#Continuous-Deployment.

[muellermh]

Wie können Sie Kubernetes-Cluster mit ArgoCD automatisieren?: "Automatisieren Sie Ihr Kubernetes-Cluster mit ArgoCD & MHM Digitale Lösungen UG!"

Automatisierung, Anwendungsentwicklung und Infrastructure-as-Code sind die Schlüssel zu erfolgreichen DevOps-Projekten. Nutze die Möglichkeiten von Continuous Deployment und Continuous Integration, um dein #Kubernetes-Cluster mit #ArgoCD zu automatisieren. Erfahre mehr bei #MHMDigitalSolutionsUG! #DevOps #Anwendungsentwicklung #InfrastructureAsCode

Mithilfe von ArgoCD und MHM Digitale Lösungen UG können Sie Ihr Kubernetes-Cluster einfach und schnell automatisieren. ArgoCD ist ein Open Source Continuous Delivery-Tool, das Änderungen an Kubernetes-Anwendungen automatisiert und in Echtzeit nachverfolgt. Es ermöglicht es Entwicklern, sicherzustellen, dass ihre Änderungen auf der Grundlage von Präferenzen und Richtlinien ausgeliefert werden. MHM…

[hellkitepriest]

i want to hear all your elaborate and niche gambits in the tags here people

[gender-trash]

i gotta go to bed but the ao3 docker container is building............

[koplakever]

I swear I've been trying to tackle this stage for 2 months+

[jarrodcummerata]

Continuous Integration Services New York

Streamline your development process and deliver high-quality software faster with our expert Continuous Integration (CI) services in New York. Our CI pipelines automate testing, building, and deployment, ensuring consistent code quality and reducing errors. Benefit from faster feedback cycles, improved collaboration, and increased productivity. Partner with us to implement efficient CI practices and achieve faster time-to-market.

[faisalakhtar12]

Building Your Serverless Sandbox: A Detailed Guide to Multi-Environment Deployments (or How I Learned to Stop Worrying and Love the Cloud)

Introduction Welcome, intrepid serverless adventurers! In the wild world of cloud computing, creating a robust, multi-environment deployment pipeline is crucial for maintaining code quality and ensuring smooth transitions from development to production.Here is part 1 and part 2 of this series. Feel free to read them before continuing on. This guide will walk you through the process of setting…

[jcmarchi]

The role of MLSecOps in the future of AI and ML

New Post has been published on https://thedigitalinsider.com/the-role-of-mlsecops-in-the-future-of-ai-and-ml/

The role of MLSecOps in the future of AI and ML

Having just spent some time in reviewing and learning further about MLSecOps (Fantastic Course on LinkedIn by Diana Kelley) I wanted to share my thoughts on the rapidly evolving landscape of technology, the integration of Machine Learning (ML) and Artificial Intelligence (AI) has revolutionized numerous industries.

However, this transformative power also comes with significant security challenges that organizations must address. Enter MLSecOps, a holistic approach that combines the principles of Machine Learning, Security, and DevOps to ensure the seamless and secure deployment of AI-powered systems.

The state of MLSecOps today

As organizations continue to harness the power of ML and AI, many are still playing catch-up when it comes to implementing robust security measures. In a recent survey, it was found that only 34% of organizations have a well-defined MLSecOps strategy in place. This gap highlights the pressing need for a more proactive and comprehensive approach to securing AI-driven systems.

Key challenges in existing MLSecOps implementations

1. Lack of visibility and transparency: Many organizations struggle to gain visibility into the inner workings of their ML models, making it difficult to identify and address potential security vulnerabilities.

2. Insufficient monitoring and alerting: Traditional security monitoring and alerting systems are often ill-equipped to detect and respond to the unique risks posed by AI-powered applications.

3. Inadequate testing and validation: Rigorous testing and validation of ML models are crucial to ensuring their security, yet many organizations fall short in this area.

4. Siloed approaches: The integration of ML, security, and DevOps teams is often a significant challenge, leading to suboptimal collaboration and ineffective implementation of MLSecOps.

5. Compromised ML models: If an organization’s ML models are compromised, the consequences can be severe, including data breaches, biased decision-making, and even physical harm.

6. Securing the supply chain: Ensuring the security and integrity of the supply chain that supports the development and deployment of ML models is a critical, yet often overlooked, aspect of MLSecOps.

