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Kubernetes Gets a New Resource Orchestrator in the Form of Kro

Kubernetes now has a new resource orchestrator called Kro, jointly developed by Amazon Web Services, Google, and Microsoft.
Kro aims to simplify managing workloads on Kubernetes by grouping resources into reusable units, making deployments more efficient.
It introduces the ResourceGraphDefinition (RGD) concept to declare collections of Kubernetes resources and their relationships.
Kro uses the Common Expression Language (CEL) for logical operations and automatically determines the sequence for object creation.
An RGD acts as a DAG for an application, managing dependencies and deployment sequence intelligently.
Applications are created by defining a ResourceGraphDefinition that specifies the structure and resources for the workload.
Kro offers advanced capabilities like automatic dependency management, allowing for easy customization and deployment of Kubernetes resources.
Compared to Helm and Kustomize, Kro provides a more secure runtime with structured YAML and automatic dependency management based on a DAG.
Kro has the potential to become a preferred tool for managing Kubernetes deployments, offering a comprehensive solution for resource orchestration.
With support from AWS, Google Cloud, and Microsoft, Kro aims to make Kubernetes more accessible and efficient in the ecosystem.

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Dev

119

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From Dockerfile to Deployment: A Simple Guide for New Developers

Docker is an open-source platform that enables developers to build, deploy, and run applications inside containers.
Consistent development and production environments, simplified application deployment, enhanced scalability and resource efficiency, and easier collaboration across teams are the benefits of using Docker.
A Dockerfile is a text file that contains a series of instructions Docker uses to build an image.
Containerization with Docker simplifies deployment and enhances scalability, making it a powerful tool for modern developers.

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Alvinashcraft

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Dew Drop – February 21, 2025 (#4367)

The Dew Drop for February 21, 2025 contains a variety of articles covering topics like .NET MAUI, AI, Web Development, Visual Studio, Design, Database, and more.
From .NET MAUI Performance Features to building AI-Powered apps using WinUI Scheduler, the top links feature a range of informative articles.
In Web & Cloud Development, discussions include TypeScript in Node.js, transitioning from Create React App to Vite, and deploying WebJobs to Azure Container Apps.
AI-related articles talk about Doc-Powered AI Assistant, ethical concerns around Generative AI, and AI Agents for beginners.
Design, Methodology & Testing topics cover Developer Experience trends and leveraging GitHub Copilot Workspace Extensions.
The Mobile, IoT & Game Development section touches on Amazon's decision to shut down its Android Appstore and introduces the Raspberry Pi team.
Podcasts featured in the Dew Drop discuss aspects like Engineering Excellence, Azure Security, AI Models, and empathy in engineering management.
Community & Events section highlights software engineering job openings, developer community engagement on content moderation, and the Opengrep launch as a free fork.
Database-related topics include SQL Server Performance, TLS 1.2 for Azure Cosmos DB, and updates on Azure Database for MySQL.
In SharePoint, M365 & MS Teams, articles detail getting started with Copilot and ClipChamp's video creation capabilities.
Miscellaneous news covers insights on DOGE currency, sea level rise due to melting glaciers, and Microsoft's updates like major OCR upgrade for Snipping Tool in Windows 11.

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Hackernoon

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Experimenting With Helm Can Take Your Kubernetes Skills to the Next Level

Helm simplifies Kubernetes application deployment by packaging resources into reusable Helm charts, streamlining complex workloads.
Benefits of using Helm include simplifying deployments, parameterization for dynamic configurations, version control, and dependency management.
Helm consists of the Helm CLI, Helm Charts, Helm Repository, Helm Release, and interacts with the Kubernetes API server directly.
The Helm command lifecycle includes repo management, installation, listing, status check, upgrades, rollbacks, and uninstallation.
Deploying applications with Helm involves installing charts, verifying deployments, customizing releases, upgrading, rolling back, and uninstalling releases.
Key best practices for Helm include organizing values.yaml, using helm dependency for managing dependencies, encrypting sensitive values, and automating deployments with CI/CD.
In production, Helm integrates with GitOps tools like ArgoCD and FluxCD, supports multi-environment management, ensures high availability, and adheres to security best practices.
Monitoring and logging Helm deployments can be achieved with Prometheus, Grafana, and Helm built-in commands for debugging.
Next steps for learning Helm include exploring official documentation, deploying real-world applications, experimenting with custom charts, integrating with CI/CD, and learning advanced features like Helm Hooks and Subcharts.
Overall, Helm is crucial for Kubernetes deployment optimization, providing flexibility, automation, and reliability for scaling efficiently.
Experimenting with Helm can elevate your Kubernetes skills and streamline deployment workflows, making it an essential tool for Kubernetes administrators and DevOps teams.

