A successful pipeline moves data efficiently, minimizing pauses and blockages between tasks, keeping every process along the way operational. Apache Airflow provides a single customizable environment for building and managing data pipelines, eliminating the need for a hodge-podge collection of tools, snowflake code, and homegrown processes. Using real-world scenarios and examples, Data Pipelines with Apache Airflow teaches you how to simplify and automate data pipelines, reduce operational overhead, and smoothly integrate all the technologies in your stack.
Check out the contents on our browser-based liveBook reader here: https://livebook.manning.com/book/data-pipelines-with-apache-airflow/
We will introduce Airflow, an Apache Project for scheduling and workflow orchestration. We will discuss use cases, applicability and how best to use Airflow, mainly in the context of building data engineering pipelines. We have been running Airflow in production for about 2 years, we will also go over some learnings, best practices and some tools we have built around it.
Speakers: Robert Sanders, Shekhar Vemuri
In the session, we discussed the End-to-end working of Apache Airflow that mainly focused on "Why What and How" factors. It includes the DAG creation/implementation, Architecture, pros & cons. It also includes how the DAG is created for scheduling the Job and what all steps are required to create the DAG using python script & finally with the working demo.
Running Airflow Workflows as ETL Processes on Hadoopclairvoyantllc
While working with Hadoop, you'll eventually encounter the need to schedule and run workflows to perform various operations like ingesting data or performing ETL. There are a number of tools available to assist you with this type of requirement and one such tool that we at Clairvoyant have been looking to use is Apache Airflow. Apache Airflow is an Apache Incubator project that allows you to programmatically create workflows through a python script. This provides a flexible and effective way to design your workflows with little code and setup. In this talk, we will discuss Apache Airflow and how we at Clairvoyant have utilized it for ETL pipelines on Hadoop.
Quick introduction about Apache Spark and how it fits in the cognitive world, how can we use it to help cognitive solutions as well as create distributed algorithms to predict and perform other machine learning tasks.
Introduction to Apache Airflow, it's main concepts and features and an example of a DAG. Afterwards some lessons and best practices learned by from the 3 years I have been using Airflow to power workflows in production.
We will introduce Airflow, an Apache Project for scheduling and workflow orchestration. We will discuss use cases, applicability and how best to use Airflow, mainly in the context of building data engineering pipelines. We have been running Airflow in production for about 2 years, we will also go over some learnings, best practices and some tools we have built around it.
Speakers: Robert Sanders, Shekhar Vemuri
In the session, we discussed the End-to-end working of Apache Airflow that mainly focused on "Why What and How" factors. It includes the DAG creation/implementation, Architecture, pros & cons. It also includes how the DAG is created for scheduling the Job and what all steps are required to create the DAG using python script & finally with the working demo.
Running Airflow Workflows as ETL Processes on Hadoopclairvoyantllc
While working with Hadoop, you'll eventually encounter the need to schedule and run workflows to perform various operations like ingesting data or performing ETL. There are a number of tools available to assist you with this type of requirement and one such tool that we at Clairvoyant have been looking to use is Apache Airflow. Apache Airflow is an Apache Incubator project that allows you to programmatically create workflows through a python script. This provides a flexible and effective way to design your workflows with little code and setup. In this talk, we will discuss Apache Airflow and how we at Clairvoyant have utilized it for ETL pipelines on Hadoop.
Quick introduction about Apache Spark and how it fits in the cognitive world, how can we use it to help cognitive solutions as well as create distributed algorithms to predict and perform other machine learning tasks.
Introduction to Apache Airflow, it's main concepts and features and an example of a DAG. Afterwards some lessons and best practices learned by from the 3 years I have been using Airflow to power workflows in production.
How I learned to time travel, or, data pipelining and scheduling with AirflowLaura Lorenz
****UPDATE: Project is now open sourced at https://www.github.com/industrydive/fileflow****
From Pydata DC 2016
Description
Data warehousing and analytics projects can, like ours, start out small - and fragile. With an organically growing mess of scripts glued together and triggered by cron jobs hiding on different servers, we needed better plumbing. After perusing the data pipelining landscape, we landed on Airflow, an Apache incubating batch processing pipelining and scheduler tool from Airbnb.
Abstract
The power of any reporting tool breaks based on the data behind it, so when our data warehousing process got too big for its humble origins, we searched for something better. After testing out several options such as Drake, Pydoit, Luigi, AWS Data Pipeline, and Pinball, we landed on Airflow, an Apache incubating batch processing pipelining and scheduler tool originating from Airbnb, that provides the benefits of pipeline construction as directed acyclic graphs (DAGs), along with a scheduler that can handle alerting, retries, callbacks and more to make your pipeline robust. This talk will discuss the value of DAG based pipelines for data processing workflows, highlight useful features in all of the pipelining projects we tested, and dive into some of the specific challenges (like time travel) and successes (like time travel!) we’ve experienced using Airflow to productionize our data engineering tasks. By the end of this talk, you will learn
- pros and cons of several Python-based/Python-supporting data pipelining libraries
- the design paradigm behind Airflow, an Apache incubating data pipelining and scheduling service, and what it is good for
- some epic fails to avoid and some epic wins to emulate from our experience porting our data engineering tasks to a more robust system
- some quick-start tips for implementing Airflow at your organization.
