Cassandra Lunch #72: Databricks and CassandraAnant Corporation
In Cassandra Lunch #72, we will discuss how we can use Databricks with Cassandra.
Accompanying Blog: https://blog.anant.us/apache-cassandra-lunch-72-databricks-and-cassandra
Accompanying YouTube: https://youtu.be/5zCN27KHADo
Sign Up For Our Newsletter: http://eepurl.com/grdMkn
Join Cassandra Lunch Weekly at 12 PM EST Every Wednesday: https://www.meetup.com/Cassandra-DataStax-DC/events/
Cassandra.Link:
https://cassandra.link/
Follow Us and Reach Us At:
Anant:
https://www.anant.us/
Awesome Cassandra:
https://github.com/Anant/awesome-cassandra
Cassandra.Lunch:
https://github.com/Anant/Cassandra.Lunch
Email:
solutions@anant.us
LinkedIn:
https://www.linkedin.com/company/anant/
Twitter:
https://twitter.com/anantcorp
Eventbrite:
https://www.eventbrite.com/o/anant-1072927283
Facebook:
https://www.facebook.com/AnantCorp/
Join The Anant Team:
https://www.careers.anant.us
Apache cassandra lunch #82 instaclustr managed cassandra and next.jsAnant Corporation
In Cassandra Lunch #82, we will discuss how to set up a Instaclustr managed Cassandra on Next.js
Accompanying Blog: https://blog.anant.us/apache-cassandra-lunch-82-instaclustr-managed-cassandra-and-next-js
Accompanying YouTube Video: https://www.youtube.com/watch?v=3UfyXEt4djg
Sign Up For Our Newsletter: http://eepurl.com/grdMkn
Join Cassandra Lunch Weekly at 12 PM EST Every Wednesday: https://www.meetup.com/Cassandra-DataStax-DC/events/
Cassandra.Link:
https://cassandra.link/
Follow Us and Reach Us At:
Anant:
https://www.anant.us/
Awesome Cassandra:
https://github.com/Anant/awesome-cassandra
Cassandra.Lunch:
https://github.com/Anant/Cassandra.Lunch
Email:
solutions@anant.us
LinkedIn:
https://www.linkedin.com/company/anant/
Twitter:
https://twitter.com/anantcorp
Eventbrite:
https://www.eventbrite.com/o/anant-1072927283
Facebook:
https://www.facebook.com/AnantCorp/
Join The Anant Team:
https://www.careers.anant.us
Apache Cassandra Lunch #82: Instaclustr Managed Cassandra and Next.jsAnant Corporation
In Cassandra Lunch #82, we will discuss how to set up a Instaclustr managed Cassandra on Next.js
Accompanying YouTube: Coming Soon!
Sign Up For Our Newsletter: http://eepurl.com/grdMkn
Join Cassandra Lunch Weekly at 12 PM EST Every Wednesday: https://www.meetup.com/Cassandra-DataStax-DC/events/
Cassandra.Link:
https://cassandra.link/
Follow Us and Reach Us At:
Anant:
https://www.anant.us/
Awesome Cassandra:
https://github.com/Anant/awesome-cassandra
Cassandra.Lunch:
https://github.com/Anant/Cassandra.Lunch
Email:
solutions@anant.us
LinkedIn:
https://www.linkedin.com/company/anant/
Twitter:
https://twitter.com/anantcorp
Eventbrite:
https://www.eventbrite.com/o/anant-1072927283
Facebook:
https://www.facebook.com/AnantCorp/
Join The Anant Team:
https://www.careers.anant.us
Spark + Cassandra = Real Time Analytics on Operational DataVictor Coustenoble
This document discusses using Apache Spark and Cassandra together for real-time analytics on transactional data. It provides an overview of Cassandra and how it can be used for operational applications like recommendations, fraud detection, and messaging. It then discusses how the Spark Cassandra Connector allows reading and writing Cassandra data from Spark, enabling real-time analytics on streaming and batch data using Spark SQL, MLlib, and Spark Streaming. It also covers some DataStax Enterprise features for high availability and integration of Spark and Cassandra.
The deck describes ScyllaDB's flagship product - a drop and replacement alternative to Apache Cassandra at 10X the speed. ScyllaDB innovative design relies on shard-per-core, own caching and c++ to deliver blazing and consistent performance. Check the deck on how this was achieved.
