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Kubernetes Delivers Scalable Analytics in Hybrid Clouds

The demand for scalable analytics solutions in hybrid clouds is increasing due to data security and cost optimization needs.
Businesses utilize hybrid cloud deployments to balance workloads and ensure data security and cost-effectiveness.
Kubernetes provides elasticity and resilience, crucial for modern IT environments in the cloud or on-prem.
Hybrid clouds allow agile scaling for shifting workloads and optimizing performance for varying demands.
Melco improved analytics with Yellowbrick's hybrid cloud, enhancing customer insights and marketing actions.
Hybrid cloud solutions enable gradual modernization and integration with existing systems for cost efficiency.
Private clouds with Kubernetes offer security and scalability benefits for sensitive data processing.
Businesses integrate AI with Kubernetes-enabled private clouds to unlock AI capabilities securely and efficiently.
Cloud cost concerns drive workload repatriation to private clouds for cost control and performance optimization.
Legacy modernization is essential for businesses to overcome challenges in scalability and integration with hybrid cloud strategies.

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Dev

126

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Transition to a Robust Infrastructure - Terraform and ArgoCD in Action

The article discusses transitioning to a robust infrastructure using Terraform and ArgoCD for managing infrastructure and continuous service deployment.
It explains the challenges faced and solutions implemented to improve Kubernetes deployment processes.
Key topics include leveraging Terraform for one-shot operations and ArgoCD for continuous deployments.
Issues covered include error handling in Terraform, proper chart updates, IP address persistence, and log persistence during cluster recreations.
It details how Terraform is used for cloud infrastructure creation and ArgoCD for Helm chart deployments.
The article delves into persisting IP addresses, ensuring logs persistence, and maintenance without cluster recreations.
It also touches on automated Helm chart updates using Renovate in conjunction with GitLab.

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Dev

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AI-Augmented Change Management: Reinventing ITSM Resilience in 2025

In 2025, change acceleration challenges traditional ITIL-based governance models, leading to the adoption of AI-Augmented Change Management for resilience.
Issues with manual risk assessments, CABs, siloed systems, and limited visibility prompt the transition to smarter change approaches.
AI-Augmented Change Management combines ML, NLP, and GenAI to predict impacts, automate changes, generate communication plans, and learn from past rollouts.
Key capabilities include predictive risk scoring, automated change categorization, GenAI for artifacts, dependency visualization, and smart approvals.
Real-world use cases showcase faster seasonal rollouts, smoother healthcare system upgrades, and safe continuous deployments in a SaaS company.
ServiceNow, integrated with AI capabilities, serves as the foundation for AI-Enabled Change, enabling structured change management and AI-driven impact prediction.
Business benefits include improved change success rates, reduced time-to-change, stronger governance, boosted operational efficiency, and resilience through intelligence.
MJB Technologies offers expertise in AI Risk Framework Design, GenAI Integration, CAB Workflow Optimization, CI/CD Pipeline Alignment, and User Training & Governance Coaching.
AI-Augmented Change Management helps enterprises accelerate innovation while maintaining control, making change a competitive advantage in the digital landscape.
The article is eligible for web story generation as it provides insights on adopting AI for ITSM resilience and includes real-world use cases and business benefits.

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Dev

275

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🚀 Why Linux is the Backbone of DevOps

Linux is the backbone of DevOps due to its stability, security, and automation capabilities.
The Linux kernel is mature, well-maintained, and known for its stability and performance.
Most cloud servers run on Linux, and DevOps tools like Docker, Kubernetes, Jenkins, and Ansible are designed for Linux.
Learning Linux commands, file permissions, users & groups, package managers, and shell scripting is crucial for DevOps success.
DevOps areas like CI/CD pipelines, containers, IaC tools, monitoring, and cloud deployments heavily rely on Linux.
Mastering Linux is essential for automating deployments, troubleshooting servers, and scaling in the cloud.