Apache Airflow (incubating) NL HUG Meetup 2016-07-19Bolke de Bruin
Introduction to Apache Airflow (Incubating), best practices and roadmap. Airflow is a platform to programmatically author, schedule and monitor workflows.
Presentation given at Coolblue B.V. demonstrating Apache Airflow (incubating), what we learned from the underlying design principles and how an implementation of these principles reduce the amount of ETL effort. Why choose Airflow? Because it makes your engineering life easier, more people can contribute to how data flows through the organization, so that you can spend more time applying your brain to more difficult problems like Machine Learning, Deep Learning and higher level analysis.
Slide deck for the fourth data engineering lunch, presented by guest speaker Will Angel. It covered the topic of using Airflow for data engineering. Airflow is a scheduling tool for managing data pipelines.
Building a Data Pipeline using Apache Airflow (on AWS / GCP)Yohei Onishi
This is the slide I presented at PyCon SG 2019. I talked about overview of Airflow and how we can use Airflow and the other data engineering services on AWS and GCP to build data pipelines.
This presentation covers how to setup an Airflow instance as a cluster which spans multiple machines instead of the traditional 1 machine distribution. In addition, it covers an added step you can take to ensure High Availability in that cluster.
From business requirements to working pipelines with apache airflowDerrick Qin
In this talk we will be building Airflow pipelines. We’ll look at real business requirements and walk through pipeline design, implementation, testing, deployment and troubleshooting - all that by adhering to idempotency and ability to replay your past data through the pipelines.
Group of Airflow core committers talking about what's coming with Airflow 2.0!
Speakers: Ash Berlin-Taylor, Kaxil Naik, Kamil Breguła Jarek Potiuk, Daniel Imberman and Tomasz Urbaszek.
The data science team at Zymergen is applying machine learning techniques to identify genetic targets, work that is supported by extensive analytical automation that systematically identifies outliers, removes process-related bias, and quantifies performance improvements. We’re using Apache Airflow to construct robust data pipelines that allow us to produce clean, reliable inputs to our predictive models. In this talk, I’ll discuss the unique data processing challenges we face in working with high-throughput, biological data and provide an overview of how we’re using Apache Airflow to meet those challenges.
Contributing to Apache Airflow | Journey to becoming Airflow's leading contri...Kaxil Naik
From not knowing Python (let alone Airflow), and from submitting the first PR that fixes typo to becoming Airflow Committer, PMC Member, Release Manager, and #1 Committer this year, this talk walks through Kaxil’s journey in the Airflow World.
The second part of this talk explains:
how you can also start your OSS journey by contributing to Airflow
Expanding familiarity with a different part of the Airflow codebase
Continue committing regularly & steadily to become Airflow Committer. (including talking about current Guidelines of becoming a Committer)
Different mediums of communication (Dev list, users list, Slack channel, Github Discussions etc)
Introduction to GCP DataFlow PresentationKnoldus Inc.
In this session, we will learn about how Dataflow is a fully managed streaming analytics service that minimizes latency, processing time, and cost through autoscaling and batch processing.
How I learned to time travel, or, data pipelining and scheduling with AirflowLaura Lorenz
****UPDATE: Project is now open sourced at https://www.github.com/industrydive/fileflow****
From Pydata DC 2016
Description
Data warehousing and analytics projects can, like ours, start out small - and fragile. With an organically growing mess of scripts glued together and triggered by cron jobs hiding on different servers, we needed better plumbing. After perusing the data pipelining landscape, we landed on Airflow, an Apache incubating batch processing pipelining and scheduler tool from Airbnb.
Abstract
The power of any reporting tool breaks based on the data behind it, so when our data warehousing process got too big for its humble origins, we searched for something better. After testing out several options such as Drake, Pydoit, Luigi, AWS Data Pipeline, and Pinball, we landed on Airflow, an Apache incubating batch processing pipelining and scheduler tool originating from Airbnb, that provides the benefits of pipeline construction as directed acyclic graphs (DAGs), along with a scheduler that can handle alerting, retries, callbacks and more to make your pipeline robust. This talk will discuss the value of DAG based pipelines for data processing workflows, highlight useful features in all of the pipelining projects we tested, and dive into some of the specific challenges (like time travel) and successes (like time travel!) we’ve experienced using Airflow to productionize our data engineering tasks. By the end of this talk, you will learn
- pros and cons of several Python-based/Python-supporting data pipelining libraries
- the design paradigm behind Airflow, an Apache incubating data pipelining and scheduling service, and what it is good for
- some epic fails to avoid and some epic wins to emulate from our experience porting our data engineering tasks to a more robust system
- some quick-start tips for implementing Airflow at your organization.
