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Environment Variables in Kubernetes: A Simplified Guide

Environment variables play a critical role in configuring and managing applications, especially in containerized environments like Kubernetes.
Advantages of using environment variables include dynamic configuration, enhanced security, and portability.
Different ways to define environment variables in Kubernetes include static variables in pod specs, using ConfigMaps for non-sensitive data, and using Secrets for sensitive data.
Best practices for using environment variables include using Secrets for sensitive data, storing non-sensitive configurations in ConfigMaps, avoiding hardcoding values in application code, and documenting all required environment variables.

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Dev

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Will DevOp skills be a must for developers in the future? (From my journey)

The author shares their journey of transitioning into a DevOps Engineer role after their startup was going to shut down.
They had to learn and pass the AWS Cloud Practitioner Exam in order to be accepted for the position.
Although they decided not to continue as a DevOps Engineer, the knowledge gained was valuable in their current role as a FullStack developer.
The author believes that integrating DevOps skills will become a necessity for developers in the future.

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Dev

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How to Easily Manage Work Across Multiple Git Branches

1. Create and Switch Between Branches: Use git branch to create new branches and git checkout or git switch to switch between branches.
2. Work on Multiple Branches Simultaneously: Open different branches in separate terminal windows/tabs or use multiple text editor windows.
3. Stash Changes to Switch Branches Temporarily: Use git stash to temporarily save changes before switching branches.

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Dev

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Our Gitlab journey. Migrating from Docker+Machine to Kubernetes

GitLab is discontinuing the Docker+Machine executor, prompting many teams to migrate to Kubernetes for running CI jobs.
GitLab SaaS's experience often falls short of its potential for teams using their platform at scale.
Currently, GitLab CI/CD is used primarily by an e-commerce retailer with circa 1,000 tech department colleagues with over 400 active GitLab users.
The decision to migrate wasn't difficult for them with Kubernetes as an easy fit, but the process of migrating was a challenge.
GitLab provides documentation, but it's often high-level, fragmented, and doesn't go deep enough to address real-world scenarios.
There are several challenges in the migration process, such as runner registration and management, handling runner tokens, and helm chart updates.
In response to these challenges, they implemented dynamic runner configuration, token retrieval workflow, pipeline resilience, and a custom helper image.
They suggest GitLab needs to provide migration-specific documentation, clear examples of Kubernetes-based workflows, and ensure version upgrades don't break runner registrations and other workflows.
The migration to Kubernetes is possible, but it's important to adapt and experiment to improve developer experience.
Improving documentation and minimizing breaking changes would help teams like theirs more effectively navigate the migration process.

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Dev

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Deploy Your Ghost Blog in Minutes with KVMPods

To deploy your Ghost blog quickly and easily, you can use KVMPods pre-made template or customize your own Docker Compose configuration.
Ghost is a modern publishing platform known for its clean design, built-in SEO tools, native newsletter system, member subscriptions, custom themes, and markdown support.
Option 1: Quick deploy with KVMPods template allows you to log into your KVMPods dashboard, find the Ghost template, and follow the setup wizard to deploy.
Option 2: Custom deployment offers a production-ready Docker Compose template with features such as health checks for MySQL, persistent volume storage, and secure networking.

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Dev

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Sherlock Holmes and The Case of the Cloudflare Timeout Mystery

Clients were experiencing Cloudflare's Gateway Timeout error after migrating to Kubernetes.
Investigation revealed that server restarts during pod restarts were causing the issue.
The root cause was identified as the cold start time of new containers in Kubernetes.
The solution involved implementing Readiness Probes in the Kubernetes configuration.

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Dev

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Allwinner T527 SystemOnModule Adapts for Android 13

FET527N-C system on module (SoM) has successfully been adapted for Android 13.
The FET527N-C SoM offers performance and compatibility enhancement with Allwinner's high-performance T527 series processor.
Users of the FET527N-C SoM running Android 13 can enjoy a rich application ecosystem and improved fluency and stability.
The FET527N-C SoM excels in hardware acceleration features, image processing, and video encoding, providing better functional performance.