This document provides an overview of Apache Cassandra and how to interact with it using Java. It begins with an introduction to Cassandra and its key features like scalability and availability. It then covers Cassandra's architecture including data distribution, fault tolerance and consistency levels. The document demonstrates Cassandra's query language CQL and how to create tables, insert and query data. It provides examples of using the Java driver to connect to Cassandra, execute queries asynchronously and in parallel, use prepared statements and load balancing policies. It concludes with information about DataStax which provides commercial support for Cassandra.
How to achieve no compromise performance and availabilityScyllaDB
ScyllaDB co-founders Dor Laor and Avi Kivity discuss why they started ScyllaDB, the decision decisions they made to achieve no-compromise performance and availability, and give a demo on how to get up and running on Docker.
Apache Cassandra Lunch #93: K8ssandra on Digital OceanAnant Corporation
In Cassandra Lunch #93, we will discuss how to use k8ssandra on Digital Ocean
Accompanying Blog: Coming Soon!
Accompanying YouTube: https://youtu.be/i1C81vYqiOw
Sign Up For Our Newsletter: http://eepurl.com/grdMkn
Join Cassandra Lunch Weekly at 12 PM EST Every Wednesday: https://www.meetup.com/Cassandra-DataStax-DC/events/
Cassandra.Link:
https://cassandra.link/
Follow Us and Reach Us At:
Anant:
https://www.anant.us/
Awesome Cassandra:
https://github.com/Anant/awesome-cassandra
Cassandra.Lunch:
https://github.com/Anant/Cassandra.Lunch
Email:
solutions@anant.us
LinkedIn:
https://www.linkedin.com/company/anant/
Twitter:
https://twitter.com/anantcorp
Eventbrite:
https://www.eventbrite.com/o/anant-1072927283
Facebook:
https://www.facebook.com/AnantCorp/
Join The Anant Team:
https://www.careers.anant.us
The document discusses Cassandra, a NoSQL database management system designed to handle large amounts of data across many servers. It provides an overview of key Cassandra concepts like its use of a gossip protocol for node communication, consistent hashing for partitioning data, and a log-structured merge tree for write performance and recovery. Cassandra was created at Facebook to enable scalable storage and querying of user inbox search data across hundreds of millions of users and data centers.
Evaluating Apache Cassandra as a Cloud DatabaseDataStax
This document discusses evaluating Apache Cassandra as a cloud database. It provides an overview of DataStax, the commercial leader in Apache Cassandra. DataStax delivers database products and services based on Cassandra. Cassandra is a free, distributed, high performance, and extremely scalable database that can serve as both a real-time and read-intensive database. The document outlines how Cassandra stacks up against key attributes of a cloud database such as transparent elasticity, scalability, high availability, and more. It encourages readers to download Cassandra to try in their own environments.
Jump Start with Apache Spark 2.0 on DatabricksDatabricks
Apache Spark 2.0 has laid the foundation for many new features and functionality. Its main three themes—easier, faster, and smarter—are pervasive in its unified and simplified high-level APIs for Structured data.
In this introductory part lecture and part hands-on workshop you’ll learn how to apply some of these new APIs using Databricks Community Edition. In particular, we will cover the following areas:
What’s new in Spark 2.0
SparkSessions vs SparkContexts
Datasets/Dataframes and Spark SQL
Introduction to Structured Streaming concepts and APIs
Data Pipelines and Telephony Fraud Detection Using Machine Learning Eugene
This document discusses data pipelines and machine learning for telephony fraud detection. It first covers data pipelines, including call detail records (CDRs), SIP messages, and local routing numbers being routed through Kafka for reliable delivery and stored in Cassandra and Postgres for storage and analysis. It then discusses fraud detection, including collecting CDR data, processing it asynchronously at scale using Spark Streaming and Cassandra, detecting anomalies both statically and dynamically, and alerting. Key challenges discussed are idempotency, partitioning, and consistency models for distributed systems.
5 Factors When Selecting a High Performance, Low Latency DatabaseScyllaDB
There are hundreds of possible databases you can choose from today. Yet if you draw up a short list of critical criteria related to performance and scalability for your use case, the field of choices narrows and your evaluation decision becomes much easier.