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Dev

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Introduction: The Evolution of AI to Agentic AI

Agentic AI signifies a notable advancement in AI, offering autonomous decision-making capabilities and adaptive behavior.
It operates independently, learns from its environment, and continuously optimizes actions to achieve set goals.
Agentic AI evolves from traditional rule-based AI to autonomous task performance systems.
Key features include goal-oriented decision-making, real-time adaptation, learning capabilities, and autonomy.
The architecture of Agentic AI comprises sensor/perception, cognitive processing, action/execution, and feedback/learning layers.
Applications of Agentic AI range from autonomous vehicles and business automation to healthcare and smart cities.
Challenges include accountability, bias, security risks, and societal impact due to potential job displacement.
Despite challenges, Agentic AI has the potential to revolutionize industries by enhancing efficiency and providing personalized solutions.
Ethical considerations include accountability, fairness, security risks, and societal impact.
The future of Agentic AI depends on addressing ethical and regulatory concerns while ensuring transparent and secure AI systems.

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Medium

11h

111

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Understanding Software Engineering Before Applying AI

AI is not just for speeding up coding and testing; it can assist in all software development stages.
Misunderstandings arise when AI is viewed as just a tool for writing code faster.
Software engineering encompasses various stages like requirement analysis, design, coding, testing, deployment, and maintenance.
Companies should invest in research, improve AI skills, and align AI with business objectives for innovation and value creation.
Software engineering addresses the software crisis by introducing structured, rule-based approaches for predictable development.
AI tools can lead to issues if used without a comprehensive understanding of software engineering.
Neglecting system design and code review while relying heavily on AI can escalate technical debt in software projects.
Developers must take responsibility for AI-generated code and ensure thorough testing to prevent hidden bugs.
Adopting AI in software development requires a well-defined process, supportive tools, and gradual integration to various tasks.
As AI evolves, companies must adapt their software development methods and prioritize training their workforce to utilize AI effectively.

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Dev

16h

278

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Nixopus: Simplifying VPS Management

The article reflects on the author's journey from using free tier clouds to discovering VPS for hosting private apps and learning about managing a VPS server.
Initial experiences with platform-specific hosting services like Heroku, Firebase, Render, and Netlify made deployment easy and quick.
Challenges arose when needing to host private apps with specific requirements like ports, memory tuning, etc., leading to the recommendation of using VPS for more control and flexibility.
VPS (Virtual Private Server) is likened to having your own apartment, offering secure, customizable space at a moderate cost.
The author purchased a VPS server, learned about its components, and transitioned apps to the VPS.
Setting up a domain name and configuring DNS for the VPS was crucial for accessibility.
Nginx and SSL were explained as important for traffic handling and securing web communication.
The author shared the challenges faced in manual deployments and the need for a standardized tool for VPS management, leading to the discovery of Nixopus.
Nixopus, still in Alpha stage, offers streamlined VPS management and potential for simplifying deployment processes.
The author recommended Nixopus and invited readers to explore and contribute to the project.
The article concludes with a note on transitioning to VPS for better control and management, emphasizing the importance of tools like Nixopus for efficient VPS operations.

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Dev

18h

350

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Part2: Kubernetes Backup on Managed Services: What Changes When You Use EKS?

When using managed Kubernetes services like Amazon EKS, the backup strategy shifts to focus on Kubernetes objects, persistent data, and application configurations.
Managed services like Amazon EKS handle the control plane, including etcd, making traditional etcd snapshots unfeasible.
For backing up on EKS, focus on Kubernetes objects, persistent volumes, networking, security, and application data.
Velero is recommended for Kubernetes object backup on EKS, supporting scheduling, retention policies, and integration with AWS S3.
Use Velero for backing up persistent data, including EBS volumes, and automate backups with regular testing for validity.
Security measures such as encryption, immutable backups, multi-region storage, and access controls are crucial for backup on EKS.
Consider cost-saving strategies like storage tiering, incremental backups, and retention policies for managing backup costs.
The control plane/etcd and node-level state are typically inaccessible for direct backup on managed services like EKS.
Best practices include using Velero for disaster recovery, automation for cost control, encryption for security, regular testing, and multi-region backups.
Follow additional resources for backup and restore guidelines specific to Amazon EKS.
Overall, leveraging tools like Velero and AWS storage features on EKS ensures a robust, cost-effective, and secure backup approach.