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Dev

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Building the Foundation: How to Connect to a Windows Virtual Machine and install Windows Server

Create a Windows Virtual Machine on Azure and wait for deployment to complete
Connect to the Windows Virtual Machine using RDP and input the password
Install Windows Server using PowerShell command
Verify the installation by accessing the VM's IP address in a browser

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Amazon

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Dissecting the Performance Gains in Amazon Q Developer agent for code transformation

Amazon Q Developer Agent is an AI-powered tool that modernizes code bases from Java 8 and Java 11 to Java 17.
The tool simplifies the migration process and reduces time and effort compared to the manual process.
Amazon Q suggests and verifies code changes, using AI to debug compilation errors.
The enhanced debugger agent significantly improves transformation efficiency and quality compared to the existing debugger.
The debugger AI possesses more tools, remembers previous errors, intelligently backtracks, and analyzes multiple errors.
The debugger AI is re-architected as a multi-agent system and limits hallucinations and drives towards progress.
Amazon Q Developer Agent is able to help update recurring issues automatically.
The results showed an 85% higher success rate compared to the previous approach in testing 62 large open-source applications.
The enhancement significantly boosts both the quality and efficiency of code transformation, marking a substantial leap forward in automated application modernization for Java.
Amazon Q Developer aims to provide developers and organizations with modern, cloud-native architectures, and to accelerate enterprise application modernization.

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Dev

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1MinDocker #7 - Superpower your builds with buildx

Buildx is a Docker plugin aimed at replacing the legacy docker build command.
Buildx provides multiple features not available in the legacy builder such as choosing drivers, creating isolated builder instances, and enabling multi-platform builds.
Drivers allow you to choose the environment where the build will run, including docker-container, kubernetes, and remote environments.
Multi-platform builds can be achieved by specifying platforms, using different builder instances, or using kernel emulation through QEMU.

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Dev

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Mastering AWS DevOps with 20 Essential Services

AWS CloudFormation automates resource deployment and supports YAML/JSON templates.
AWS Cloud Development Kit (CDK) lets you define AWS infrastructure using Python, TypeScript, or Java.
AWS CloudWatch provides real-time monitoring and offers metrics, dashboards, alarms, and logs.
AWS CodePipeline automates the software release process and supports integration with GitHub, Jenkins, and CodeBuild.
AWS CodeBuild is a fully managed build service that compiles code, runs tests, and produces deployable artifacts.
AWS CodeDeploy automates application deployments across compute platforms.
AWS Systems Manager is a unified interface for managing AWS resources and automating operational tasks.
AWS IAM (Identity and Access Management) manages access and permissions for AWS resources.
Amazon VPC (Virtual Private Cloud) allows you to host applications in private and secure networks with fine-tuned access controls.
Amazon ECS (Elastic Container Service) is a fully managed container orchestration service for Docker workloads.

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Hashicorp

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5 ways to improve DevEx and security for infrastructure provisioning

Organizations need to stop using most of their manual infrastructure provisioning and review workflows and start giving developers the keys to provision their own infrastructure (i.e. servers, databases, load balancers, caches, firewall settings, queues, monitoring, subnet configurations, routing rules) on a platform with great developer experience (DevEx).
By automating infrastructure provisioning, using an infrastructure as code (IaC) solution, organizations can achieve both speed and control.
Use IaC and create templates for various teams, to stop reinventing the wheel.
To address the challenge of enforcing policy consistently across an organization, many organizations use automated policy-as-code checks.
Self-service addresses this issue and enables organizations to scale cloud infrastructure for greater innovation quickly and efficiently.
By automating infrastructure destruction, organizations can set end-of-life dates or pre-defined inactivity periods and use them to remove cloud infrastructure without the need for manual tracking, audits, or intervention.
Leveraging best practices for ILM and leaning into automation can eliminate provisioning bottlenecks, accelerate developer workflows, and help organizations go to market faster — all without compromising on compliance or security.
Vodafone automated 95% of infrastructure provisioning using IaC, accelerated their release cadence by 3X, cut infrastructure setup time from three months to one week, and did it all while ensuring every compliance requirement was met.
Trimble reduced infrastructure development from three days to one hour and enabled the company to control deployment based on specific policies, helping developers identify compliance, security, and governance issues much earlier in the development cycle.
Cielo S.A. used standard configurations to reduce infrastructure provisioning time by 90%, resulting in a 5X increase in speed to market while also meeting their security and compliance goals.