In this session, we’ll explore 5 essential factors to consider when selecting a high performance low latency database, including options, opportunities, and tradeoffs related to software architecture, hardware utilization, interoperability, RASP, and Deployment.
MySQL Cluster Scaling to a Billion QueriesBernd Ocklin
MySQL Cluster is a distributed database that provides extreme scalability, high availability, and real-time performance. It uses an auto-sharding and auto-replicating architecture to distribute data across multiple low-cost servers. Key benefits include scaling reads and writes, 99.999% availability through its shared-nothing design with no single point of failure, and real-time responsiveness. It supports both SQL and NoSQL interfaces to enable complex queries as well as high-performance key-value access.
- The document is an introduction to Cassandra presented by Patrick McFadin, a Cassandra expert and chief evangelist at DataStax. It provides an overview of Cassandra's origins, architecture, data distribution, fault tolerance, and example applications.
- Cassandra is based on Amazon Dynamo and Google BigTable and allows for shared-nothing, predictable scaling across multiple servers through data replication and configurable consistency levels.
- Popular companies like Netflix, Spotify, and Instagram rely on Cassandra to handle high volumes of user data and queries in a highly available and resilient manner.
Webinar Slides: Real-Time Analytics from MySQLContinuent
Learn how Continuent Tungsten can replicate in real-time to multiple analytics powerhouses with no dips in performance. Targets include AWS RedShift, Kafka, Vertica and more. Don't miss the supplemental training video.
We will explore how to deploy a cluster slave in your existing environment, answering the following questions:
- What is a cluster slave?
- Why should I consider adding a cluster slave?
- What targets can I replicate to?
AGENDA
This webinar has three parts, and lasts about 30 minutes.
- Re-cap of Tungsten Cluster and Tungsten Replicator
- Use case: replicating from a cluster to analytics
- Continuent benefits
- Q & A
This document discusses processing 50,000 transactions per second using Apache Spark and Apache Cassandra. It describes monitoring over 600 servers running Cassandra by developing a metric history system using Spark, Cassandra, and other tools. Key aspects covered include data modeling, writing data efficiently in batches, joining Spark and Cassandra tables for faster data extraction during rollups, and using Cassandra aggregates to further improve performance.
Similar to A Microservices approach with Cassandra and Quarkus | DevNation Tech Talk (20)
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.
Quinoa: A modern Quarkus UI with no hassles | DevNation tech TalkRed Hat Developers
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.
Extra micrometer practices with Quarkus | DevNation Tech TalkRed Hat Developers
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.
Event-driven autoscaling through KEDA and Knative Integration | DevNation Tec...Red Hat Developers
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 🦊♥: an old-school Web framework with today's touch | DevNatio...Red Hat Developers
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.
Distributed deployment of microservices across multiple OpenShift clusters | ...Red Hat Developers
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.
DevNation Workshop: Object detection with Red Hat OpenShift Data Science [Mar...Red Hat Developers
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.
Dear security, compliance, and auditing: We’re sorry. Love, DevOps | DevNatio...Red Hat Developers
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.
11 CLI tools every developer should know | DevNation Tech TalkRed Hat Developers
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.
GitHub Actions and OpenShift: Supercharging your software development loops...Red Hat Developers
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.
To the moon and beyond with Java 17 APIs! | DevNation Tech TalkRed Hat Developers
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!
Profile your Java apps in production on Red Hat OpenShift with Cryostat | Dev...Red Hat Developers
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.
Kafka at the Edge: an IoT scenario with OpenShift Streams for Apache Kafka | ...Red Hat Developers
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.
Kubernetes configuration and security policies with KubeLinter | DevNation Te...Red Hat Developers
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
Level-up your gaming telemetry using Kafka Streams | DevNation Tech TalkRed Hat Developers
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.
Friends don't let friends do dual writes: Outbox pattern with OpenShift Strea...Red Hat Developers
Dual writes are a common source of issues in distributed event-driven applications. A dual write occurs when an application has to change data in two different systems - for instance, when an application needs to persist data in the database and send a Kafka message to notify other systems. If one of these two operations fail, you might end up with inconsistent data which can be hard to detect and fix.
