Agile, which started off as a better and more practical method of software development proposed by a group of developers, is now transforming the way in which organizations are run. Agile is now adopted by banks, manufacturers, research & development centers, hospitals, and even airports for execution. 

When the scale and reach of Agile increased, newer frameworks such as Scaled Agile Framework (SAFe), Large Scale Scrum, Nexus, and so on gained popularity. Enterprise agility and business agility is radically changing the way in which organizations are structured. 

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Value Stream Management (VSM) is about empowering delivery organizations to measure, mitigate, and monitor complexity. Simply put, it aims at improving the flow of value in your organization. The VSM Consortium recently released their highly anticipated report on The State of Value Stream Management Report 2022.  

In this article, we recap some of the findings and look at it specifically from a software engineering and DevOps point of view. Can we capture some key lessons that lead to healthier and more productive engineering teams? What has worked and what has not? Can we simplify and adapt ideas of organizational change to create a thriving engineering organization?

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In this tutorial, we’ll go over how to use and understand React Hooks. This article is an extension of article how-to-manage-state-with-hooks-on-react-components. It has been expanded with other Hooks and logic and Lessons Learned.

Here we create a simple product page with a shopping cart (see image 2). The shopping cart represents the memory (or the ‘state’) of the product page. The state generally refers to application data that must be tracked.

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Efficient code doesn’t just run faster; if it’s using less compute-resource, it may also be cheaper to run. In particular, distributed cloud applications can benefit from fast, lightweight serialization. 

OpenSource Java Serializer

Chronicle-Wire is an OpenSource Java serializer that can read and write to different message formats such as JSON, YAML, and raw binary data. This serializer can find a middle ground between compacting data formatting (storing more data in the same space) versus compressing data (reducing the amount of storage required). Instead, data is stored in as few bytes as possible without causing performance degradation. This is done through marshaling an object.

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In a previous post, I showed you how to use AWS CDK to automate the deployment and configuration of your Apache Airflow environments using Managed Workflows for Apache Airflow (MWAA) on AWS. In this quick how-to guide, I will share how you can use Terraform to do the same thing.

You will need:

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Technologies such as artificial intelligence (AI), machine learning (ML), and natural language processing (NLP) have led the way to software robots that reduce the manual, time-consuming, and repetitive actions performed on digital platforms. The concept of automating tasks on digital platforms is called robotic process automation (RPA). RPA is a software robot that interacts with computer-centric processes and aims to introduce a digital workforce that performs repetitive tasks previously completed by humans. This Refcard introduces RPA technology, how it works, key components, and how to set up your environment.
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Tabular data is one of the best sources of data on the web. They can store a massive amount of useful information without losing its easy-to-read format, making it gold mines for data-related projects.

Whether it is to scrape football data or extract stock market data, we can use Python to quickly access, parse and extract data from HTML tables, thanks to Requests and Beautiful Soup.

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I have lost count of the number of times I have been told that Java is not a suitable language in which to develop applications where performance is a major consideration. My first response is usually to ask for clarification on what is actually meant by “performance” as two of the most common measures – throughput and latency, sometimes conflict with each other, and approaches to optimise for one may have a detrimental effect on the other. 

Techniques exist for developing Java applications that match, or even exceed, the performance requirements of applications that have been built using languages more traditionally used for this purpose. However, even this may not be enough to get the best performance from a latency perspective. Java applications still have to rely on the Operating System to provide access to the underlying hardware. Typically latency-sensitive (often called “Real Time”) applications operate best when there is almost direct access to the underlying hardware, and the same applies to Java. In this article, we will introduce some approaches that can be taken when we want to have our applications utilise system resources most effectively. 

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With more and more digitalization, there are more requirements for mobile and mobile apps that we use daily. The increase in mobile storage spaces raised to 256 GB, which is sure to increase as we meet customer needs, add new features, and support apps on different screen sizes. 

Based on the report, 74% of the world uses Android, and around 70% of users look for the app size before installing any app.

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This is an article from DZone’s 2022 Database Systems Trend Report.

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One of the key components of microservices is how to manage and access data. The means to do that are different compared to traditional monolithic or three-tier applications. Some patterns are quite common, but others are specific and need to be evaluated before being incorporated into a solution. We will briefly go over some of these common database patterns for microservices before exploring CQRS (including how it differs from CRUD) and, finally, look at how it can be combined with event sourcing.

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