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How to Build Comprehensive Dashboards for Your SaaS and Cloud Apps

Creating comprehensive dashboards for SaaS/Cloud apps is crucial for troubleshooting and visibility of system components.
Architecture diagrams provide a high-level view, but detailed information is essential for deployment and troubleshooting.
MechCloud dashboards use AWS and System Info UI components to collect data from AWS, Cloudflare, Kubernetes, and Docker via REST APIs.
Exemplifying an app on self-managed Kubernetes on AWS Lightsail connected via Cloudflare tunnels, with Docker serving cloudflared on Lightsail VM.
Dashboard setup involves creating cards for Cloudflare, Docker, Kubernetes, and AWS Lightsail to display relevant system data.
Processes include creating teams, frames, sites, and pages using MechCloud page designer.
Utilizing CSS Grid with MechCloud AWS and System Info components, setting grid area labels for each card for layout.
Configuring Cloudflare, Docker, Kubernetes, and AWS system accounts with appropriate details in the MechCloud console.
Customizing System Info components for Cloudflare, Kubernetes, Docker, and AWS Info with prompts to fetch specific data.
A well-designed dashboard enhances visibility, collaboration, and operational efficiency for SaaS and Cloud applications.

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Devopsonline

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Critical skills for tomorrow’s workforce

AI foundational skills across all roles and departments are important to effectively integrate AI technologies into operations.
Quantum mechanics, algorithms, and programming principles are crucial skills for organisations to pioneer advancements in quantum innovation.
Soft skills development is essential for technical staff to effectively communicate, negotiate, and represent their team.
Implementing continuous learning 'in the flow of work' enables access to relevant learning materials in real-time and improves employee engagement and productivity.

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Dev

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Scaling Globally? Here's Why IP Geolocation API Should Be in Your Stack

When building applications for a global audience, understanding user locations is crucial for content customization, fraud prevention, and compliance.
Integrating IP-based location data tools like IP geolocation APIs enables personalized experiences at scale.
These tools allow for real-time detection of user locations, enhancing features like localized content delivery and security measures.
IP geolocation APIs are essential for serving hundreds of thousands of location-based decisions daily when scaling globally.
Consider factors like low latency, uptime, global coverage, API call limits, and advanced features when choosing a service.
Look for providers with flexible pricing, generous free limits, and scalable options to meet growing demands.
Premium features to consider include city-level geolocation, ISP info, timezone detection, and proxy/vpn detection.
Responsive customer support, easy integration, SDK availability, and real-time/batch processing capabilities are important criteria.
IP-based geolocation data is accurate to the city level in most countries and complies with privacy laws like GDPR or CCPA.
Choose a provider that offers burst tolerance and quick plan scaling to handle API rate limits during traffic spikes.
Integrating IP geolocation APIs early on saves from scalability issues later and enhances user experience globally.

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Towards Data Science

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AWS: Deploying a FastAPI App on EC2 in Minutes

AWS is a popular cloud provider for deploying and scaling applications, essential for software engineers and data scientists.
This tutorial guides deploying a FastAPI application on AWS EC2, applicable to other application types.
Considers core EC2 networking concepts, but excludes best practices for AWS usage.
Steps include instance creation, SSH connection setup, and environment configuration.
Demo uses t3.nano instance type, SSH authentication, and Nginx setup to redirect traffic.
Package installation instructions, FastAPI server launch, and Nginx restart are covered.
Exercise section details creating a FastAPI example repository with main.py and requirements.txt.
Instructions to handle file upload issues in Nginx by adjusting client_max_body_size are provided.
Article concludes by summarizing the process of deploying a FastAPI server on AWS EC2 for beginners.
Next steps suggested include creating multiple EC2 instances and connecting them for further learning.

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Dev

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If You Run Your CI Locally, You’ve Already Failed

Testing GitHub workflow files is painful, so ACT allows running GitHub Actions locally.
However, running CI locally instead of pushing it to the repo undermines the purpose of CI.
Continuous Integration (CI) serves as a gate and referee to block code that shouldn't pass, rather than for testing code until it works.
CI failures are not annoyances but rather bugs, indicating deeper issues with the process, not the code.