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Dev

19h

211

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The Role of AI and Compliance in Modern Risk Management: ShowMeCon 2025

ShowMeCon 2025, held in St. Charles, focused on security, compliance, and risk management discussions.
Key themes included the importance of context, rigor, and adaptive posture in real security practices.
Jeff Man highlighted the evolution of PCI compliance, emphasizing the need for continuous security operations beyond mere compliance.
Dan Yarger discussed the role of AI in policy creation, emphasizing human oversight and validation.
Tim Malcolm-Vetter emphasized the importance of fundamentals over flashy AI models in cybersecurity defense.
The event underscored the message that compliance should serve as a foundation for security, with continuous, adaptive measures built around it.
Practitioners were urged to focus on operationalizing controls, identity threat detection, and the dual nature of AI as both a partner and a threat.
The sessions stressed the need for teamwork, continuous enforcement, and merging policy with security practices for operational resilience.
A forward-thinking approach involves viewing compliance as a scaffold rather than a fortress, aiming for real-time security readiness and response.
The call to action is to shift focus from mere compliance to ensuring current security effectiveness and readiness.

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Dev

20h

122

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Docker containers vs. Virtual machines: What's the difference?

Docker containers and virtual machines offer isolated environments for running applications, with each having distinct advantages and drawbacks.
Virtual machines act like mini-computers, separate from the main system, while Docker containers share the host OS, providing lightweight isolation.
VMs offer full security and support for various OSes, but consume more resources and are slower to manage than Docker containers.
Docker containers are efficient, easy to scale, and promote consistency, but may pose security risks if not configured correctly.
VMs are best for scenarios needing diverse OSes and stringent security, whereas Docker containers excel in portability, scalability, and DevOps practices.
Use cases for Docker include development, cloud deployment, and microservices, while VMs are suitable for legacy software, security-focused tasks, and emulation.
Choosing between Docker containers and virtual machines depends on factors like resource usage, security needs, scalability, and management preferences.
Overall, both technologies have strengths that cater to specific requirements, and the decision should be based on individual project needs.
The comparison highlights resource usage, security, portability, scalability, and management differences between VMs and Docker containers.

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Dev

21h

163

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💻 OCI Journey – Part 3: Compute Services in Oracle Cloud Infrastructure

Oracle Cloud Infrastructure (OCI) Compute Services provide a range of virtual machines, bare metal servers, and dedicated hosts.
Key concepts in OCI Compute include Virtual Machines, Bare Metal Instances, and Dedicated Hosts.
Factors to consider in OCI Compute are scalability, performance requirements, cost-efficiency, and image & shape selection.
OCI offers flexible shapes allowing dynamic definition of compute resources like OCPUs and Memory.
OCI is the only cloud provider offering AMD-based, Intel-based, and Ampere ARM-based CPUs.
OCI's pricing model is pay-as-you-go and claims to be 50% cheaper than other providers; features Preemptible VMs for cost savings.
OCI supports live migration of VMs across hosts during hardware maintenance without downtime.
To launch an instance in OCI, create a VCN and subnet, launch a VM, assign it to a subnet, and optionally assign a Public IP.
Scaling in OCI can be done vertically by increasing OCPUs or memory, involving some downtime, or horizontally by adding/removing instances for better resilience.
OCI offers Oracle Kubernetes Engine (OKE) for managed Kubernetes service with options for different cluster and node types.
OCI Container Instances allow running containers serverlessly, ideal for short-running apps and microservices.
Serverless Compute with Oracle Functions is based on a Function-as-a-Service model integrated with OCI events and services.
OCI Compute provides flexibility and cost-efficiency for various workloads, offering VMs, Bare Metal, or Dedicated Hosts, flexible shapes, Kubernetes, Container Instances, and Oracle Functions.
The article is eligible for web story generation.