Apache Airflow (incubating) NL HUG Meetup 2016-07-19Bolke de Bruin
Introduction to Apache Airflow (Incubating), best practices and roadmap. Airflow is a platform to programmatically author, schedule and monitor workflows.
Presentation given at Coolblue B.V. demonstrating Apache Airflow (incubating), what we learned from the underlying design principles and how an implementation of these principles reduce the amount of ETL effort. Why choose Airflow? Because it makes your engineering life easier, more people can contribute to how data flows through the organization, so that you can spend more time applying your brain to more difficult problems like Machine Learning, Deep Learning and higher level analysis.
Slide deck for the fourth data engineering lunch, presented by guest speaker Will Angel. It covered the topic of using Airflow for data engineering. Airflow is a scheduling tool for managing data pipelines.
Building a Data Pipeline using Apache Airflow (on AWS / GCP)Yohei Onishi
This is the slide I presented at PyCon SG 2019. I talked about overview of Airflow and how we can use Airflow and the other data engineering services on AWS and GCP to build data pipelines.
This presentation covers how to setup an Airflow instance as a cluster which spans multiple machines instead of the traditional 1 machine distribution. In addition, it covers an added step you can take to ensure High Availability in that cluster.
From business requirements to working pipelines with apache airflowDerrick Qin
In this talk we will be building Airflow pipelines. We’ll look at real business requirements and walk through pipeline design, implementation, testing, deployment and troubleshooting - all that by adhering to idempotency and ability to replay your past data through the pipelines.
Group of Airflow core committers talking about what's coming with Airflow 2.0!
Speakers: Ash Berlin-Taylor, Kaxil Naik, Kamil Breguła Jarek Potiuk, Daniel Imberman and Tomasz Urbaszek.
The data science team at Zymergen is applying machine learning techniques to identify genetic targets, work that is supported by extensive analytical automation that systematically identifies outliers, removes process-related bias, and quantifies performance improvements. We’re using Apache Airflow to construct robust data pipelines that allow us to produce clean, reliable inputs to our predictive models. In this talk, I’ll discuss the unique data processing challenges we face in working with high-throughput, biological data and provide an overview of how we’re using Apache Airflow to meet those challenges.
Contributing to Apache Airflow | Journey to becoming Airflow's leading contri...Kaxil Naik
From not knowing Python (let alone Airflow), and from submitting the first PR that fixes typo to becoming Airflow Committer, PMC Member, Release Manager, and #1 Committer this year, this talk walks through Kaxil’s journey in the Airflow World.
The second part of this talk explains:
how you can also start your OSS journey by contributing to Airflow
Expanding familiarity with a different part of the Airflow codebase
Continue committing regularly & steadily to become Airflow Committer. (including talking about current Guidelines of becoming a Committer)
Different mediums of communication (Dev list, users list, Slack channel, Github Discussions etc)
Introduction to GCP DataFlow PresentationKnoldus Inc.
In this session, we will learn about how Dataflow is a fully managed streaming analytics service that minimizes latency, processing time, and cost through autoscaling and batch processing.
Precima data scientist and architect discussing their data science and big data tech stack at the Toronto Data Science & Big Data meetup on Jan 30, 2019 hosted by WeCloudData https://weclouddata.com and sponsored by precima and loyaltyone.
A whitepaper is about How big data engines are used for exploring and preparing data, building pipelines, and delivering data sets to ML applications.
https://www.qubole.com/resources/white-papers/big-data-engineering-for-machine-learning
Unbounded, unordered, global scale datasets are increasingly common in day-to-day business, and consumers of these datasets have detailed requirements for latency, cost, and completeness. Apache Beam defines a new data processing programming model that evolved from more than a decade of experience building Big Data infrastructure within Google, including MapReduce, FlumeJava, Millwheel, and Cloud Dataflow.
Apache Beam handles both batch and streaming use cases, offering a powerful, unified model. It neatly separates properties of the data from run-time characteristics, allowing pipelines to be portable across multiple run-time environments, both open source, including Apache Apex, Apache Flink, Apache Gearpump, Apache Spark, and proprietary. Finally, Beam's model enables newer optimizations, like dynamic work rebalancing and autoscaling, resulting in an efficient execution.
This talk will cover the basics of Apache Beam, touch on its evolution, and describe main concepts in its powerful programming model. We'll show how Beam unifies batch and streaming use cases, and show efficient execution in real-world scenarios. Finally, we'll demonstrate pipeline portability across Apache Apex, Apache Flink, Apache Spark and Google Cloud Dataflow in a live setting.
Catch the Wave: SAP Event-Driven and Data Streaming for the Intelligence Ente...confluent
In our exclusive webinar, you'll learn why event-driven architecture is the key to unlocking cost efficiency, operational effectiveness, and profitability. Gain insights on how this approach differs from API-driven methods and why it's essential for your organization's success.
Streaming Data Ingest and Processing with Apache KafkaAttunity
Apache™ Kafka is a fast, scalable, durable, and fault-tolerant
publish-subscribe messaging system. It offers higher throughput, reliability and replication. To manage growing data volumes, many companies are leveraging Kafka for streaming data ingest and processing.