The imperative for embracing MLSecOps

The importance of MLSecOps cannot be overstated. As AI and ML continue to drive innovation and transformation, the need to secure these technologies has become paramount. Adopting a comprehensive MLSecOps approach offers several key benefits:

1. Enhanced security posture: MLSecOps enables organizations to proactively identify and mitigate security risks inherent in ML-based systems, reducing the likelihood of successful attacks and data breaches.

2. Improved model resilience: By incorporating security testing and validation into the ML model development lifecycle, organizations can ensure the robustness and reliability of their AI-powered applications.

3. Streamlined deployment and maintenance: The integration of DevOps principles in MLSecOps facilitates the continuous monitoring, testing, and deployment of ML models, ensuring they remain secure and up-to-date.

4. Increased regulatory compliance: With growing data privacy and security regulations, a robust MLSecOps strategy can help organizations maintain compliance and avoid costly penalties.

Potential reputational and legal implications

The failure to implement effective MLSecOps can have severe reputational and legal consequences for organizations:

1. Reputational damage: A high-profile security breach or incident involving compromised ML models can severely damage an organization’s reputation, leading to loss of customer trust and market share.

2. Legal and regulatory penalties: Noncompliance with data privacy and security regulations can result in substantial fines and legal liabilities, further compounding the financial impact of security incidents.

3. Liability concerns: If an organization’s AI-powered systems cause harm due to security vulnerabilities, the organization may face legal liabilities and costly lawsuits from affected parties.

Key steps to implementing effective MLSecOps

1. Establish cross-functional collaboration: Foster a culture of collaboration between ML, security, and DevOps teams to ensure a holistic approach to securing AI-powered systems.

2. Implement comprehensive monitoring and alerting: Deploy advanced monitoring and alerting systems that can detect and respond to security threats specific to ML models and AI-driven applications.

3. Integrate security testing into the ML lifecycle: Incorporate security testing, including adversarial attacks and model integrity checks, into the development and deployment of ML models.

4. Leverage automated deployment and remediation: Automate the deployment, testing, and remediation of ML models to ensure they remain secure and up-to-date.

5. Embrace explainable AI: Prioritize the development of interpretable and explainable ML models to enhance visibility and transparency, making it easier to identify and address security vulnerabilities.

6. Stay ahead of emerging threats: Continuously monitor the evolving landscape of AI-related security threats and adapt your MLSecOps strategy accordingly.

7. Implement robust incident response and recovery: Develop and regularly test incident response and recovery plans to ensure organizations can quickly and effectively respond to compromised ML models.

8. Educate and train employees: Provide comprehensive training to all relevant stakeholders, including developers, security personnel, and end-users, to ensure a unified understanding of MLSecOps principles and best practices.

9. Secure the supply chain: Implement robust security measures to ensure the integrity of the supply chain that supports the development and deployment of ML models, including third-party dependencies and data sources.

10. Form violet teams: Establish dedicated “violet teams” (a combination of red and blue teams) to proactively search for and address vulnerabilities in ML-based systems, further strengthening the organization’s security posture.

The future of MLSecOps: Towards a proactive and intelligent approach

As the field of MLSecOps continues to evolve, we can expect to see the emergence of more sophisticated and intelligent security solutions. These may include:

1. Autonomous security systems: AI-powered security systems that can autonomously detect, respond, and remediate security threats in ML-based applications.

2. Federated learning and secure multi-party computation: Techniques that enable secure model training and deployment across distributed environments, enhancing the privacy and security of ML systems.

3. Adversarial machine learning: The development of advanced techniques to harden ML models against adversarial attacks, ensuring their resilience in the face of malicious attempts to compromise their integrity.

4. Continuous security validation: The integration of security validation as a continuous process, with real-time monitoring and feedback loops to ensure the ongoing security of ML models.

By embracing the power of MLSecOps, organizations can navigate the complex and rapidly evolving landscape of AI-powered technologies with confidence, ensuring the security and resilience of their most critical systems, while mitigating the potential reputational and legal risks associated with security breaches.

Have access to hundreds of hours of talks by AI experts OnDemand.

Sign up for our Pro+ membership today.

AI Accelerator Institute Pro+ membership

Unlock the world of AI with the AI Accelerator Institute Pro Membership. Tailored for beginners, this plan offers essential learning resources, expert mentorship, and a vibrant community to help you grow your AI skills and network. Begin your path to AI mastery and innovation now.

