Javantura v3 - Conquer the Internet of Things with Java and Docker – Johan Janssen
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This document discusses using Docker and Java on a Raspberry Pi. It outlines some advantages of Docker like enabling continuous delivery, provisioning environments quickly and easily, updating and synchronizing environments, disk space and memory efficiency. It then provides steps to install and run Docker on a Raspberry Pi, including building Dockerfiles and containers for Tomcat and a sample web application. It also demonstrates creating a local Docker registry to push and pull images.
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This document describes a Parallel Streaming Transformation Loader (PSTL) that uses Kafka, Spark, and Vertica for real-time data ingestion and analytics. It summarizes the PSTL as follows:
1. The PSTL ingests streaming data from Kafka into Spark RDDs in parallel.
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•Data volumes are large, or moving raw data is expensive,
•Data is generated by widely distributed assets (eg: mobile devices),
•Data is of ephemeral value and analysis can’t wait, or
•It is critical to always have the latest insight and extrapolation won’t do.
Use cases include prediction of failures on assembly lines, prediction of traffic flows in cities, predicting demand placed in power grids, detection of hackers, and understanding connection quality in mobile networks. They are characterized by a need to know – now – and require real-time processing of streaming data. Our goal is to enable real-time stream processing for Apache Pulsar in which analysis, learning and prediction are done on-the-fly, with continuous insights streamed back to the broker.
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This was the first Kafka Meetup in South Africa.
Analyzing Petabyte Scale Financial Data with Apache Pinot and Apache Kafka | ...
At Stripe, we operate a general ledger modeled as double-entry bookkeeping for all financial transactions. Warehousing such data is challenging due to its high volume and high cardinality of unique accounts.
aFurthermore, it is financially critical to get up-to-date, accurate analytics over all records. Due to the changing nature of real time transactions, it is impossible to pre-compute the analytics as a fixed time series. We have overcome the challenge by creating a real time key-value store inside Pinot that can sustain half million QPS with all the financial transactions.
We will talk about the details of our solution and the interesting technical challenges faced.
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Several different frameworks have been developed to draw data from Kafka and maintain standard SQL over continually changing data. This provides an easy way to query and transform data - now accessible by orders of magnitude more users.
At the same time, using Standard SQL against changing data is a new pattern for many engineers and analysts. While the language hasn’t changed, we’re still in the early stages of understanding the power of SQL over Kafka - and in some interesting ways, this new pattern introduces some exciting new idioms.
In this session, we’ll start with some basic use cases of how Standard SQL can be effectively used over events in Kafka- including how these SQL engines can help teams that are brand new to streaming data get started. From there, we’ll cover a series of more advanced functions and their implications, including:
- WHERE clauses that contain time change the validity intervals of your data; you can programmatically introduce and retract records based on their payloads!
- LATERAL joins turn streams of query arguments into query results; they will automatically share their query plans and resources!
- GROUP BY aggregations can be applied to ever-growing data collections; reduce data that wouldn't even fit in a database in the first place.
We'll review in-production examples where each of these cases make unmodified Standard SQL, run and maintain over data streams in Kafka, and provide the functionality of bespoke stream processors.
Web application
This project report describes a College Information Management System that was created to manage student records like registration, attendance, results, and feedback in a centralized digital system. It aims to address problems with existing manual paper-based systems by creating a web application with a frontend created in Eclipse IDE and backend database in MySQL. The system includes modules for registration, attendance tracking, viewing results, and submitting feedback. The report provides details on the hardware, software, database structure, and screenshots of the key features developed in the project.
Dissolving the Problem (Making an ACID-Compliant Database Out of Apache Kafka®)
Presenter: Tim Berglund, Senior Director of Developer Experience, Confluent
It has become a truism in the past decade that building systems at scale, using non-relational databases, requires giving up on the transactional guarantees afforded by the relational databases of yore. ACID transactional semantics are fine, but we all know you can’t have them all in a distributed system. Or can we?
In this talk, I will argue that by designing our systems around a distributed log like Apache Kafka®, we can in fact achieve ACID semantics at scale. We can ensure that distributed write operations can be applied atomically, consistently, in isolation between services, and of course with durability. What seems to be a counterintuitive conclusion ends up being straightforwardly achievable using existing technologies, as an elusive set of properties becomes relatively easy to achieve with the right architectural paradigm underlying the application.
Kappa Architecture on Apache Kafka and Querona: datamass.io
This document discusses Kappa Architecture, an alternative to Lambda Architecture for event processing. Kappa Architecture uses a single stream of events from Apache Kafka as the input, rather than separating batch and stream processing. It reads all events from Kafka and runs analytics on the full data set to enable both learning from historical events and reacting to new events. The document outlines how Kappa Architecture provides benefits like avoiding duplicate processing logic and making actionable analytics easier. It also describes how to read bounded batches of events from Kafka for analytics using tools like Apache Spark.