OpenShift Streams for Apache Kafka is Red Hat's fully hosted and managed Apache Kafka service targeting development teams that want to incorporate streaming data and scalable messaging in their applications, without the burden of setting up and maintaining a Kafka cluster infrastructure. Debezium is an open source distributed platform for change data capture. Built on top of Apache Kafka, it allows applications to react to inserts, updates, and deletes in your databases.
In this session you will learn how you can leverage OpenShift Streams for Apache Kafka and Debezium to avoid the dual write issue in an event-driven application using the outbox pattern. More specifically, we will show you how to:
Provision a Kafka cluster on OpenShift Streams for Apache Kafka.
Deploy and configure Debezium to use OpenShift Streams for Apache Kafka.
Refactor an application to leverage Debezium and OpenShift Streams for Apache Kafka to avoid the dual write problem.
The Rise of Supernetwork Data Intensive ComputingLarry Smarr
Invited Remote Lecture to SC21
The International Conference for High Performance Computing, Networking, Storage, and Analysis
St. Louis, Missouri
November 18, 2021
Transcript: Details of description part II: Describing images in practice - T...BookNet Canada
This presentation explores the practical application of image description techniques. Familiar guidelines will be demonstrated in practice, and descriptions will be developed “live”! If you have learned a lot about the theory of image description techniques but want to feel more confident putting them into practice, this is the presentation for you. There will be useful, actionable information for everyone, whether you are working with authors, colleagues, alone, or leveraging AI as a collaborator.
Link to presentation recording and slides: https://bnctechforum.ca/sessions/details-of-description-part-ii-describing-images-in-practice/
Presented by BookNet Canada on June 25, 2024, with support from the Department of Canadian Heritage.
Blockchain technology is transforming industries and reshaping the way we conduct business, manage data, and secure transactions. Whether you're new to blockchain or looking to deepen your knowledge, our guidebook, "Blockchain for Dummies", is your ultimate resource.
How Social Media Hackers Help You to See Your Wife's Message.pdfHackersList
In the modern digital era, social media platforms have become integral to our daily lives. These platforms, including Facebook, Instagram, WhatsApp, and Snapchat, offer countless ways to connect, share, and communicate.
Quality Patents: Patents That Stand the Test of TimeAurora Consulting
Is your patent a vanity piece of paper for your office wall? Or is it a reliable, defendable, assertable, property right? The difference is often quality.
Is your patent simply a transactional cost and a large pile of legal bills for your startup? Or is it a leverageable asset worthy of attracting precious investment dollars, worth its cost in multiples of valuation? The difference is often quality.
Is your patent application only good enough to get through the examination process? Or has it been crafted to stand the tests of time and varied audiences if you later need to assert that document against an infringer, find yourself litigating with it in an Article 3 Court at the hands of a judge and jury, God forbid, end up having to defend its validity at the PTAB, or even needing to use it to block pirated imports at the International Trade Commission? The difference is often quality.
Quality will be our focus for a good chunk of the remainder of this season. What goes into a quality patent, and where possible, how do you get it without breaking the bank?
** Episode Overview **
In this first episode of our quality series, Kristen Hansen and the panel discuss:
⦿ What do we mean when we say patent quality?
⦿ Why is patent quality important?
⦿ How to balance quality and budget
⦿ The importance of searching, continuations, and draftsperson domain expertise
⦿ Very practical tips, tricks, examples, and Kristen’s Musts for drafting quality applications
https://www.aurorapatents.com/patently-strategic-podcast.html
Implementations of Fused Deposition Modeling in real worldEmerging Tech
The presentation showcases the diverse real-world applications of Fused Deposition Modeling (FDM) across multiple industries:
1. **Manufacturing**: FDM is utilized in manufacturing for rapid prototyping, creating custom tools and fixtures, and producing functional end-use parts. Companies leverage its cost-effectiveness and flexibility to streamline production processes.
2. **Medical**: In the medical field, FDM is used to create patient-specific anatomical models, surgical guides, and prosthetics. Its ability to produce precise and biocompatible parts supports advancements in personalized healthcare solutions.
3. **Education**: FDM plays a crucial role in education by enabling students to learn about design and engineering through hands-on 3D printing projects. It promotes innovation and practical skill development in STEM disciplines.