Join experts from Confluent, the creators of Apache™ Kafka, and the experts at Attunity, a leader in data integration software, for a live webinar where you will learn how to:
-Realize the value of streaming data ingest with Kafka
-Turn databases into live feeds for streaming ingest and processing
-Accelerate data delivery to enable real-time analytics
-Reduce skill and training requirements for data ingest
The recorded webinar on slide 32 includes a demo using automation software (Attunity Replicate) to stream live changes from a database into Kafka and also includes a Q&A with our experts.
For more information, please go to www.attunity.com/kafka.
Qubole Pipeline Services - A Complete Stream Processing Service - Data SheetsVasu S
A Data Sheet about Qubole Pipeline Service to manage streaming ETL pipelines with zero overhead of installation, Integration with Maintenance.
https://www.qubole.com/resources/data-sheets/qubole-pipeline-services
The Open Data Lake Platform Brief - Data Sheets | WhitepaperVasu S
An open data lake platform provides a robust and future-proof data management paradigm to support a wide range of data processing needs, including data exploration, ad-hoc analytics, streaming analytics, and machine learning.
Elasticsearch + Cascading for Scalable Log ProcessingCascading
Supreet Oberoi's presentation on "Large scale log processing with Cascading & Elastic Search". Elasticsearch is becoming a popular platform for log analysis with its ELK stack: Elasticsearch for search, Logstash for centralized logging, and Kibana for visualization. Complemented with Cascading, the application development platform for building Data applications on Apache Hadoop, developers can correlate at scale multiple log and data streams to perform rich and complex log processing before making it available to the ELK stack.
Slides for the talk given on 20-07-2019 at Nairobi JVM. It was a talk about building data pipelines with Apache Kafka as a message broker or enterprise bus and Apache spark as a distributed computing engine that enables processing of large volume of data efficiently.
Privacy-Preserving Machine Learning: secure user data without sacrificing mod...Manning Publications
Privacy Preserving Machine Learning is a comprehensive introduction to data privacy in machine learning. Based on years of DARPA-funded cybersecurity research, the book is filled with lightbulb moments that will change the way you think about algorithm design. You’ll learn how to apply privacy-enhancing techniques to common machine learning tasks, and experiment with source code fresh from the latest academic papers.
Learn more about the book here: http://mng.bz/go5Z
Inside Deep Learning: theory and practice of modern deep learningManning Publications
Inside Deep Learning is an accessible guide to implementing deep learning with the PyTorch framework. It demystifies complex deep learning concepts and teaches you to understand the vocabulary of deep learning so you can keep pace in a rapidly evolving field. No detail is skipped—you’ll dive into math, theory, and practical applications. Everything is clearly explained in plain English.
Learn more about the book here: http://mng.bz/MXyE
Data-Oriented Programming: making data a first-class citizenManning Publications
Eliminate the unavoidable complexity of object-oriented designs. Using the persistent data structures built into most modern programming languages, Data-oriented programming cleanly separates code and data, which simplifies state management and eases concurrency. Data-Oriented Programming teaches you to design applications using the data-oriented paradigm. These powerful new ideas are presented through conversations, code snippets, diagrams, and even songs to help you quickly grok what’s great about DOP. You’ll learn to write DOP code that can be implemented in languages like JavaScript, Ruby, Python, Clojure and also in traditional OO languages like Java or C#.
Learn more about the book here: http://mng.bz/XdKl
Automated Machine Learning in Action reveals how premade machine learning components can automate time-consuming ML tasks. It’s written in a math-lite and accessible style, and filled with hands-on examples for applying AutoML techniques to every stage of a pipeline. You’ll use tools like AutoKeras to create pipelines that automatically select the best approach for your task, remove the burden of manual tuning, and can even be implemented by machine learning novices!
Learn more about the book here: http://mng.bz/Qme1
The Programmer's Brain: improve the way you learn and think about codeManning Publications
The Programmer’s Brain explores the way your brain works when it’s thinking about code. In it, you’ll master practical ways to apply these cognitive principles to your daily programming life. You’ll improve your code comprehension by turning confusion into a learning tool, and pick up awesome techniques for reading code and quickly memorizing syntax. This practical guide includes tips for creating your own flashcards and study resources that can be applied to any new language you want to master. By the time you’re done, you’ll not only be better at teaching yourself—you’ll be an expert at bringing new colleagues and junior programmers up to speed.
Learn more about the book here: https://bit.ly/39gKx9J
Pipeline as Code is a practical guide to automating your development pipeline in a cloud-native, service-driven world. You’ll use the latest infrastructure-as-code tools like Packer and Terraform to develop reliable CI/CD pipelines for numerous cloud-native applications. Follow this book's insightful best practices, and you’ll soon be delivering software that’s quicker to market, faster to deploy, and with less last-minute production bugs.