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Automate drupal deployments with linux containers, docker and vagrant
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Drupalcamp es 2013 drupal with lxc docker and vagrant
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Java cro'21 the best tools for java developers in 2021 - hujak
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JavaCro'21 - Java is Here To Stay - HUJAK KeynoteHUJAK - Hrvatska udruga Java korisnika / Croatian Java User Association
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Javantura v7 - Behaviour Driven Development with Cucumber - Ivan LozićHUJAK - Hrvatska udruga Java korisnika / Croatian Java User Association
Javantura v7 - Behaviour Driven Development with Cucumber - Ivan Lozić
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Javantura v7 - Learning to Scale Yourself: The Journey from Coder to Leader -...HUJAK - Hrvatska udruga Java korisnika / Croatian Java User Association
Javantura v7 - Learning to Scale Yourself: The Journey from Coder to Leader - Daniel Strmečki
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JavaCro'19 - The State of Java and Software Development in Croatia - Communit...HUJAK - Hrvatska udruga Java korisnika / Croatian Java User Association
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Bugs happen! It is a developers life fact. Let'e explore one way we the developers can help customers to make batter bug reports.
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Javantura v6 - When remote work really works - the secrets behind successful ...HUJAK - Hrvatska udruga Java korisnika / Croatian Java User Association
With several years of remote work experience in an agile environment, working from beautiful Zagreb for clients abroad and trying out different distributed team setups, we will share the motivation and philosophy behind it. We will also cover best practices, challenges and general tips & tricks in different segments such as work organisation, technical requirements, social requirements, methodology etc.
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Javantura v6 - End to End Continuous Delivery of Microservices for Kubernetes...HUJAK - Hrvatska udruga Java korisnika / Croatian Java User Association
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Individual microservices are relatively easy to develop, but managing a distributed system composed of microservices is never a simple task. Kubernetes helps, but it falls short of providing everything such a system needs. This is where the Istio Service Mesh comes in.
Running microservices in production, you'll soon realize you want things like traffic splitting, automatic connection retries, timeouts and failovers, secure communication and authentication between your services, distributed metrics, tracing and logging. By introducing Istio into your architecture, you get all of that and more. And you get most of it without changing your code at all.
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Javantura v6 - How can you improve the quality of your application - Ioannis ...HUJAK - Hrvatska udruga Java korisnika / Croatian Java User Association
Do your customers keep complaining about bugs in your software application? Does it take you too much time to implement new features? If yes, then you probably have issues with the quality of your application. Join me to find out what practical steps you can follow to improve the quality of your application!Javantura v6 - Just say it v2 - Pavao Varela Petrac
Javantura v6 - Just say it v2 - Pavao Varela PetracHUJAK - Hrvatska udruga Java korisnika / Croatian Java User Association
We are used to give commands to our computers with keyboard - by natural language recognition improvement, services around this technology stack become better and better each day. Using Google Home mini device, IFTTT service and java web socket netty server hosted on red hat Openshift platform, control your loving private computer terminal or any application from distance with your bare voice.Javantura v6 - Automation of web apps testing - Hrvoje Ruhek
Javantura v6 - Automation of web apps testing - Hrvoje RuhekHUJAK - Hrvatska udruga Java korisnika / Croatian Java User Association
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Javantura v6 - Master the Concepts Behind the Java 10 Challenges and Eliminat...HUJAK - Hrvatska udruga Java korisnika / Croatian Java User Association
Bugs are a daily cause of stress in our work as Java developers. Those pesky things can hide behind core concepts in Java 9 and 10—there is no way out of this. If we don’t keep up to date with new Java versions, bugs will take over our projects. But can we have fun hunting them? You bet! How about solving a series of Java puzzles as a way to master concepts and save a lot of time finding those tricky bugs? In this session, attendees can help the bug hunters solve fun Java challenges, gain a clear understanding of what causes the most-stressful bugs—and have fun eliminating them from projects.Javantura v6 - Building IoT Middleware with Microservices - Mario Kusek
Javantura v6 - Building IoT Middleware with Microservices - Mario KusekHUJAK - Hrvatska udruga Java korisnika / Croatian Java User Association
In H2020 EU project symbIoTe (symbiosis of smart objects across IoT environments) we have been building IoT middleware based on microservices programmed in Java with Spring Boot and Spring Cloud components. Here I will present our experiences in developing such services in distributed team across EU and employed by 15 organizations. I will present organizational and technical advantages and drawbacks as well as our choices in building such system.More from HUJAK - Hrvatska udruga Java korisnika / Croatian Java User Association (20)
Java cro'21 the best tools for java developers in 2021 - hujak
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Javantura v6 - Java in Croatia and HUJAK - Branko Mihaljević, Aleksander Radovan
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Javantura v6 - End to End Continuous Delivery of Microservices for Kubernetes...