4. **Science**: Researchers use FDM to prototype equipment for scientific experiments, build custom laboratory tools, and create models for visualization and testing purposes. It facilitates rapid iteration and customization in scientific endeavors.
5. **Automotive**: Automotive manufacturers employ FDM for prototyping vehicle components, tooling for assembly lines, and customized parts. It speeds up the design validation process and enhances efficiency in automotive engineering.
6. **Consumer Electronics**: FDM is utilized in consumer electronics for designing and prototyping product enclosures, casings, and internal components. It enables rapid iteration and customization to meet evolving consumer demands.
7. **Robotics**: Robotics engineers leverage FDM to prototype robot parts, create lightweight and durable components, and customize robot designs for specific applications. It supports innovation and optimization in robotic systems.
8. **Aerospace**: In aerospace, FDM is used to manufacture lightweight parts, complex geometries, and prototypes of aircraft components. It contributes to cost reduction, faster production cycles, and weight savings in aerospace engineering.
9. **Architecture**: Architects utilize FDM for creating detailed architectural models, prototypes of building components, and intricate designs. It aids in visualizing concepts, testing structural integrity, and communicating design ideas effectively.
Each industry example demonstrates how FDM enhances innovation, accelerates product development, and addresses specific challenges through advanced manufacturing capabilities.
INDIAN AIR FORCE FIGHTER PLANES LIST.pdfjackson110191
These fighter aircraft have uses outside of traditional combat situations. They are essential in defending India's territorial integrity, averting dangers, and delivering aid to those in need during natural calamities. Additionally, the IAF improves its interoperability and fortifies international military alliances by working together and conducting joint exercises with other air forces.
An invited talk given by Mark Billinghurst on Research Directions for Cross Reality Interfaces. This was given on July 2nd 2024 as part of the 2024 Summer School on Cross Reality in Hagenberg, Austria (July 1st - 7th)
Coordinate Systems in FME 101 - Webinar SlidesSafe Software
If you’ve ever had to analyze a map or GPS data, chances are you’ve encountered and even worked with coordinate systems. As historical data continually updates through GPS, understanding coordinate systems is increasingly crucial. However, not everyone knows why they exist or how to effectively use them for data-driven insights.
During this webinar, you’ll learn exactly what coordinate systems are and how you can use FME to maintain and transform your data’s coordinate systems in an easy-to-digest way, accurately representing the geographical space that it exists within. During this webinar, you will have the chance to:
- Enhance Your Understanding: Gain a clear overview of what coordinate systems are and their value
- Learn Practical Applications: Why we need datams and projections, plus units between coordinate systems
- Maximize with FME: Understand how FME handles coordinate systems, including a brief summary of the 3 main reprojectors
- Custom Coordinate Systems: Learn how to work with FME and coordinate systems beyond what is natively supported
- Look Ahead: Gain insights into where FME is headed with coordinate systems in the future
Don’t miss the opportunity to improve the value you receive from your coordinate system data, ultimately allowing you to streamline your data analysis and maximize your time. See you there!
Paradigm Shifts in User Modeling: A Journey from Historical Foundations to Em...Erasmo Purificato
Slide of the tutorial entitled "Paradigm Shifts in User Modeling: A Journey from Historical Foundations to Emerging Trends" held at UMAP'24: 32nd ACM Conference on User Modeling, Adaptation and Personalization (July 1, 2024 | Cagliari, Italy)
Understanding Insider Security Threats: Types, Examples, Effects, and Mitigat...Bert Blevins
Today’s digitally connected world presents a wide range of security challenges for enterprises. Insider security threats are particularly noteworthy because they have the potential to cause significant harm. Unlike external threats, insider risks originate from within the company, making them more subtle and challenging to identify. This blog aims to provide a comprehensive understanding of insider security threats, including their types, examples, effects, and mitigation techniques.
How RPA Help in the Transportation and Logistics Industry.pptxSynapseIndia
Revolutionize your transportation processes with our cutting-edge RPA software. Automate repetitive tasks, reduce costs, and enhance efficiency in the logistics sector with our advanced solutions.
