#Kubernetes Skill Tree

[labexio]

Understanding the Basics and Key Concepts of Kubernetes

Kubernetes has emerged as a powerful tool for managing containerized applications, providing a robust framework for deploying, scaling, and orchestrating containers. Whether you're a developer, system administrator, or DevOps engineer, understanding the fundamentals of Kubernetes is crucial for leveraging its full potential. This article will walk you through the basics of Kubernetes, key concepts, and how resources like Kubernetes Integration, Kubernetes Playgrounds, and Kubernetes Exercises can help solidify your understanding.

What is Kubernetes?

Kubernetes, often abbreviated as K8s, is an open-source container orchestration platform developed by Google. It automates the deployment, scaling, and management of containerized applications, allowing for a more efficient and reliable way to handle complex applications across clusters of machines. Kubernetes abstracts the underlying infrastructure, enabling developers to focus on building and deploying applications rather than managing the hardware.

Key Concepts in Kubernetes

Cluster: At the core of Kubernetes is the cluster, which is a set of nodes (physical or virtual machines) that run containerized applications. The cluster includes a control plane and one or more worker nodes.

Control Plane: The control plane manages the Kubernetes cluster, making decisions about the cluster’s state and coordinating activities such as scheduling and scaling. Key components include:

API Server: The entry point for all API requests, handling CRUD operations on Kubernetes objects.

Controller Manager: Ensures the cluster's desired state is maintained by managing controllers that handle various operational tasks.

Scheduler: Assigns tasks (pods) to nodes based on resource availability and requirements.

etcd: A distributed key-value store that holds the cluster’s state and configuration data.

Nodes: Nodes are the machines in a Kubernetes cluster where containerized applications run. Each node runs a container runtime (like Docker), a kubelet (agent that communicates with the control plane), and a kube-proxy (handles network routing).

Pods: The smallest deployable unit in Kubernetes, a pod encapsulates one or more containers, along with storage resources, network configurations, and other settings. Pods ensure that containers within them run in a shared context and can communicate with each other.

Services: Services provide a stable endpoint to access a set of pods, enabling load balancing and service discovery. They abstract the underlying pods, making it easier to manage dynamic workloads.

Deployments: A deployment manages a set of pods and ensures that the desired number of pod replicas is running. It also handles rolling updates and rollbacks, providing a seamless way to manage application versions.

Namespaces: Namespaces are used to organize and isolate resources within a cluster. They allow for the separation of different environments or applications within the same cluster.

Enhancing Your Kubernetes Knowledge

To get hands-on experience with Kubernetes and deepen your understanding, consider exploring resources like Kubernetes Integration, Kubernetes Playground, and Kubernetes Exercises:

Kubernetes Integration: This involves incorporating Kubernetes into your existing development and deployment workflows. Tools like Helm for package management and CI/CD pipelines integrated with Kubernetes can streamline the development process and improve efficiency.

Kubernetes Playgrounds: These are interactive environments that allow you to experiment with Kubernetes without needing to set up your own cluster. Platforms like Labex provide Kubernetes playgrounds where you can practice deploying applications, configuring services, and managing resources in a controlled environment.

Kubernetes Exercises: Engaging in practical exercises is one of the best ways to learn Kubernetes. These exercises cover various scenarios, from basic deployments to complex multi-cluster setups, and help reinforce your understanding of key concepts.

Conclusion

Kubernetes is a powerful tool that simplifies the management of containerized applications through its robust orchestration capabilities. By familiarizing yourself with its core concepts—such as clusters, pods, services, and deployments—you can harness its full potential. Utilizing resources like Kubernetes Integration, Kubernetes Playgrounds, and Kubernetes Exercises will provide you with practical experience and deepen your understanding, making you better equipped to manage and scale your containerized applications effectively. As you continue to explore Kubernetes, you’ll find it an indispensable asset in the world of modern application development and operations.

[ascendient-learning]

7 Skills You'll Build in Top AI Certification Courses

You're considering AI certification courses to advance your career, but what exactly will you learn? These programs pack tremendous value by teaching practical skills that translate directly to real-world applications. Let's explore the seven key capabilities you'll develop through quality AI certification courses.

1. Machine Learning Fundamentals

Your journey begins with understanding how machines learn from data. You'll master supervised and unsupervised learning techniques, working with algorithms like linear regression, decision trees, and clustering methods. These foundational concepts form the backbone of AI systems, and you'll practice implementing them through hands-on projects that simulate actual business scenarios.