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I develop the Ruby programming language, RubyGems, and Bundler, which are package managers for Ruby. Today, I will introduce how to enhance the security of your application using open-source software (OSS) examples from Ruby and RubyGems.
The first topic is CVE (Common Vulnerabilities and Exposures). I have published CVEs many times. But what exactly is a CVE? I'll provide a basic understanding of CVEs and explain how to detect and handle vulnerabilities in OSS.
Next, let's discuss package managers. Package managers play a critical role in the OSS ecosystem. I'll explain how to manage library dependencies in your application.
I'll share insights into how the Ruby and RubyGems core team works to keep our ecosystem safe. By the end of this talk, you'll have a better understanding of how to safeguard your code.
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Javantura v3 - Conquer the Internet of Things with Java and Docker – Johan Janssen
- 1. Johan Janssen (Info Support) @johanjanssen42
- 2. Internet of Things Docker and Java on a Raspberry Pi Advantages of using Docker Questions
- 4. Continuous Delivery Virtual machines Provisioning (Chef, Puppet, Vagrant …) Version control / infrastructure as code Isolation Updating and synchronizing environments
- 9. To enable continuous delivery Quickly provision environments Easy to roll forward Security For instance to run ‘untrusted’ applications like a Dropbox client Alternative for virtual machines On top of virtual machines
- 11. Disk space efficiency Memory efficiency Speed Compatibility (run anywhere) Isolation Versioning Internet of Things (Raspberry Pi etc.)
- 12. Update repositories pacman –Syy Optional update al packages: pacman -Syu Install Docker pacman -S docker
- 13. Docker on the Raspberry Pi docker run -i –t resin/rpi-raspbian /bin/bash
- 14. FROM resin/rpi-raspbian RUN apt-get update RUN apt-get install -y openjdk-8-jre-headless wget RUN wget -O /tmp/tomcat8.tar.gz http://archive.apache.org/dist/tomcat/tomcat- 8/v8.0.9/bin/apache-tomcat-8.0.9.tar.gz RUN (cd /opt && tar zxf /tmp/tomcat8.tar.gz) RUN (mv /opt/apache-tomcat* /opt/tomcat) ENV JAVA_HOME /usr/lib/jvm/java-1.8.0-openjdk-armhf RUN rm -rf /opt/tomcat/webapps/docs /opt/tomcat/webapps/examples /opt/tomcat/webapps/host-manager /opt/tomcat/webapps/manager EXPOSE 8080 CMD ["/opt/tomcat/bin/catalina.sh", "run"]
- 15. FROM tomcat ADD DockerPiExample.war /opt/tomcat/webapps/
- 17. Create the Dockerfiles Build the containers cd Tomcat (optional) docker build -t tomcat . (optional) cd .. (optional) cd TomcatApp docker build -t tomcatapp .
- 18. Start the container docker run -p 8042:8080 -d tomcatapp
- 22. Creating the Docker registry docker run -p 5000:5000 registry
- 23. Change container (using touch for instance) Commit docker.io commit 064f 192.168.56.31:5000/test-version-0.2 New containerid -> ff7e Push docker.io push 192.168.56.31:5000/test-version-0.2
- 24. Pull docker.io pull 192.168.56.31:5000/test-version-0.2 Run docker.io run -i -t ff7e /bin/bash
- 26. docker images -tree └─153bf43b408a 194.2 MB test-version-0.1:latest docker pull 192.168.56.31:5000/test-version-0.2 ff7e110ebadd: Download complete 153bf43b408a: Download complete docker images -tree └─153bf43b408a 194.2 MB test-version-0.1:latest └─ff7e110ebadd 194.2 MB test-version-0.2:latest
- 27. GeneralBase AppServerBase Environment D Environment T Environment A Environment P Jenkins JenkinsDataContainer SonarQube Gitblit Nexus
- 28. # docker.io images --tree └─ 179.9 MB Tags: ubuntu:saucy └─253.6 MB └─741.8 MB Tags: GeneralBase:latest └─763.6 MB Tags: AppServerBase:latest ├─763.6 MB Tags: EnvironmentP:latest └─865.6 MB Tags: Nexus:latest └─808.3 MB Tags: Gitblit:latest └─901.5 MB Tags: Sonar:latest └─805.4 MB Tags: Jenkins:latest
- 29. real 4m11.729s user 0m3.329s sys 0m10.054s
- 30. Big potential market for Docker and Java Easy to use Highly flexible and customizable
Editor's Notes
- http://192.168.1.3:8080/DockerPiExample/helloworld/hello/JavaOne