TrustArc Webinar - 2024 Data Privacy Trends: A Mid-Year Check-InTrustArc
Six months into 2024, and it is clear the privacy ecosystem takes no days off!! Regulators continue to implement and enforce new regulations, businesses strive to meet requirements, and technology advances like AI have privacy professionals scratching their heads about managing risk.
What can we learn about the first six months of data privacy trends and events in 2024? How should this inform your privacy program management for the rest of the year?
Join TrustArc, Goodwin, and Snyk privacy experts as they discuss the changes we’ve seen in the first half of 2024 and gain insight into the concrete, actionable steps you can take to up-level your privacy program in the second half of the year.
This webinar will review:
- Key changes to privacy regulations in 2024
- Key themes in privacy and data governance in 2024
- How to maximize your privacy program in the second half of 2024
7. Origin of the term “NoSQL”
7
● Meetup name on June 11, 2009 in San Francisco
○ Catchy hashtag intended to refer to databases like BigTable and DynamoDB
○ Meetup presentations: Cassandra, MongoDB, CouchDB, HBase, Voldemort,
Dynomite, and Hypertable
● Sometimes referred to “Not only SQL”
8. Relational vs. NoSQL
8
● Relational
○ Standard relational data model
and language SQL
○ ACID transactions
○ Integration database
○ Designed for a single machine
○ Hard to scale
○ Impedance mismatch
● NoSQL
○ Variety of data models and
languages
○ Lower-guarantee transactions
○ Application database
○ Designed for a cluster
○ Easy to scale
○ Better database-app compatibility
9. The CAP Theorem
9
Availability
Consistency
AP
CA
Partition tolerance
CP
Always responds,
may not always return
the most recent write
pick two
Every read receives
the most recent write
or an error
Operates in the
presence of network
partition failures
13. Why partitioning?
Because scaling doesn’t have to be [s]hard!
Big Data doesn’t fit to a single server, splitting it into
chunks we can easily spread them over dozens, hundreds
or even thousands of servers, adding more if needed.
14. Is Cassandra AP or CP?
Cassandra is configurably consistent. In any moment of the
time, for any particular query you can set the Consistency Level
you require to have. It defines how many CONFIRMATIONS
you’ll wait before the response is dispatched;
14
PreparedStatement pstmt = session.prepare(
"INSERT INTO product (sku, description) VALUES (?,
?)"
);
pstmt.setConsistencyLevel(ConsistencyLevel.ONE);
cqlsh> CONSISTENCY
Current consistency level is QUORUM.
cqlsh> CONSISTENCY ALL
Consistency level set to ALL.
18. c
OSS Apache Cassandra
A tabular NoSQL database
OSS Stargate.io
A data gateway to allow
multiple usages
$25/month credit
Launch a database in the cloud with a few clicks, no credit card required.
Z
Swagger UI
GraphQL
Playground
Tools
User Interface
Web-based developer
tools and apps
CQL JSON GraphQL REST GRPC
Apps
CQL
Console
22. A cohesive platform for optimized Microservices
joy
● Based on standards
● Unified configuration
● Live coding
● Streamlined code for the 80% common usages
○ Flexible for the 20% uncommon
● No hassle native executable generation
Inner loop == Developer Productivity
“Our developers used to wait 2 to 3 mins to see their changes. Live coding does away
with this!”
22
24. @
@
</>
Packaging
(maven,
gradle…)
Build Time
Runtime
Load config file
from file system
Parse it
Classpath scanning
to find
annotated classes
Attempt to load
class to
enable/disable
features
Build its
model of
the world
Start the
management
(thread,
pool…)
How does a Typical Java Framework Work?
27. Microservices Architecture evolution
Monolith 90s
User Interface
Services
Data
Multi Tiers 2000 SOA (2005) Microservices (2015)
