CodeIsGo.com

When evaluating a Kotlin Multiplatform solution, it was very important to our team that we understand how we could build a CI/CD pipeline for the project. It needed to be easy for our team to push changes and build a new version of the project. By Nate Ebel, Android Engineer.

Both our iOS and Android applications use GitHub Actions for our CI needs. So, in this post, we’ll walkthrough how to setup a GitHub Actions workflow for building a Kotlin Multiplatform Mobile project.

The article covers:

• Creating a GitHub actions workflow for Kotlin Multiplatform Mobile
• Setting up our workflow environment
• Configuring a job to build a Kotlin Multiplatform Mobile Project
• Checking out Kotlin Multiplatform and Swift package repos
• Setting up Java and Xcode tooling
• Extracting project version for Git tagging
• Building the artifacts
• Publishing the JVM artifacts
• Reviewing a PR workflow solution

… and more.

These workflows have worked well for us in the past 1.5 years. Authors publishing model for their Swift Package is evolving, but the workflow itself has worked great. Nice one!

The current influx of data — structured, semi-structured, and unstructured — being driven by an array of data sources is fueling opportunities to leverage machine learning to extract insights and accelerate innovations that can transform businesses and industries. As these data volumes continue to rise, companies are struggling with the complicated task of managing this data and figuring out how to harness it for analytics and AI. By Vedant Jain, Denny Lee.

The article explains:

• What is Delta Lake?
• What is Amazon SageMaker Studio?
• Integrate SageMaker Studio with Delta Lake
• The benefits of connecting SageMaker Studio and Delta Lake

Delta Lake is an open-source storage framework that enables building a Lakehouse architecture with compute engines, including Spark, PrestoDB, Flink, Trino, and Hive, and APIs for Scala, Java, Rust, Ruby, and Python. Delta Lake is a great option for storing data in the AWS Cloud because it reads and writes in open-source Apache Parquet file format. This format makes it easy to write connectors from engines that can process Parquet. Nice one!

The way we measure and optimize website speed is always changing. New web standards are introduced (and eventually widely supported), new tools are developed, and new metrics suggested. By Matt Zeunert.

This article takes a look at some of the ways that the web performance landscape changed in 2022:

• Priority hints
• No more OSCP requests in Chrome
• Interaction to Next Paint Metric
• Desktop core web vitals as a ranking factor
• Back/forward cache in Chrome
• View observed metrics in PageSpeed Insights
• HTTP/3 standardized
• Better data on what requests are render-blocking
• Chrome DevTools performance insights panel
• 103 early hints
• Full page prerendering in Chrome

… and more. A lot of new browser features have become available to improve website performance in the last year. We also have new tools to measure and improve site speed. Good read!

It’s not a secret that the Angular community has needed better tools to inspect the structure of Angular applications and profile their performance. Angular DevTools has been introduced for just that! By Nethmi Wijesinghe.

Source: https://www.syncfusion.com/blogs/post/debug-angular-apps-easily-using-angular-devtools.aspx

This article will go through Angular DevTools in detail and provide step-by-step guidance on making the best of it:

• Angular DevTools
• Getting started with Angular DevTools
• Debugging the application
• Look up a component or directive
• Profiling the application
• Understand the application’s execution

In this article, author discussed the features of Angular DevTools and how to use them. Even though it’s relatively new to the Angular community, DevTools eases your development process and brings transparency. Author encourages you to try it out. Nice one!

Older article about building neural networks from scratch. From the math behind them to step-by-step implementation coding samples in Python with Google Colab. By Pratik Shukla, Roberto Iriondo.

Source: https://pub.towardsai.net/building-neural-networks-from-scratch-with-python-code-and-math-in-detail-i-536fae5d7bbf

This tutorial explains (amongst others):

• What is a neural network?
• Applications of Artificial Neural Networks
• General structure of an Artificial Neural Network (ANN)
• What is a Perceptron?
• Where we can use Perceptrons?
• Neural Network implementation from scratch

… and more. Comprehensive list of resources for further reading is also including. Fabulous!

Digital services made for consumers are opening up new opportunities and vulnerabilities. With more employees bringing unmanaged devices to the office, business networks can be accessed by many more people. Plus, remote work means that an organization’s IT perimeter is no longer restricted within its walls. By Mihaela Marian.