[surendra-nareshit]

Master DevOps: Your Complete Guide and Roadmap | DevOps Online Training

Introduction to DevOps

In today's rapidly evolving technological landscape, the need for streamlined and efficient software development practices has never been greater. Enter DevOps—a culture, philosophy, and set of practices that bring development (Dev) and operations (Ops) together to improve collaboration, integration, and automation throughout the software development lifecycle. DevOps is not just a buzzword; it's a transformative approach that enables organizations to deliver high-quality software faster and more reliably. If you're looking to build a career in this field, DevOps Online Training is your gateway to mastering the skills required to excel in this domain.

What is DevOps?

DevOps is a combination of practices, tools, and cultural philosophies designed to increase an organization's ability to deliver applications and services at high velocity. By breaking down the traditional silos between development and operations teams, DevOps fosters a culture of collaboration, where both teams work together throughout the entire software development lifecycle. This collaboration leads to faster development, more frequent deployment of updates, and higher overall software quality.

At its core, DevOps emphasizes automation, continuous integration, continuous delivery (CI/CD), and monitoring. The goal is to minimize manual intervention, reduce errors, and improve the efficiency of software development and deployment. Through DevOps Online Training, you can learn how to implement these practices in real-world scenarios, making you an invaluable asset to any tech organization.

How DevOps Works

DevOps is built on a set of principles and practices that enable organizations to build, test, and deploy software rapidly and efficiently. Here's how DevOps works in practice:

1. Continuous Integration and Continuous Deployment (CI/CD)

Continuous Integration (CI) is the practice of merging code changes frequently, often multiple times a day, into a shared repository. Automated testing is then conducted to identify and resolve issues early in the development process. Continuous Deployment (CD) takes this a step further by automatically deploying code changes to production after passing the CI pipeline. Together, CI/CD reduces the time between writing code and delivering it to customers, ensuring that software updates are released frequently and reliably.

2. Automation

Automation is a critical component of DevOps. From building and testing code to deploying and monitoring applications, automation helps streamline the entire software development lifecycle. By automating repetitive tasks, teams can focus on more strategic activities, such as optimizing code and improving system performance. Automation tools like Jenkins, Ansible, and Puppet are commonly used in DevOps to create efficient, repeatable processes.

3. Infrastructure as Code (IaC)

Infrastructure as Code (IaC) is the practice of managing and provisioning computing infrastructure through machine-readable scripts rather than manual processes. This approach allows teams to automate the setup and configuration of environments, ensuring consistency across development, testing, and production stages. Tools like Terraform and AWS CloudFormation are popular choices for implementing IaC.

4. Monitoring and Logging

Effective monitoring and logging are essential to maintaining the health and performance of applications in a DevOps environment. By continuously monitoring systems and capturing logs, teams can identify and resolve issues before they impact end-users. Tools like Prometheus, Grafana, and ELK Stack are widely used for monitoring and logging in DevOps.

5. Collaboration and Communication

DevOps is as much about culture as it is about technology. A key aspect of DevOps is fostering a culture of collaboration and communication between development, operations, and other stakeholders. This collaboration ensures that everyone is aligned with the project's goals and that issues are addressed quickly. Tools like Slack, Microsoft Teams, and Jira facilitate communication and collaboration in a DevOps environment.

6. Security in DevOps (DevSecOps)

As security becomes increasingly important in software development, DevOps practices have evolved to include security as a core component. DevSecOps integrates security into every stage of the software development lifecycle, ensuring that security vulnerabilities are identified and addressed early in the process. By adopting DevSecOps practices, organizations can build more secure applications without compromising on speed and agility.

The Roadmap to Becoming a DevOps Engineer

Becoming a DevOps engineer requires a combination of technical skills, practical experience, and a deep understanding of DevOps principles. Here's a step-by-step roadmap to guide you on your journey:

1. Understand the Basics of DevOps

Before diving into specific tools and technologies, it's important to understand the fundamental principles of DevOps. Learn about the core concepts of CI/CD, automation, IaC, and monitoring. DevOps Online Training can provide you with a solid foundation in these areas, helping you grasp the essential elements of DevOps.