Front End
Backend
Data Layer
UI UI
ESB
Service
RDMS
SPA
Backend for frontend
Native Web Component
API
gateway
Service
Registry
Service
Mesh
Service
Service
Service
Service
NoSQL
Object
BigData
NoSQL
NoSQL
Microfrontend
Service
MicroServices
Service
Service
Service
Service
Service
Service
Service
Service
Service
Service
Service
Service
Service
Service
Service
Service
Service Service
NoSQL
NoSQL
NoSQL
NoSQL
NoSQL
NoSQL
NoSQL
NoSQL
NoSQL
NoSQL
NoSQL
NoSQL
Data Mesh
31. Rest vs gRPC vs GraphQL ?
● Decoupling Client / Server (Schema on read)
● API Lifecycle (Versioning)
● Tooling (API Management, Serverless)
● Verbose payloads (json, xml)
● No discoverability
● Not suitable for command-like (functions) API
● CRUD superstar
● Relevant for mutations (OLTP)
● Public and web APIs
● Limited Business Scope
+
-
32. Rest vs gRPC vs GraphQL ?
● High Performances (http/2 – binary serialization)
● Multiple stubs : Sync, Async, Streaming
● Multi languages - Interoperability
● Strongly coupled (schema with proto files)
● No discoverability
● Protobuf serialization format
● Distributed network of services (no waits)
● High throughput & streaming use cases
● Command-like (eg: slack)
+
-
33. Rest vs gRPC vs GraphQL ?
● Discoverability, documentation
● Custom payloads
● Match standards (JSON | HTTP)
● Single endpoint (versioning, monitoring, security)
● Complex implementation (tooling, still young)
● Nice for customers nasty for DB (N+1 select)
● Backend for frontend (JS)
● Service aggregation | composition (joins)
● When volume matters (mobile phones)
+
-
GraphQL
34. Quarkus Cassandra Extension
34
● Native Quarkus Config
● Cassandra Driver Session Support
● Cassandra Driver Object Mapper Support
● Support for Mutiny Types (Reactive Types)
● Native Image Support
● Support for DataStax Astra (Cassandra DBaaS)
40. Specification of Service layer
Create a new Task
Mark a task as completed
Delete a task
List all tasks
41. Data Model
CREATE TABLE todos.todoitems (
user_id text,
item_id timeuuid,
completed boolean,
title text,
offset int,
PRIMARY KEY ((user_id),item_id)
);
user_id
item_id
completed
title
offset
todoitems
TEXT
TIMEUUID
BOOLEAN
TEXT
INT
K
C↑
42. Rational
● Our Partition key is user_id
○ We chose to have one todo list per user (avoiding any select * from table)
● Service
○ findTodos() for user
○ createTodo() for user
○ deleteTodo() from its id (userid + itemid)
○ updateTodo() from its id (both to mark it as complete and update title)
● REST API
○ The userid will appear in the URL
○ Provide major version (best practice)
/api/v1/{user_id}/todos
49. 49
AstraDB astra.datastax.com Gitpod IDE: https://gitpod.io Katacoda katacoda.com/datastax
Complete Workshops Labs
2
c
Database + GraphQL + PlayGround
c
c
c
50. Become a Jedi Master of Astra 50
datastax.com/workshops
51. JOIN OUR ASTRA DB
BUILD-A-THON HACK!
📍 3 months, 3 rounds of challenges. 📍
Join 1 month, 2 months or all 3
Each month, we’ll reveal a fresh new set of
challenges you can partake in.
All you have to do is have Astra DB as your
backend.
USD$41,000 worth of prizes
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buildathonhack.com
52. Try Cassandra+Quarkus
52
● Create your quarkus + cassandra app (code.quarkus.io or running the following):
$ mvn io.quarkus:quarkus-maven-plugin:1.12.1.Final:create
-DprojectGroupId=io.quarkus.astra
-DprojectArtifactId=quarkus-astra-demo
-DprojectVersion=1.0.0
-DclassName="io.quarkus.astra"
-Dextensions="resteasy-reactive, resteasy-reactive-jackson, micrometer-registry-prometheus, smallrye-openapi,
smallrye-health, cassandra-quarkus-client"
$ cd quarkus-astra-demo
$ ./mvnw clean quarkus:dev
● Stand up your Astra free database (astra.datastax.com)
● Check out https://k8ssandra.io
quarkus.cassandra.cloud.secure-connect-bundle=<path>/secure-connect-bundle.zip
quarkus.cassandra.auth.username=<user>
quarkus.cassandra.auth.password=<pw>
● Get coding + see docs for more info and try the Quarkus + Cassandra workshop
https://quarkus.io/guides/cassandra
https://github.com/datastaxdevs/workshop-intro-quarkus-cassandra/