Learn more about the book here: http://mng.bz/opMv
Tuning Up: From A/B testing to Bayesian optimization teaches you proven methods for improving your production systems. Each method has been tested in industry and is fully explained using basic math and code written in Python and NumPy. The book is filled with real-world use cases for quantitative trading, recommender systems, and social media. You’ll learn how to evaluate changes to your system and explore ways to ensure that your testing is not undermining revenue and other business metrics. By the time you’re done, you’ll be able to seamlessly run effective performance experiments whilst avoiding common mistakes and pitfalls.
Learn more about the book here: http://mng.bz/5jnD
Kubernetes Native Microservices with Quarkus and MicroProfileManning Publications
Kubernetes Native Microservices with Quarkus, and MicroProfile introduces a modern approach to enterprise Java development using new tools designed for cloud-native applications. This book begins by exploring the impact Kubernetes and cloud systems have on your application design. Then, it quickly guides you through setting up an application using MicroProfile APIs, Kubernetes, and Quarkus. Using carefully selected examples and crystal-clear explanations, it guides you step by step from design to deployment.
Learn more about the book here: http://mng.bz/Yqrj
Cloud Native Machine Learning is a guide to bringing your experimental machine learning code to production using serverless capabilities from major cloud providers. You’ll start with best practices for your datasets, learning to bring VACUUM data-quality principles to your projects, and ensure that your datasets can be reproducibly sampled. Next, you’ll learn to implement machine learning models with PyTorch, discovering how to scale up your models in the cloud and how to use PyTorch Lightning for distributed ML training. Finally, you’ll tune and engineer your serverless machine learning pipeline for scalability, elasticity, and ease of monitoring with the built-in notification tools of your cloud platform. When you’re done, you’ll have the tools to easily bridge the gap between ML models and a fully functioning production system.
Learn more about the book here: http://mng.bz/em9w
Spring in Action, 6th Edition guides you through Spring’s core features explained in Craig Walls’ famously clear style. You’ll roll up your sleeves and build a secure database-backed web app step by step. Along the way, you’ll explore reactive programming, microservices, service discovery, RESTful APIs, deployment, and expert best practices. The latest version of a bestseller upgraded for Spring 5.2, this new edition also covers the RSocket specification for reactive networking between applications, and delves deep into essential features of Spring Security. Whether you’re just discovering Spring or leveling up to Spring 5.2, this Manning classic is your ticket!
Learn more about the book here: http://mng.bz/OvQn
Crafting interactive troubleshooting guides and team documentation for your K...Manning Publications
Tyler Leonhardt's slides from the live@Manning Kubernetes conference (June 30th, 2020).
Learn more about live@Manning conferences here: https://freecontent.manning.com/livemanning-conferences/
Entity Framework Core in Action, Second Edition is a comprehensive guide to accessing databases from .NET applications. Updated and upgraded with new content, new diagrams, and new examples, this second edition of the bestselling original begins with a clear breakdown of Entity Framework, along with the mental model behind ORM. You’ll discover time-saving patterns and best practices for security, performance tuning, and even unit testing, as well as tips and tricks developed by the author through their extensive experience working on different client applications. As you go, you’ll address common data access challenges and learn how to handle them with Entity Framework.
Learn more about the book here: https://www.manning.com/books/entity-framework-core-in-action-second-edition
Code like a Pro in C# builds on your existing programming skills to help you seamlessly upskill your coding practice or transition to C# from Java or another OO language. You’ll learn to write the kind of idiomatic C# code that’s essential for enterprise development, honing your mastery with guided coding katas. You’ll start with essential backend skills, putting them into practice with a common career challenge: refactoring a legacy codebase to be secure, clean, and readable. In the second part of the book, you’ll dive into the brand-new Blazor framework for writing browser-based code in C#, securing your role as a full-stack web developer. By the time you’re done, you’ll have a professional-level understanding of C# and be ready to start specializing with advance-level resources.
Learn more about the book here: https://www.manning.com/books/code-like-a-pro-in-c-sharp
Microservices in .NET Core, Second Edition provides a complete guide to building microservice applications. You’ll start by getting to grips with the unique architectural style of microservices, explained in a way that’s clear and accessible. You’ll move on quickly to practical development skills for building your own microservices using MVC Core and ASP.NET Core, working on real-world projects such as an ecommerce shopping cart. You'll design and build individual services in C# and learn how to compose them into a simple but functional application back end. In brand-new coverage for the second edition, you’ll also learn about scoping microservices and how to handle the complexities of deploying to Kubernetes. Along the way, you'll address production and operations concerns like monitoring, logging, and security.
Learn more about the book here: https://www.manning.com/books/microservices-in-net-core-second-edition
Kubernetes in Action, Second Edition teaches you to use Kubernetes to deploy container-based distributed applications. You'll start with an overview of how Docker containers work with Kubernetes and move quickly to building your first cluster. You'll gradually expand your initial application, adding features and deepening your knowledge of Kubernetes architecture and operation. In this revised and expanded second edition, you’ll take a deep dive into the structure of a Kubernetes-based application and discover how to manage a Kubernetes cluster in production. As you navigate this comprehensive guide, you'll also appreciate thorough coverage of high-value topics like monitoring, tuning, and scaling.