2. Gain Proficiency in Programming and Scripting

A strong foundation in programming and scripting is essential for a DevOps engineer. Start by learning a programming language like Python, Ruby, or Go, as well as scripting languages like Bash or PowerShell. These skills will enable you to automate tasks, write custom scripts, and work with various DevOps tools.

3. Master Version Control Systems

Version control systems (VCS) like Git are critical to DevOps practices. Learn how to use Git for version control, branching, and merging code. Understand how to collaborate with other developers using GitHub, GitLab, or Bitbucket. Version control is a fundamental skill that every DevOps engineer must possess.

4. Get Hands-On with CI/CD Tools

CI/CD is at the heart of DevOps, so gaining hands-on experience with CI/CD tools is crucial. Learn how to set up and configure Jenkins, CircleCI, or Travis CI to automate the build, test, and deployment processes. DevOps Online Training often includes practical labs and exercises that allow you to practice using these tools in real-world scenarios.

5. Learn About Infrastructure as Code (IaC)

IaC is a key practice in DevOps, enabling teams to manage and provision infrastructure programmatically. Familiarize yourself with IaC tools like Terraform, AWS CloudFormation, and Ansible. Learn how to write scripts that automate the creation and configuration of infrastructure, ensuring consistency across environments.

6. Develop Cloud Computing Skills

Cloud computing is an integral part of DevOps, as it provides the scalability and flexibility needed for modern software development. Gain proficiency in cloud platforms like AWS, Azure, or Google Cloud. Learn how to deploy applications to the cloud, manage cloud resources, and work with cloud-based DevOps tools.

7. Enhance Your Automation Skills

Automation is a cornerstone of DevOps, so it's essential to master automation tools and techniques. Learn how to automate tasks using tools like Jenkins, Puppet, and Chef. Understand how to create automated workflows that integrate with other DevOps tools and processes.

8. Learn About Monitoring and Logging

Effective monitoring and logging are crucial for maintaining the health of applications in a DevOps environment. Familiarize yourself with monitoring tools like Prometheus and Grafana, as well as logging tools like the ELK Stack. Learn how to set up monitoring dashboards, create alerts, and analyze logs to identify and resolve issues.

9. Embrace DevSecOps Practices

Security is a critical aspect of DevOps, and understanding DevSecOps practices is essential for a successful career in this field. Learn how to integrate security into the CI/CD pipeline, conduct security testing, and implement security best practices throughout the software development lifecycle.

10. Gain Practical Experience

Theory alone is not enough to become a proficient DevOps engineer. Hands-on experience is crucial. Work on real-world projects, contribute to open-source DevOps projects, or participate in internships. Practical experience will help you apply the skills you've learned and build a portfolio that showcases your expertise.

11. Obtain DevOps Certifications

Certifications can validate your skills and make you stand out in the job market. Consider obtaining certifications like AWS Certified DevOps Engineer, Google Cloud DevOps Engineer, or Microsoft Certified: Azure DevOps Engineer Expert. These certifications demonstrate your proficiency in DevOps practices and tools.

12. Stay Updated with Industry Trends

The field of DevOps is constantly evolving, with new tools and practices emerging regularly. Stay updated with industry trends by reading blogs, attending conferences, and participating in online communities. DevOps Online Training programs often include updates on the latest trends and tools in the industry.

13. Build a Strong Professional Network

Networking is important in any career, and DevOps is no exception. Join DevOps communities, attend meetups, and connect with other professionals in the field. Building a strong network can lead to job opportunities, collaborations, and valuable insights.

14. Prepare for DevOps Interviews

As you near the end of your learning journey, it's time to prepare for DevOps interviews. Practice common DevOps interview questions, participate in mock interviews, and review your projects and experiences. DevOps Online Training programs often include interview preparation sessions to help you succeed in landing your first DevOps job.

Conclusion

DevOps is a powerful approach that has revolutionized the way software is developed, tested, and deployed. By fostering collaboration between development and operations teams and leveraging automation, CI/CD, and cloud computing, DevOps enables organizations to deliver high-quality software at a rapid pace. Whether you're just starting your career or looking to transition into the field, DevOps Online Training can provide you with the skills and knowledge needed to succeed as a DevOps engineer.

By following the roadmap outlined in this article, you can develop the technical expertise, practical experience, and industry knowledge required to excel in DevOps. Remember to stay updated with the latest trends, build a strong network, and continuously improve your skills.