In the article you will find information on:

• What is Continuous Adaptive Risk and Trust Assessment (CARTA)?
• Why is Role-Based Access Control (RBAC) inadequate?
• How CARTA works
• How CARTA relates to other risk assessments
• How to implement Continuous Adaptive Risk and Trust Assessment
• CARTA vs. Zero-Trust

CARTA continuously evaluates all users and devices and makes contextual access decisions. It has its roots in the Zero-Trust framework, which advocates the idea that no user or device can be trusted, even if they’re already on your network. Companies with zero trust security go to great lengths to ensure that only appropriate access is granted to critical assets. Good read!

The growing popularity of serverless architectures has led to an increased need for solutions to the modern challenges of microservice observability—one of the most critical components for running high-performing, secure, and resilient serverless applications By @DeveloperSteve.

In this article, we will:

• Explore the challenges that serverless architectures present to observability
• Suggest possible solutions
• Identify the hidden costs of these solutions
• Discuss ways to mitigate such expenses

In serverless environments, not only are you abstracted from the underlying infrastructure that runs your code, but the distributed, event-driven nature of serverless applications makes traditional approaches to monitoring and debugging ineffective. Serverless functions are often chained through asynchronous event sources such as AWS SNS, SQS, Kinesis, or DynamoDB, making tracing extremely difficult. Interesting read!

Observability-driven DevOps and SRE automation can help enterprises achieve SLO goals and reduce MTTR. But, how do you get started? By Rob Jahn.

We refer to this culture and practice as observability-driven DevOps and SRE automation. The article discusses:

• The role of observability within DevOps
• The results of observability-driven DevOps speak for themselves
• 5 steps to achieve observability-driven automation
• Gain visibility into your existing releases
• Report and act upon SLOs for your critical services
• Automate release validation through SLO health scoring
• Speed up existing delivery pipelines through SLO-driven orchestration
• Reduce MTTR through SLO-driven remediation

Automating and orchestrating DevOps remediation action and incident response starts by adopting and integrating SLOs within enterprise processes. This automation also relies on integrating tools for releases, notifications, and incident management. This connection empowers platform and site reliability engineers to automate release validation, improve resiliency engineering, support multi-stage delivery, and incorporate automated problem remediation. Good read!

People expect exceptional performance when they access your site. They want quick load times, stable layouts and quick interactivity, regardless of whether they’re on desktop or mobile. By Ben Schwarz.

However, there are a near-limitless number of ways you could try to measure web performance, and some are far better than others. These 7 website performance metrics allow you to understand how your web page performs across several different page load aspects:

• Largest Contentful Paint (LCP)
• Cumulative Layout Shift (CLS)
• Total Blocking Time (TBT)
• Interaction to Next Paint (INP)
• Time to First Byte (TTFB)
• Number of Third Party Scripts
• Time to Interactive (TTI)
• Commonly tracked metrics you should avoid

Too much data can be just as harmful as not enough. For that reason, you need to ensure you’re only tracking the best possible website performance metrics. These three metrics are often tracked but should be avoided: First Input Delay, First Meaningful Paint, Performance Score. Interesting read!

A four-year-old company is coming to market soon with an unexpected technology to cool CPUs and SoCs. Frore Systems has developed a cooling chip it calls AirJet that sits on top of a heat-generating chip and cools it without the need for mechanical fans. By Josh Norem.

It’s 2.8mm thick and uses pulsating inlets to suck air into it and exhaust it out the sides. The company claims its “solid-state” cooling solution allows for double the CPU performance compared with using traditional methods. It’s secured $100 million in funding and is now partnering with Intel to bring its technology to the company’s Evo line of laptops.

The AirJet is designed to deal with the ever-shrinking nature of our electronic devices. As phones, tablets, and laptops get smaller, cooling them becomes more difficult. When insufficient cooling is applied, a CPU will throttle, lowering its clock speeds to reduce temps. This naturally results in decreased performance. Frore Systems claims its AirJet tackles this problem better than a fan, without taking much room inside the device. The heart of the issue is how long a CPU can maintain its maximum clock speed with peak power consumption.

According to CEO Dr. Seshu Madhavapeddy in an interview with PCWorld, a 1.8GHz ARM processor with four AirJet Minis will be able to run at 3.5GHz “forever.” An AirJet Pro that’s made for x86 could run at PL1 at 2.1GHz instead of 1.4GHz with a fan. Additionally, the AirJet in a 15-inch laptop would produce just 29 dBA of sound, instead of 42 dBA with a fan. Interesting read!