Learn more about the book here: https://www.manning.com/books/kubernetes-in-action-second-edition
Core Kubernetes is a reference guide designed to teach operators, SREs, and developers how to improve reliability and performance of Kubernetes-based systems. In it, Kubernetes experts Chris Love and Jay Vyas provide a guided tour through all major aspects of Kubernetes, from managing iptables to setting up dynamically scaled clusters that respond to changes in load. You’ll understand the unique security concerns of container-based applications, discover tips to minimize costly unused capacity, and get pro tips for maximizing performance. This awesome collection of undocumented internals, expert techniques, and practical guidance has invaluable information you won’t find anywhere else.
Learn more about the book on its product page: https://www.manning.com/books/core-kubernetes
In Machine Learning Bookcamp you’ll learn the essentials of machine learning by completing a carefully designed set of real-world projects. Beginning as a novice, you’ll start with the basic concepts of ML before tackling your first challenge: creating a car price predictor using linear regression algorithms. You’ll then advance through increasingly difficult projects, developing your skills to build a churn prediction application, a flight delay calculator, an image classifier, and more. When you’re done working through these fun and informative projects, you’ll have a comprehensive machine learning skill set you can apply to practical on-the-job problems.
Learn more about the book here: https://www.manning.com/books/machine-learning-bookcamp
This fully revised second edition of Machine Learning with TensorFlow teaches you the foundational concepts of machine learning, and how to utilize the TensorFlow library to rapidly build powerful ML models. You’ll learn the basics of regression, classification, and clustering algorithms, applying them to solve real-world challenges such as call center volume prediction and sentiment analysis of movie reviews. Once you’ve mastered core ML concepts, you’ll move on to the money chapters: exploring cutting-edge neural network techniques such as deep speech classifiers, facial identification, and auto-encoding with CIFAR-10. Digest this book, and you’ll be able to start modelling your everyday problems as automated machine learning tasks.
Check out the product page here: https://www.manning.com/books/machine-learning-with-tensorflow-second-edition
While creating secure applications is critically important, it can also be tedious and time-consuming to stitch together the required collection of tools. For Java developers, the powerful Spring Security framework makes it easy for you to bake security into your software from the very beginning. Filled with code samples and practical examples, Spring Security in Action teaches you how to secure your apps from the most common threats, ranging from injection attacks to lackluster monitoring. In it, you’ll learn how to manage system users, configure secure endpoints, and use OAuth2 and OpenID Connect for authentication and authorization.
Learn more about the book here: https://www.manning.com/books/spring-security-in-action
By dividing large applications into separate self-contained units, Microservices are a great step toward reducing complexity and increasing flexibility. Spring Microservices in Action, Second Edition teaches you how to build microservice-based applications using Java and the Spring platform. This second edition is fully updated for the latest version of Spring, with expanded coverage of API routing with Spring Cloud Gateway, logging with the ELK stack, metrics with Prometheus and Grafana, security with the Hashicorp Vault, and modern deployment practices with Kubernetes and Istio.
Learn more about the book here: https://www.manning.com/books/spring-microservices-in-action-second-edition
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I ...Juraj Vysvader
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I didn't get rich from it but it did have 63K downloads (powered possible tens of thousands of websites).
How to Position Your Globus Data Portal for Success Ten Good PracticesGlobus
Science gateways allow science and engineering communities to access shared data, software, computing services, and instruments. Science gateways have gained a lot of traction in the last twenty years, as evidenced by projects such as the Science Gateways Community Institute (SGCI) and the Center of Excellence on Science Gateways (SGX3) in the US, The Australian Research Data Commons (ARDC) and its platforms in Australia, and the projects around Virtual Research Environments in Europe. A few mature frameworks have evolved with their different strengths and foci and have been taken up by a larger community such as the Globus Data Portal, Hubzero, Tapis, and Galaxy. However, even when gateways are built on successful frameworks, they continue to face the challenges of ongoing maintenance costs and how to meet the ever-expanding needs of the community they serve with enhanced features. It is not uncommon that gateways with compelling use cases are nonetheless unable to get past the prototype phase and become a full production service, or if they do, they don't survive more than a couple of years. While there is no guaranteed pathway to success, it seems likely that for any gateway there is a need for a strong community and/or solid funding streams to create and sustain its success. With over twenty years of examples to draw from, this presentation goes into detail for ten factors common to successful and enduring gateways that effectively serve as best practices for any new or developing gateway.
How Recreation Management Software Can Streamline Your Operations.pptxwottaspaceseo
Recreation management software streamlines operations by automating key tasks such as scheduling, registration, and payment processing, reducing manual workload and errors. It provides centralized management of facilities, classes, and events, ensuring efficient resource allocation and facility usage. The software offers user-friendly online portals for easy access to bookings and program information, enhancing customer experience. Real-time reporting and data analytics deliver insights into attendance and preferences, aiding in strategic decision-making. Additionally, effective communication tools keep participants and staff informed with timely updates. Overall, recreation management software enhances efficiency, improves service delivery, and boosts customer satisfaction.