[intelliatech]

Future Of AI In Software Development

The usage of AI in Software Development has seen a boom in recent years and it will further continue to redefine the IT industry. In this blog post, we’ll be sharing the existing scenario of AI, its impacts and benefits for software engineers, future trends and challenge areas to help you give a bigger picture of the performance of artificial intelligence (AI). This trend has grown to the extent that it has become an important part of the software development process. With the rapid evolvements happening in the software industry, AI is surely going to dominate.

Read More

[starstruckmiraclekitty]

Simon Riley is a sucker for eye contact. Being as his eyes are the only part of his face that he allows to be visible to others, eye contact is incredibly important to him.

But with you, he reads you best when he can see your eyes. He loves to know what you’re thinking, what you’re feeling.

Having an argument with him? You best bet he’s holding your gaze, regardless of what you’re arguing about. If you look away? This man will simply not speak, not utter a single word until you look back at him.

He’ll hold your gaze the entire time he’s fucking you. He’ll force you to keep your eyes open as he pounds into you, wanting to see every bit of pleasure played out in them.

Going down on you? You better hold his gaze. He’ll rip his mouth away so fast and refuse to continue if you let your eyes flutter closed. One of his favorite things in the universe is watching your eyes as come undone.

Going down on him? This man’s fist will be so tightly wound in your hair, pulling your head back ever so slightly so he can see your tear filled eyes, so pretty just for him.

One of his favorite things is when he comes home from deployment, the two of you have a ritual where you will lay in bed together, facing one another as you catch each other up on what you’ve missed. He’ll hold your gaze the entire time, his hand lacing through your hair softly as he hangs onto every word you say.

Simon Riley may not be a man of many words, but with you he’s learned that eyes are windows to the soul. And he’s more than happy to bare his to you.

[muellermh]

Unterschiede zwischen CI und CD: "Verstehen Sie den Unterschied zwischen CI und CD mit MHM Digitale Lösungen UG"

#CIvsCD #ContinuousIntegration #ContinuousDeployment #MHMDigitaleLösungenUG #DigitaleTransformation

Continuous Integration (CI) und Continuous Delivery (CD) bilden zwei grundlegende Aspekte der Softwareentwicklung, die sich nicht nur im Namen unterscheiden, sondern auch in der Funktion. Aber was ist der Unterschied zwischen den beiden Methoden? Mit MHM Digitale Lösungen UG können Sie die Unterschiede leicht verstehen. Continuous Integration bezieht sich auf den Prozess, bei dem Entwickler ihren…

[lostconsultants]

Accelerating Success: The Empowering Force of Continuous Delivery

A few years ago, I was part of a software development team struggling with long, stressful release cycles. Every deployment was fraught with anxiety, and we frequently spent sleepless nights fixing bugs that slipped through rushed testing. The client was frustrated with the delays, and our team morale was plummeting. We knew there had to be a better way allowing us to deploy changes confidently…

[maxlearnmicrolearningplatform]

10 Reasons to Opt for Microlearning for Employee Training

In today's fast-paced business environment, organizations are constantly seeking effective methods to train their employees while minimizing disruption to productivity. Traditional training programs, often lengthy and time-consuming, are increasingly being supplemented or replaced by microlearning. This modern approach delivers training content in small, focused bursts that are easy to digest and apply. Here are ten compelling reasons to opt for microlearning for employee training.

1. Enhanced Retention and Recall

One of the primary benefits of microlearning is its ability to improve retention and recall. Research suggests that breaking down information into smaller, manageable chunks helps learners process and remember content more effectively. Microlearning leverages this by presenting key concepts in bite-sized pieces, often reinforced with interactive elements like quizzes and practice exercises. This method aligns with the brain’s natural learning processes, making it easier for employees to retain and recall information when needed.

2. Flexibility and Convenience

Microlearning offers unparalleled flexibility and convenience, which is crucial for today’s diverse and often remote workforce. Employees can access microlearning modules anytime, anywhere, using various devices such as smartphones, tablets, or computers. This accessibility allows learners to fit training into their schedules, whether it’s during a commute, lunch break, or any other downtime. The convenience of microlearning ensures that employees can engage with training materials without significant disruptions to their workday.