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Dev

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Deploying Dapr with Kubernetes

This guide walks you through deploying Dapr on Kubernetes using the Hello Kubernetes quickstart.
Prerequisites: Docker, kubectl, Dapr CLI, and a Kubernetes cluster (Minikube, Docker Desktop, AKS, etc.).
Step 1: Clone the Repository: git clone https://github.com/dapr/quickstarts.git
Step 2: Initialize Dapr on Kubernetes: dapr init -k --dev
Step 3: Deploy the Sample Applications: kubectl apply -f deploy/

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The New Stack

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Kubernetes v1.33 Advances in AI, Security and the Enterprise

The latest release of Kubernetes, v1.33, brings advancements in AI workloads, security, and enterprise use, featuring 64 enhancements.
Key updates include support for sidecar containers and in-place resource resizing for pods, alongside dynamic resource allocation and user namespaces.
121 companies and 570 individuals contributed to Kubernetes v1.33 during the release cycle.
The release introduces Sidecar Containers for handling networking, logging, and metrics gathering, streamlining the management of multi-container applications.
Dynamic Resource Allocation (DRA) API in Beta allows for allocating non-CPU resources like GPUs, TPUs, and FPGAs, crucial for AI workloads.
User namespaces are enabled by default for Linux pods in this release, enhancing security and resource isolation in Kubernetes.
Kubernetes v1.33 aims to make clusters more secure, scalable, and easier to manage, with improvements highlighted by technical experts.
The update is installable via kubeadm and is available for download on GitHub, offering enhanced features for Kubernetes users.
For full details and changes, users can refer to the release notes or attend the web presentation by the Release Team.

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Siliconangle

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Three insights you may have missed from theCUBE’s coverage of KubeCon + CloudNativeCon Europe

Cloud-native observability is emerging as a key lever in managing multicloud ecosystems, addressing complexity and skill gaps.
Observability tools help unify platforms, simplify operations, and adapt to AI-driven environments for real-time diagnostic support.
Cloud-native observability expands into compliance monitoring, security, and decision-making to enhance performance.
Platform engineering matures with challenges like DevSecOps adoption, platform sprawl, and managing upgrades at scale.
Kubernetes evolves to involve a broader range of creators and integrates with AI development, offering more intuitive experiences.
AI at scale transitions towards more cost-effective and domain-specific models, utilizing Kubernetes as the underlying infrastructure.
Cloud-native observability becomes crucial for understanding smaller AI models and building trust for production deployment.
Development tools are becoming more iterative and inspiring, prioritizing creativity over configuration.
The CNCF promotes open collaboration to help cloud-native AI transition from theory to production, fostering stronger partner ecosystems.
The article highlights key insights from theCUBE's coverage of KubeCon + CloudNativeCon Europe, emphasizing the evolving landscape of cloud-native technologies.

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Kubernetes

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Continuing the transition from Endpoints to EndpointSlices

Since the introduction of EndpointSlices, the Endpoints API in Kubernetes has become obsolete for new features.
As of Kubernetes 1.33, the Endpoints API is officially deprecated, and users are encouraged to switch to EndpointSlices.
The plan is to change Kubernetes Conformance criteria to eliminate the need for running the Endpoints controller in modern clusters.
Users with workloads or scripts still using the Endpoints API should start migrating to EndpointSlices.
EndpointSlice API allows Services to have multiple EndpointSlices associated with them, supporting features like dual-stack networking.
EndpointSlices are used to represent endpoints of a single IP family, handle changes in port configurations, and manage a large number of endpoints efficiently.
When fetching EndpointSlices, users should use labels to associate them with the corresponding Service rather than by name.
Migrating to EndpointSlices involves updating code to fetch and process EndpointSlices instead of Endpoints.
For generating EndpointSlices, a new YAML format is required, including explicit address types and conditions for each endpoint.
EndpointSlices offer new features like topology hints and terminating endpoints, enhancing functionality beyond the Endpoints API.