In software engineering, the right architecture is essential for robust, scalable platforms. Wix has undergone a pivotal shift from event sourcing to a CRUD-based model for its microservices. This talk will chart the course of this pivotal journey.
Event sourcing, which records state changes as immutable events, provided robust auditing and "time travel" debugging for Wix Stores' microservices. Despite its benefits, the complexity it introduced in state management slowed development. Wix responded by adopting a simpler, unified CRUD model. This talk will explore the challenges of event sourcing and the advantages of Wix's new "CRUD on steroids" approach, which streamlines API integration and domain event management while preserving data integrity and system resilience.
Participants will gain valuable insights into Wix's strategies for ensuring atomicity in database updates and event production, as well as caching, materialization, and performance optimization techniques within a distributed system.
Join us to discover how Wix has mastered the art of balancing simplicity and extensibility, and learn how the re-adoption of the modest CRUD has turbocharged their development velocity, resilience, and scalability in a high-growth environment.
TROUBLESHOOTING 9 TYPES OF OUTOFMEMORYERRORTier1 app
Even though at surface level ‘java.lang.OutOfMemoryError’ appears as one single error; underlyingly there are 9 types of OutOfMemoryError. Each type of OutOfMemoryError has different causes, diagnosis approaches and solutions. This session equips you with the knowledge, tools, and techniques needed to troubleshoot and conquer OutOfMemoryError in all its forms, ensuring smoother, more efficient Java applications.
Modern design is crucial in today's digital environment, and this is especially true for SharePoint intranets. The design of these digital hubs is critical to user engagement and productivity enhancement. They are the cornerstone of internal collaboration and interaction within enterprises.
We describe the deployment and use of Globus Compute for remote computation. This content is aimed at researchers who wish to compute on remote resources using a unified programming interface, as well as system administrators who will deploy and operate Globus Compute services on their research computing infrastructure.
Field Employee Tracking System| MiTrack App| Best Employee Tracking Solution|...informapgpstrackings
Keep tabs on your field staff effortlessly with Informap Technology Centre LLC. Real-time tracking, task assignment, and smart features for efficient management. Request a live demo today!
For more details, visit us : https://informapuae.com/field-staff-tracking/
Advanced Flow Concepts Every Developer Should KnowPeter Caitens
Tim Combridge from Sensible Giraffe and Salesforce Ben presents some important tips that all developers should know when dealing with Flows in Salesforce.
Globus Compute wth IRI Workflows - GlobusWorld 2024Globus
As part of the DOE Integrated Research Infrastructure (IRI) program, NERSC at Lawrence Berkeley National Lab and ALCF at Argonne National Lab are working closely with General Atomics on accelerating the computing requirements of the DIII-D experiment. As part of the work the team is investigating ways to speedup the time to solution for many different parts of the DIII-D workflow including how they run jobs on HPC systems. One of these routes is looking at Globus Compute as a way to replace the current method for managing tasks and we describe a brief proof of concept showing how Globus Compute could help to schedule jobs and be a tool to connect compute at different facilities.
Prosigns: Transforming Business with Tailored Technology SolutionsProsigns
Unlocking Business Potential: Tailored Technology Solutions by Prosigns
Discover how Prosigns, a leading technology solutions provider, partners with businesses to drive innovation and success. Our presentation showcases our comprehensive range of services, including custom software development, web and mobile app development, AI & ML solutions, blockchain integration, DevOps services, and Microsoft Dynamics 365 support.
Custom Software Development: Prosigns specializes in creating bespoke software solutions that cater to your unique business needs. Our team of experts works closely with you to understand your requirements and deliver tailor-made software that enhances efficiency and drives growth.
Web and Mobile App Development: From responsive websites to intuitive mobile applications, Prosigns develops cutting-edge solutions that engage users and deliver seamless experiences across devices.
AI & ML Solutions: Harnessing the power of Artificial Intelligence and Machine Learning, Prosigns provides smart solutions that automate processes, provide valuable insights, and drive informed decision-making.
Blockchain Integration: Prosigns offers comprehensive blockchain solutions, including development, integration, and consulting services, enabling businesses to leverage blockchain technology for enhanced security, transparency, and efficiency.
DevOps Services: Prosigns' DevOps services streamline development and operations processes, ensuring faster and more reliable software delivery through automation and continuous integration.
Microsoft Dynamics 365 Support: Prosigns provides comprehensive support and maintenance services for Microsoft Dynamics 365, ensuring your system is always up-to-date, secure, and running smoothly.
Learn how our collaborative approach and dedication to excellence help businesses achieve their goals and stay ahead in today's digital landscape. From concept to deployment, Prosigns is your trusted partner for transforming ideas into reality and unlocking the full potential of your business.
Join us on a journey of innovation and growth. Let's partner for success with Prosigns.
Software Engineering, Software Consulting, Tech Lead.