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Dev

21h

353

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Relax About Your DORA Metrics

Investing too much in precision for software delivery metrics is wasteful, focus on responding to data.
Precision isn't crucial for DORA metrics; focus on performance improvement milestones.
Marginal gains are beneficial for elite sports but not necessary for monthly deployments.
Compare and track software delivery performance over time for improvement purposes.
Define metrics collaboratively with your team; choose what's most beneficial for improvement.
Software delivery metrics should inform continuous improvement processes.
Focus on wider system improvements beyond just software delivery.
DORA metrics serve to improve software delivery, not for unhealthy team comparisons.
High-performance levels require a broader view for improvement efforts.
No formal metrics solution needed to start using DORA's four keys.
Teams should vary measurement methods for what's useful in their improvement process.

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Openstack

22h

126

Image Credit: Openstack

Part One: Getting Started with Standalone OpenStack Ironic

The article focuses on demystifying private cloud infrastructures and bare metal lifecycle management using OpenStack Ironic in "standalone" mode.
OpenStack Ironic integrates physical servers into the OpenStack framework, treating them as cloud resources, allowing for API-based lifecycle management.
The bare metal server lifecycle is transformed with Ironic, covering processes like discovery, provisioning, remote management, and decommissioning.
Ironic manages physical hardware directly, installing the OS without virtualization layers, simplifying management tasks.
The article details setting up a minimal OpenStack Ironic environment, including server installation, Podman setup, creating a Python Virtual Environment, and deploying OpenStack.
Configuration steps for Ironic standalone mode, defining hardware types, interfaces, and setting up various components like conductor and API are outlined.
Post-setup checks, testing the service, querying the API, and using OpenStack client commands for management tasks are demonstrated.
The article concludes by hinting at a follow-up post continuing the Ironic journey on Superuser.

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Dev

22h

265

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Linux Insight Blogs: lsof

lsof is a command-line utility on Unix/Linux systems that stands for 'list open files' and shows which files are open by processes, users, port, or specific process.
Linux treats everything as a file, making it crucial to know how to list specific files with lsof.
lsof commands can be used to check open files, processes using specific files, files using a given port, files opened by a particular process, open network connections, etc.
Using lsof, you can list all open files, processes, network connections, and even the current working directory of a process.
The lsof command can be combined with various options to filter results, such as -i, -p, -c, -n, etc.
You can also examine the largest open files on your system by using lsof in conjunction with other commands like awk and sort.
By utilizing lsof, you can inspect open files, network ports, and running processes effectively.
Exploring and experimenting with lsof commands can provide insights into your system's activities and processes.
The lsof command is a helpful tool for system administrators and users to monitor and manage open files and processes.

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Dev

22h

216

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Interactive Cloud Infrastructure Scheme | Hostman

Hostman introduces a new feature, the Cloud Infrastructure Scheme, providing a synchronized, interactive map of users' infrastructure at no extra cost.
Users can view all project services, navigate quickly, organize visually, and access live data and alerts for each element displayed on the map.
The infrastructure scheme is built with React Flow with custom improvements, ensuring data freshness, efficient editing, and safe loading processes.
It offers users instant insight into their infrastructure setup, making it interactive, clean, and reliable without manual diagram management.
Future plans for the scheme include the ability to create drafts, introduce new element types, and customizable display modes to enhance management capabilities.
Users can access the infrastructure scheme feature by logging into Hostman, navigating to the project, and selecting the Infrastructure scheme tab to generate their infrastructure map.

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