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Medium

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✅ Day 3 Topic: Mastering Windows Event Viewer for DevOps & SRE

Event Viewer is a valuable tool for DevOps and SRE professionals to troubleshoot issues on Windows systems.
It logs everything, including successes, failures, warnings, and audits.
Users can navigate different categories within Event Viewer, such as Windows Logs, to identify specific issues.
Creating custom views and exporting logs are useful features for recurring scenarios.

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Medium

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Mastering Terraform: 5 Essential Commands for AWS Cloud Provisioning

Terraform is an Infrastructure as Code (IaC) tool developed by HashiCorp.
It allows you to automate the creation, management, and versioning of cloud infrastructure.
The top 5 essential Terraform commands for AWS cloud provisioning are: terraform init, terraform plan, terraform apply, terraform destroy, and terraform fmt.
Using Terraform, AWS cloud engineers or DevOps students can automate and scale infrastructure at a professional level.

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Dev

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Setting Up My Linux Lab with RHEL 9 (30-Day RHCSA Journey)

Day 1 of the RHCSA + Ansible Fast Track Training with the CloudWhistler Community focused on setting up the lab environment.
The tasks included installing VirtualBox, downloading the RHEL 9 ISO, creating a VM, and exploring the Linux CLI.
Some common troubleshooting issues during installation were addressed, such as VirtualBox not detecting the RHEL ISO and VM crashes.
Setting up the lab provides valuable learning opportunities on topics like resource allocation and troubleshooting errors.

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Medium

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Terraform : Guide to create AWS EC2 and S3 setup using IAC

This blog provides a guide on using Terraform to create an AWS EC2 instance and S3 bucket.
Terraform is an open-source tool that allows infrastructure provisioning using a high-level configuration language called HCL.
It acts as a bridge between code and the cloud, ensuring consistency across environments.
The guide covers the necessary steps to define resources, create, update, destroy, and shows the benefits of Infrastructure as Code.

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Dev

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Building a Secret Scanner in Julia: A GitLeaks Alternative

A new tool called Julia aims to provide an alternative to GitLeaks for scanning secrets, passwords, and API key leaks.
Julia offers more advanced features like specifying custom regex pattern lists, producing proper JSON output for automation, and backend use.
The tool also allows scanning directories, GitHub repositories directly, and loading custom patterns from a YAML file.
The project structure includes the use of Docker, Julia, and nfpm for creating DEB and RPM packages.
A Makefile is used for handling Docker builds, Docker container operations, pushing images to Docker Hub, and creating GitHub releases.
GitHub CLI is utilized for tagging repositories, uploading releases, and creating GitHub releases with version numbers like v1.0.0.
Testing is done by running the script in a Docker container against a test repository that contains secret leaks.
A GitHub pipeline is set up for automated CI/CD workflows using Docker, Make, GitHub Actions, and Makefile commands.
Julia, Docker, and GitHub tools simplify the process of building, testing, packaging, and deploying projects, making it suitable for everyday tasks.

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Ubuntu

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The hitchhiker’s guide to infrastructure modernization

The article discusses the importance of infrastructure modernization and the key takeaways from the Infra Masters 2025 event held by Canonical.
One key lesson is to reconsider vendor relationships to speed up innovation, as demonstrated by BT shifting from vendor-consumer to partnership with Canonical.
ESA plans to double missions by 2030 and has leveraged Canonical Kubernetes for automating deployment and freeing up resources for critical tasks.
Open source software plays a crucial role in modernizing infrastructure, offering flexibility, scalability, and cost-effectiveness.
BT's Network Cloud project utilized open source solutions like MAAS, Ceph, LXD, and Juju to streamline operations and focus on application development.
The future of infrastructure lies in edge computing, containerized applications, serverless computing, and Kubernetes management.
ESA's plan to scale satellites relies on Kubernetes and cloud-native computing for managing workloads effectively.
Canonical's infrastructure portfolio automations improve efficiency and reduce costs, benefiting organizations without capacity or skill shortages.
Choosing managed solutions for infrastructure can ease migration efforts and free up in-house engineers.
Overall, the event highlighted the importance of collaboration, open source adoption, and managed solutions for successful infrastructure modernization.
Canonical's software, such as Ubuntu, offers trusted open source options for organizations looking to optimize infrastructure and lower costs.

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