2. Deep Learning and Neural Networks

Building on machine learning basics, you will dive into neural networks and deep learning architectures. You will construct and train models using frameworks like TensorFlow and PyTorch, understanding how layers, activation functions, and backpropagation work together. Through AI certification courses, you will gain confidence working with convolutional neural networks for image processing and recurrent neural networks for sequential data. 

3. Natural Language Processing (NLP)

You will develop skills to make computers understand and generate human language. This includes text preprocessing, sentiment analysis, named entity recognition, and building chatbots. You'll work with transformer models and learn how technologies like GPT and BERT revolutionize language understanding. These NLP skills are increasingly valuable as businesses seek to automate customer service and content analysis.

4. Data Preprocessing and Feature Engineering

Raw data rarely comes ready for AI models. You'll learn to clean, transform, and prepare datasets effectively. This includes handling missing values, encoding categorical variables, scaling features, and creating new meaningful features from existing data. You'll understand why data scientists spend 80% of their time on data preparation and master techniques to streamline this crucial process.

5. Model Evaluation and Optimization

Creating an AI model is just the beginning. You'll learn to evaluate model performance using metrics like accuracy, precision, recall, and F1-score. You'll master techniques for preventing overfitting, including cross-validation, regularization, and dropout. AI certification courses teach you to fine-tune hyperparameters and optimize models for production environments, ensuring your solutions perform reliably in real-world conditions.

6. Ethical AI and Responsible Development

You'll explore the critical aspects of AI ethics, including bias detection and mitigation, fairness in algorithms, and privacy considerations. You'll learn frameworks for responsible AI development and understand regulatory requirements like GDPR's right to explanation. This knowledge positions you as a thoughtful practitioner who can navigate the complex ethical landscape of artificial intelligence.

7. AI Deployment and MLOps

Finally, you'll bridge the gap between development and production. You'll learn to deploy models using cloud platforms, create APIs for model serving, and implement monitoring systems to track performance over time. You'll understand containerization with Docker, orchestration with Kubernetes, and continuous integration/continuous deployment (CI/CD) pipelines for machine learning projects.

Conclusion

These seven skills represent a comprehensive toolkit for AI practitioners. The best AI certification courses combine theoretical knowledge with practical application, ensuring you can immediately apply what you've learned.

As you progress through your chosen program, you'll notice how these skills interconnect – from data preprocessing through model development to ethical deployment. This holistic understanding distinguishes certified AI professionals and provides the foundation for a successful career in artificial intelligence.

For more information, visit: https://www.ascendientlearning.com/it-training/vmware

[cgrdgrg]

Explore The Essential Skills Of A Postgraduate In Computer Science For A Smart Career Move.

The world of technology is continually changing, necessitating a dynamic skill set from computer science experts. As a postgraduate, you are about to begin an exciting career path. However, what key competencies will distinguish you and help you succeed?

At ISTM, we are committed to giving our students the skills and information they need to succeed in this competitive environment. Here is a thorough examination of the essential abilities that any Post Graduate In Computer Science student studying computer science should develop:

1. Foundational Programming Prowess:

Languages: Proficiency with fundamental programming languages such as Python, Java, C++, and JavaScript is necessary. Numerous software programs and systems are built on top of these languages.

Algorithms & Data Structures: A solid understanding of data structures (arrays, linked lists, trees, and graphs) and algorithms (sorting, searching, and graph traversal) is essential for effective problem-solving and code optimization.

OOP, or object-oriented programming: Understanding OOP concepts like inheritance, polymorphism, and encapsulation to build modular, reusable, and manageable code.

2. Data Science & Analytics:

Data Wrangling & Analysis: In today's data-driven environment, the capacity to extract, clean, transform, and analyze data is extremely valuable.

Machine Learning: Familiarity with machine learning principles, algorithms (supervised, unsupervised, and deep learning), and tools (such as TensorFlow and PyTorch) is becoming increasingly crucial.

Big Data Technologies: Handling and processing large datasets requires understanding big data technologies like Hadoop, Spark, and NoSQL databases.

3. Software Engineering Principles:

Software Development Lifecycle (SDLC): Successful software development projects require an understanding of the SDLC, which includes requirements gathering, design, implementation, testing, and maintenance.