3. Higher Engagement Levels

Keeping employees engaged in training can be challenging, especially with traditional long-form content. Microlearning addresses this issue by delivering content in engaging, interactive formats. Short videos, infographics, and gamified elements capture learners’ attention and maintain their interest. By making training content more appealing and enjoyable, microlearning increases engagement levels, leading to better learning outcomes.

4. Cost-Effectiveness

Implementing microlearning can be more cost-effective compared to traditional training methods. Producing short, focused training modules typically requires fewer resources and less time. Additionally, microlearning reduces the need for extensive classroom training sessions, travel expenses, and printed materials. The scalability of digital microlearning content means it can be easily updated and reused, providing ongoing value without significant additional costs.

5. Rapid Development and Deployment

In the fast-moving business world, organizations need to be agile and responsive to changing training needs. Microlearning allows for rapid development and deployment of training content. Creating short modules focused on specific topics can be done quickly, enabling organizations to address immediate training needs promptly. This agility ensures that employees receive up-to-date information and skills training relevant to their current roles and responsibilities.

6. Personalized Learning Experience

Microlearning supports a personalized learning experience by allowing employees to select modules that are relevant to their individual needs and career goals. This learner-centric approach ensures that employees engage with content that is directly applicable to their roles, enhancing motivation and effectiveness. Personalized learning paths can be created based on job functions, skill levels, or professional development plans, providing a tailored training experience for each employee.

7. Improved Performance and Productivity

By delivering training in a focused and concise manner, microlearning enables employees to quickly apply what they’ve learned to their jobs. This immediate application of knowledge leads to improved performance and productivity. Employees can swiftly close skill gaps and enhance their competencies, contributing to better overall organizational performance. The just-in-time nature of microlearning ensures that employees have access to relevant training precisely when they need it, fostering a culture of continuous improvement.

8. Easier Measurement and Analytics

Measuring the effectiveness of traditional training programs can be challenging. Microlearning, on the other hand, offers easier measurement and analytics. Digital platforms used for microlearning can track various metrics such as module completion rates, quiz scores, and learner feedback. These analytics provide valuable insights into how employees are engaging with the content and the impact of the training on their performance. Organizations can use this data to refine and improve their training strategies continuously.

9. Scalability and Consistency

Microlearning modules can be easily scaled across the organization, ensuring consistent training experiences for all employees, regardless of location. This scalability is particularly beneficial for large organizations with a geographically dispersed workforce. Consistent training content helps maintain uniform standards and practices across the organization, promoting a cohesive corporate culture and ensuring that all employees receive the same quality of training.

10. Adaptability to Various Learning Styles

Employees have diverse learning preferences and styles, and microlearning caters to this diversity. The variety of formats available in microlearning—such as videos, interactive simulations, audio clips, and text-based content—allows learners to engage with the material in a way that suits them best. This adaptability ensures that all employees, regardless of their preferred learning style, can benefit from the training. By accommodating different learning preferences, microlearning enhances the overall effectiveness of employee training programs.

Conclusion

Microlearning represents a powerful approach to employee training, offering numerous advantages over traditional methods. Its ability to enhance retention and recall, provide flexibility and convenience, and maintain high engagement levels makes it an attractive option for modern organizations. The cost-effectiveness, rapid development, and deployment capabilities further underscore its value. Moreover, microlearning’s personalized learning experience, improved performance outcomes, ease of measurement, scalability, and adaptability to various learning styles make it a comprehensive solution for addressing the diverse training needs of today’s workforce.

Incorporating microlearning into your employee training strategy can lead to more effective and efficient training programs, ultimately driving better performance and success for your organization. By embracing the benefits of microlearning, organizations can ensure that their employees are well-equipped with the knowledge and skills needed to thrive in a competitive business environment.

[virtualizationhowto]

Jenkins Docker Compose Install and Configuration

Jenkins Docker Compose Install and Configuration #devops #jenkins #cicd #continuousintegration #continuousdeployment #dockercompose #docker #kubernetes #traefik #ingress #jenkinsagent #jenkinsssh #homelab #homeserver #virtualizationhowto #virtualization

I have been experimenting with many different continuous integration and continuous deployment tools in the home lab. Recently, I have been using GitLab for most of my workflows. However, I have played around with Jenkins in the past and want to get an instance back in the lab environment for comparison with GitLab. In this post, we will look at content around how to install and configure a…