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Dev

215

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Architecting Fault-Tolerant Cloud Infrastructure on AWS: Key Considerations and Best Practices

Fault tolerance in cloud infrastructure on AWS is crucial for ensuring uninterrupted service and high availability.
Architecting fault-tolerant systems involves redundancy, automation, and distributed architectures on AWS.
Key considerations include designing for redundancy, leveraging managed services, using auto scaling and load balancing, implementing distributed data storage, planning for disaster recovery, monitoring and automating recovery, securing infrastructure, and testing fault tolerance.
Best practices involve following the Well-Architected Framework, using Infrastructure as Code, adopting microservices architecture, implementing circuit breakers, leveraging Spot Instances, and regularly updating and patching systems.
A real-world example of a fault-tolerant e-commerce application on AWS includes using CloudFront, ALB, Amazon ECS or EKS, Amazon Aurora, Amazon S3, AWS Backup, and Route 53.
Architects must focus on redundancy, automation, and proactive monitoring to build resilient, scalable, and cost-efficient systems on AWS.
Continuous testing, refinement, and optimization are essential for maintaining fault tolerance in cloud infrastructure.
It's emphasized that fault tolerance is an ongoing process that requires iterative improvements for ensuring uninterrupted service delivery.

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Dev

439

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AWS CloudTrail Logs : Boost Your Security Now

AWS CloudTrail is a service that enables governance, compliance, and operational and risk auditing of your AWS account.
CloudTrail records all AWS API calls, providing insight into user activity and resource changes.
Key features of AWS CloudTrail include event logging, multi-region and organization trail support, integration with security services, and log storage and retention.
The benefits of using AWS CloudTrail include improved security and compliance, operational monitoring, and cost optimization.

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Dev

178

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Beyond Basics: Building a More Powerful Container in Go — Network Isolation & Advanced Features

The article delves deeper into containerization in Go, exploring network isolation and advanced features beyond basic container systems.
It discusses the core components required for building a more powerful container system, including the User CLI, Container Daemon, Container Runtime, Image Service, Network Manager, and Storage Driver.
Important features like command completion, output formatting, REST/gRPC API, event logging, and resource tracking are highlighted for each core component.
The article emphasizes the challenges faced, especially regarding aspects like OverlayFS and networking, showcasing the complexity involved in creating a functional container runtime tool.
It explains the crucial aspect of network isolation in containerization, detailing the process of creating network namespaces, setting up virtual network interfaces, and ensuring internet connectivity through NAT rules.
Resource cleanup after container stops is highlighted as a key consideration, ensuring proper management and preventing resource leaks.
Common issues in container networking, such as DNS resolution problems, network interface issues, and connection problems, are discussed alongside solutions and debugging tips.
Security considerations like network isolation and resource cleanup are emphasized for enhanced container security.
The article provides code snippets and explanations for setting up network namespaces, virtual network interfaces, NAT rules, and essential devices for container operation.
The importance of signal handling, DNS setup, and cleaning up resources for proper container functioning is highlighted as part of the overall container network implementation.
The article concludes with a note on the ongoing journey to achieve production-ready container runtime systems and offers guidance on testing code with system file images and resolving common bugs.

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Siliconangle

178

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Cloud and AI in 2025: Five trends shaping the future of application development

AI-powered development tools are becoming indispensable, serving as augmentation tools to help developers modernize applications.
Unified DevOps platforms are on the rise, enhancing collaboration and optimizing software delivery lifecycles.
Hybrid operating models that blend cloud, edge, and on-premises computing are becoming the new norm.
DevSecOps is crucial with the integration of automated security tools and embedding security measures across all phases of development.

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Dev

219

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Creating an AKS Automatic cluster with your OWN custom VNET in Bicep

The article demonstrates deploying an AKS Automatic Cluster within a custom virtual network using Bicep.
AKS Automatic simplifies setting up Azure Kubernetes Service with default configurations, covering node management, security, and more.
It utilizes Azure Linux OS, automatic upgrades, Azure RBAC, and workload identity for secure authentication.
AKS Automatic implements Azure CNI overlay networking with Cilium for pod communication and AKS App Routing for ingress.
Auto-scaling features include AKS Node Autoprovisioning, KEDA, and Vertical Pod Autoscaler for efficient resource utilization.
Observability aspects include Managed Prometheus, Container Insights, and Managed Grafana for metrics, logs, and visualization.
Deployment through Infrastructure-as-code may not include all features initially, such as Managed Prometheus and Grafana.
The article guides on creating resources like an AKS cluster, managed identity, and a virtual network with subnets using Bicep.
Network Security Group is set up to restrict traffic between subnets, and a user-assigned managed identity is created for authentication.
Role assignments, including Network Contributor and AKS Cluster Admin roles, are explained to manage permissions.

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Dev

343

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How I Helped a Startup Automate Cloud Infrastructure in Minutes

The author was approached by a Co-Founder to help automate cloud infrastructure creation quickly and easily as part of a workflow.
Infrastructure as Code (IAC) was used, specifically Terraform, to achieve this for AWS and GCP.
The article outlines Terraform scripts for creating AWS EC2 instances, VPC, Subnet, Internet Gateway, Route Table, Security Groups, EBS, and Key pair.
Key elements include configuring the AWS provider, setting up security groups with specific rules, and creating EC2 instances with associated resources.
The Terraform file structure comprises main.tf, outputs.tf, and variables.tf to manage resources efficiently and dynamically.
Variables such as instance count, region, AMI, instance type, and more are defined to customize resource deployment.
The article highlights the creation process of secure EC2 instances with supporting infrastructure components in an automated manner.
Overall, the author successfully assisted the startup in automating cloud infrastructure deployment for AWS using Terraform.
The setup allows for streamlined, repeatable creation of resources essential for the startup's new feature deployment.
The use of Infrastructure as Code tools like Terraform simplifies the process of managing cloud infrastructure with scalability and consistency.