Spring Boot, Spring Cloud, Spring Core, Spring JDBC, Spring Security,
Spring Transaction, Spring MVC,
Log4j, REST/SOAP WEB-SERVICES.
top nidhi software solution freedownloadvrstrong314
This presentation emphasizes the importance of data security and legal compliance for Nidhi companies in India. It highlights how online Nidhi software solutions, like Vector Nidhi Software, offer advanced features tailored to these needs. Key aspects include encryption, access controls, and audit trails to ensure data security. The software complies with regulatory guidelines from the MCA and RBI and adheres to Nidhi Rules, 2014. With customizable, user-friendly interfaces and real-time features, these Nidhi software solutions enhance efficiency, support growth, and provide exceptional member services. The presentation concludes with contact information for further inquiries.
Accelerate Enterprise Software Engineering with PlatformlessWSO2
Key takeaways:
Challenges of building platforms and the benefits of platformless.
Key principles of platformless, including API-first, cloud-native middleware, platform engineering, and developer experience.
How Choreo enables the platformless experience.
How key concepts like application architecture, domain-driven design, zero trust, and cell-based architecture are inherently a part of Choreo.
Demo of an end-to-end app built and deployed on Choreo.
A Comprehensive Look at Generative AI in Retail App Testing.pdfkalichargn70th171
Traditional software testing methods are being challenged in retail, where customer expectations and technological advancements continually shape the landscape. Enter generative AI—a transformative subset of artificial intelligence technologies poised to revolutionize software testing.
Large Language Models and the End of ProgrammingMatt Welsh
Talk by Matt Welsh at Craft Conference 2024 on the impact that Large Language Models will have on the future of software development. In this talk, I discuss the ways in which LLMs will impact the software industry, from replacing human software developers with AI, to replacing conventional software with models that perform reasoning, computation, and problem-solving.
Multiple Your Crypto Portfolio with the Innovative Features of Advanced Crypt...Hivelance Technology
Cryptocurrency trading bots are computer programs designed to automate buying, selling, and managing cryptocurrency transactions. These bots utilize advanced algorithms and machine learning techniques to analyze market data, identify trading opportunities, and execute trades on behalf of their users. By automating the decision-making process, crypto trading bots can react to market changes faster than human traders
Hivelance, a leading provider of cryptocurrency trading bot development services, stands out as the premier choice for crypto traders and developers. Hivelance boasts a team of seasoned cryptocurrency experts and software engineers who deeply understand the crypto market and the latest trends in automated trading, Hivelance leverages the latest technologies and tools in the industry, including advanced AI and machine learning algorithms, to create highly efficient and adaptable crypto trading bots
Gamify Your Mind; The Secret Sauce to Delivering Success, Continuously Improv...Shahin Sheidaei
Games are powerful teaching tools, fostering hands-on engagement and fun. But they require careful consideration to succeed. Join me to explore factors in running and selecting games, ensuring they serve as effective teaching tools. Learn to maintain focus on learning objectives while playing, and how to measure the ROI of gaming in education. Discover strategies for pitching gaming to leadership. This session offers insights, tips, and examples for coaches, team leads, and enterprise leaders seeking to teach from simple to complex concepts.
Gamify Your Mind; The Secret Sauce to Delivering Success, Continuously Improv...
Data Pipelines with Apache Airflow
1. Better Data Pipeline
Management
With Data Pipelines with Apache Airflow.
Take 42% off the book by entering
slharenslak into the discount code box at
manning.com.
2. A successful pipeline moves data efficiently, minimizing pauses and blockages
between tasks, keeping every process along the way operational. Apache
Airflow provides a single customizable environment for building and
managing data pipelines, eliminating the need for a hodge-podge collection of
tools, snowflake code, and homegrown processes.
3. Using real-world scenarios and
examples, Data Pipelines with Apache
Airflow teaches you how to simplify
and automate data pipelines, reduce
operational overhead, and smoothly
integrate all the technologies in your
stack.
Airflow lets you schedule, restart,
and backfill pipelines, and its easy-
to-use UI and workflows with
Python scripting has users praising
its incredible flexibility
4. Data Pipelines with Apache Airflow is your essential guide to working with the
powerful Apache Airflow pipeline manager. In it, you’ll learn how to
automate moving and transforming data, managing pipelines by backfilling
historical tasks, developing custom components for your specific systems,
and setting up Airflow in production environments.
5. What people are saying
about the book:
A great intro to
what a DAG is and
the basics behind
its architecture.
-Vlad Navitski
A great introduction
to Apache Airflow.
It's well-written and
well thought out.
-Kent Spillner
Easy to read and
provides a range
of tips to be
productive with
Airflow.
-Eric Platon
6. About the authors:
Bas Harenslak and Julian de
Ruiter are data engineers with
extensive experience using
Airflow to develop pipelines for
major companies including
Heineken, Unilever, and
Booking.com. Bas is a
committer, and both Bas and
Julian are active contributors to
Apache Airflow.
7. With Data Pipelines with Apache Airflow.
Take 42% off the book by entering
slharenslak into the discount code box at
manning.com.
If you want to learn more about the book,
you can check it out on our browser-
based liveBook reader here.