As a Software Engineer with 10 years of experience, my development practices have been drastically changed with the LLM-based rapid evolution of Generative AI in the past year.
Here I am not trying to list down all the AI tools that I used, But the practices that I am following to increase my productivity by 200% plus.
Continue readingBy following this guide, you’ll be able to quickly and easily set up a Kubernetes cluster on your Windows PC with the following tech stack
Kind is a simple, lightweight CNCF-certified Kubernetes installer CNCF K8s Installer
Compared to Minikube, Kind provides support for Hyperkit on Mac and Hyper-V on Windows hypervisors, including features such as Load balancer and Ingress support. Additionally, Kind supports multi-node clusters, including those with high availability (HA).
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#Kubectl Kind using powershell
curl.exe -Lo kind-windows-amd64.exe https://kind.sigs.k8s.io/dl/v0.22.0/kind-windows-amd64
Move-Item .\kind-windows-amd64.exe C:\Dev\env\kind\kind.exe
#Kubectl Install
curl.exe -LO "https://dl.k8s.io/release/v1.30.0/bin/windows/amd64/kubectl.exeCreating a cluster with 1 control plane node and 3 workers
apiVersion: kind.x-k8s.io/v1alpha4
kind: Cluster
name: ckad-cluster
nodes:
- role: control-plane
- role: worker
- role: worker
- role: workerThis will create all the necessary k8s control plane objects and worker nodes
Spock aims to be a more powerful alternative to the traditional JUnit stack, by leveraging Groovy features which seamlessly integrate with Java
JUNIT -> SPOCK -> CUCUMBER
Spock lies between junit and cucumber
Date : 2022-12-12 5.57 PM
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Spring auto-configuration can be tricky when it comes to conditional based bean creation. The best way to ensure the proper application context is through meticulous testing.
Spring Boot 2.X provides some test helpers for easily configuring an ApplicationContext to simulate auto-configuration test scenarios.
Utility design to run an ApplicationContext and provide AssertJ style assertions. The test is best used as a field of a test class,
Let’s try this with a use case,
Let’s assume the application consists of multiple features and these features are toggled ( bean creation ) by environment configuration-based conditions,
All the features of the application are defined as an enum and the enum contains a code and the application configuration itself. For simplicity let’s consider an app with 3 features.
| public enum AppHubFeature { | |
| LOGISTIC_UNIT_UPDATE("Logistic Unit Update", FeatureConfig.LOGISTIC_UNIT_UPDATE), | |
| ORDER_STATUS_UPDATE("Order Status Update", FeatureConfig.ORDER_STATUS_UPDATE), | |
| STOCK_ADJUSTMENT("Stock Adjustment", FeatureConfig.STOCK_ADJUSTMENT); | |
| public static class FeatureConfig { | |
| public static final String LOGISTIC_UNIT_UPDATE = "app-hub.feature.logistic-unit-update"; | |
| public static final String ORDER_STATUS_UPDATE = "app-hub.feature.order-line-status-update"; | |
| public static final String STOCK_ADJUSTMENT = "app-hub.feature.stock-adjustment"; | |
| } | |
| public final String feature; | |
| public final String config; | |
| AppHubFeature(String feature, String config) { | |
| this.feature = feature; | |
| this.config = config; | |
| } | |
| public String config() { | |
| return this.config; | |
| } | |
| public String feature() { | |
| return this.feature; | |
| } | |
| } |
This is a monitoring infrastructure building task with some basic matrices. where the metrics are extracted, processed and visualized using the proposed setup to facilitate data-driven decision making.
Specifically, the following metrics were introduced,
Any performance metrics analyzing platform based on following basic steps
Windows Subsystem for Linux (WSL) 2 provides a seamless Linux integration with many features. As developers, we can take full advantage of both OS at the same time.
For this example, I am using a Spring Boot project located in windows and run the project on a WSL2 Linux environment.
Continue readingLog4j22 provides multiple ways of creating a custom layout for many requirements. This article will explain simple ways to implement custom layouts using log4j2 plugins
In Log4j 2 a plugin is declared by adding a @Plugin annotation to the class declaration. During initialization, the Configuration will invoke the PluginManager to load the built-in Log4j plugins as well as any custom plugins.
We can use both AbstractStringLayout or LogEventPatternConverter according to our requirements. Both options will provide a way to access log4j LogEvent that has all the relevant details about the log event to be customized.