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Siliconangle

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Three insights you might have missed from KubeCon + CloudNativeCon NA

Artificial intelligence is driving innovation in cloud-native technologies, streamlining processes and enhancing decision-making across industries.
Automation and innovation remains central to unlocking Kubernetes' full potential, according to Mike Barrett, vice president and general manager of hybrid cloud platforms at Red Hat Inc.
Kubernetes AI advancements play a pivotal role in enhancing scalability and flexibility for AI workloads, with Nutanix Inc and MinIO Inc offering scalable and secure AI infrastructure.
Open-source ecosystems continue to be the foundation of innovation in Kubernetes AI, enabling organizations to scale solutions while fostering collaboration across industries.
Enterprises are embracing advanced tools to transform legacy systems and drive operational efficiency, with Red Hat's enhanced OpenShift Virtualization platform providing hybrid cloud solutions.
Kubernetes AI models are being used to efficiently queue tasks across multiple cloud environments, as modern observability tools identify inefficiencies and help identify significant cost savings for enterprises.
Recent upgrades to Google Kubernetes Engine have expanded its capacity to support clusters of up to 65,000 nodes, meeting the scalability needs of modern AI applications.
Intel Corp's Open Platform for Enterprise AI provides a vendor-neutral framework that integrates more than 30 cloud-native microservices, allowing customized AI applications with single-click deployment.
Oracle Corp's contributions to the Cloud Native Computing Foundation further emphasize the critical role of Kubernetes AI in advancing generative models and simplifying service launches, prioritizing cross-sector collaboration and innovation.
Red Hat is driving Kubernetes AI innovation through its collaborative Kubernetes solutions to create accessible, cost-effective tools for domain-specific applications and addressing the challenges of deploying, scaling AI workloads.

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The New Stack

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Dapr Graduates CNCF and Connects to WebAssembly

Microsoft led Dapr project has graduated from the Cloud Native Computing Foundation (CNCF), and is now focussed on the growing use of WebAssembly (WASM) for enhanced security features, ultra-low latency, and other benefits.
Dapr enables organisations to leverage simple and user-friendly APIs in Kubernetes environments instead of requiring developers to master complex Kubernetes concepts and infrastructure setup.
Dapr has grown to over 3,700 individual contributors, used by tens of thousands of organisations, and has robust security mechanisms for enforcing zero-trust policies and seamless infrastructure integration across entire infrastructures.
Projects in which Dapr integrates includes OpenTelemetry for observability data, Prometheus for metrics, and gRPC and CloudEvents for sending communications between application services.
The CNCF graduation is a significant milestone in its own right as Dapr releases new developer APIs every quarter, including workflows, secrets, configuration management and LLMs.
The Wasm sidecar for Dapr is gaining traction as well, making the developer experience easier to deliver value as quickly as possible without worrying about the underlying implementation.
During the talk at KubeCon + CloudNativeCon, Next-Level Powers, Dapr was discussed as a platform to create an abstraction layer around whatever implementation a company chooses.
To help developers think less about everything surrounding them, a SpinKube Triumvirate using Dapr, KEDA and SpinKube was introduced.
Dapr provides an abstraction to infrastructure so developers can focus entirely on their creating applications with a sidecar mechanism for Pub/Sub, eliminating unnecessary complexity.
Dapr is built on the actor model, making it easier to structure code based on communication patterns and consists of multiple building blocks, including state management, Pub/Sub, security and observability. Developers don’t need to worry about the underlying implementation of these components.

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Dev

317

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The Pocket Guide to Internal Developer Platform

Developer self-serve refers to a model where developers have direct access to the tools, resources, and infrastructure they need.
Key components include automated provisioning, self-service access to resources, on-demand scaling, streamlined deployment pipelines, and comprehensive documentation.
Companies without developer self-serve face slower time-to-market, talent drain, increased operational overhead, reduced innovation, and scalability challenges.
Implementing developer self-serve offers benefits like boosted productivity, reduced frustration, enhanced compliance, cost-effective scaling, and focus on core competencies.
To implement developer self-serve, evaluate existing solutions, start small, invest in integration, foster a cultural shift, and prioritize continuous improvement.

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