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Dev

210

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Automate File Transfers to Azure Storage with Synology Cloud Sync

Synology Cloud Sync provides a seamless way to sync files automatically to Azure Storage.
No custom API required – Simple GUI-based setup.
Automated scheduling – No need for additional cron jobs or scripts.
One-way sync from local to cloud – Files remain on Azure even if deleted locally.

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Dev

123

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Grafana Architecture Explained: How the Backend and Data Flow Work.

Grafana is a powerful open-source tool for creating interactive dashboards from raw data, popular among DevOps teams.
The backend of Grafana handles data processing, query execution, and connection to various data sources like Prometheus and InfluxDB.
The Grafana server acts as a bridge between dashboards and data sources, managing requests and enabling automation through its API.
Data queries in Grafana involve the frontend sending requests to the backend, which retrieves and processes data before rendering visualizations.
Grafana seamlessly connects to different data sources such as Prometheus, InfluxDB, and Elasticsearch for monitoring and analysis.
Setting up a data source in Grafana involves selecting, configuring, and authenticating the connection before testing and saving it.
Every user interaction with a Grafana dashboard initiates a well-coordinated data flow process involving query processing, data retrieval, and visualization.
The data flow in Grafana ensures that users receive current and accurate visualizations of the data being processed in real-time.
Grafana simplifies the data visualization process by efficiently handling query translation, data cleaning, and formatting tasks.
Grafana's backend expertise in managing data requests and processing contributes to its effectiveness as a real-time monitoring and analysis tool.

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Solarwinds

304

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What Nature Can Teach Us About Alert Fatigue

Alert fatigue is a prevalent issue in IT environments, caused by excessive and irrelevant notifications leading to slower responses and increased stress.
Factors contributing to alert fatigue include poorly configured monitoring tools, lack of prioritization, complex environments, and inadequate filtering.
To combat alert fatigue, insights from nature can be applied to prioritize essential signals and reduce unnecessary noise.
Lessons from natural systems suggest using anomaly-based alerting, predictive and proactive strategies, contextual alerts, and intelligent escalation.
Customizable and multi-channel notifications, as well as automated remediation processes, can help streamline alert management and reduce human intervention.
Success in combating alert fatigue can be measured by metrics like reduced mean time to resolution, fewer ignored alerts, and increased team satisfaction.
Integrating cues from natural systems into alert management strategies can improve observability and focus on critical issues in IT environments.
Observability platforms should aim to be intelligent, predictive, automated, and context-aware to optimize alert management.
By prioritizing signals effectively, organizations can enhance their observability strategies and address the challenges of alert fatigue in IT operations.
The use of intelligent alerting strategies inspired by nature can lead to more efficient response mechanisms and reduced alert fatigue in IT teams.
Stay tuned for the upcoming articles in the blog series for more insights on improving observability and overcoming common obstacles in IT environments.

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Dev

105

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My Love-Hate Relationship with Helm

Helm is a popular Kubernetes package manager that simplifies grouping Kubernetes resources into units for easy deployment.
Helm charts define all the resources needed to run applications like Grafana or MySQL in a Kubernetes cluster.
Challenges with Helm include complex YAML configuration, potential for configuration overrides, and manual resource tracking.
Cyclops, an open-source framework, addresses Helm issues by offering a UI for Helm charts and using Modules for configuration persistence.
Cyclops allows for the migration of existing Helm releases to Modules without disrupting deployments.
To install Cyclops, users can follow simple commands and access the UI to manage Helm releases more efficiently.
Migrating Helm releases to Cyclops Modules involves referencing the Helm chart, tweaking configurations, and deploying without impacting existing resources.
Cyclops provides centralized configuration management, resource visibility, and avoids conflicts when multiple users are working on deployments.
Future plans for Cyclops include extending support beyond Helm to accommodate various configuration languages like Kustomize, KPT, or Cue.
Users can join the Cyclops Discord server for updates and engage with the team for any queries or feedback.

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Solarwinds

293

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5 Things We Learned from the Latest Public Sector Cybersecurity Report

The most significant security threats in the public sector come from the general hacking community and careless insiders, highlighting the need for stronger security awareness training.
Most organizations are still in the early or middle stages of their digital transformation journey, facing challenges such as data privacy, security concerns, and integrating new systems.
Hybrid IT environments are difficult to manage, with data protection and privacy being top concerns, leading to a lack of visibility and standardization.
Observability tools are crucial for security and digital transformation, but their adoption faces challenges related to security and privacy concerns.
AI adoption is on the rise in the public sector, with concerns around data privacy and compliance, requiring careful consideration and management.

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