Git version control: Effective code management, change tracking, and collaborative development depend on Git proficiency.

Flexible Methodologies: By comprehending agile concepts like Scrum and Kanban, you can deliver projects iteratively and adjust to changing requirements.

4. Cloud Computing:

Cloud Platforms: Knowledge of the services offered by well-known cloud providers, such as AWS, Azure, and GCP (compute, storage, networking, databases).

Cloud-Native Technology: Building and implementing cloud-based apps requires understanding serverless computing, orchestration (Kubernetes), and containerization (Docker).

5. Cybersecurity:

Fundamentals: To create secure and robust systems, it is essential to comprehend fundamental cybersecurity concepts such as threats, vulnerabilities, and assaults.

Ethical Hacking: You can find and fix security flaws by understanding ethical hacking techniques.

6. Communication & Collaboration:

Effective Communication: Briefly conveying technical information to audiences, including technical and non-technical people, is essential.

Teamwork: The success of every software development project depends on cooperation and efficient teamwork.

7. Problem-Solving & Critical Thinking:

Analytical Skills: It is crucial to dissect complicated issues into smaller, more manageable components and find workable answers.

Creative Thinking: It is highly regarded that one can think creatively and solve complex problems in novel ways.

8. Continuous Learning:

Lifelong Learning: Technology is a constantly changing sector. Maintaining a competitive edge and staying updated with the latest developments requires dedication to lifelong learning.

How ISTM Helps You Develop These Skills:

ISTM's extensive and industry-relevant curriculum aims to help students develop these vital abilities in pursuing Post Graduate In Computer Science. Our innovative facilities, industrial collaborations, and knowledgeable instructors guarantee that you will obtain real-world experience and be ready for the challenges of the workplace.

Practical Projects and Laboratories: We prioritize practical learning through case studies, and real-world projects.

Industry Partnerships: Our solid industry relationships can help you obtain certifications, internships, and guest lectures.

Emphasis on Innovation: Through research initiatives, hackathons, and incubator programs, we promote creativity and innovation.

Personalized support: Our committed faculty offers individualized support and mentorship to assist you with reaching your professional objectives.

Conclusion:

A Post Graduate In Computer Science gives you the skills you need to succeed in the ever-evolving tech sector. You can make a wise career choice by becoming proficient in these crucial abilities and taking advantage of the chances offered by a reputable organization like ISTM. To distinguish in the competitive job market, emphasize technical proficiency, real-world experience, and interpersonal development. Take the first step toward a fulfilling career in computer science by beginning your journey with ISTM right now. 

[jurysoft-raas]

Top 10 Skills to Look for in a Python Developer in 2025: How Jurysoft Helps You Hire the Best Talent

As we approach 2025, Python continues to dominate the programming landscape, offering unparalleled versatility in fields like web development, data science, machine learning, and automation. The demand for skilled Python developers is only growing, and finding the right talent can significantly impact the success of your projects. At Jurysoft, we understand the challenges of hiring the best Python developers, which is why we focus on delivering top-tier professionals with the skills that matter most.

In this article, we'll explore the top 10 skills you should look for in a Python developer in 2025 and show you how Jurysoft can help you hire the right developer to meet your unique needs.

1. Mastery of Python Fundamentals and Advanced Concepts

A strong foundation in Python basics is non-negotiable. Developers should be proficient in variables, data types, loops, functions, and control flow. But the best developers take it a step further, demonstrating expertise in advanced features like decorators, context managers, and lambda functions.

At Jurysoft, we ensure that our developers not only excel in Python fundamentals but are also capable of handling more sophisticated programming challenges, ensuring they can write clean, scalable, and efficient code for any project.

2. Expertise in Web Development Frameworks (Django, Flask, FastAPI)

Web development is one of the most common areas for Python developers, and proficiency in popular frameworks like Django, Flask, and FastAPI is crucial. Django is perfect for large, enterprise-level applications, while Flask offers a lighter, more flexible framework, and FastAPI is optimized for high-performance APIs.

With Jurysoft, you get access to developers who are experts in these frameworks, ensuring that your web applications are developed efficiently, securely, and are built to scale according to your business needs.

3. Deep Knowledge of Data Structures and Algorithms

Whether you are building data-heavy applications or working on performance optimization, a strong understanding of data structures and algorithms is a must. Developers should know when and how to use lists, stacks, queues, trees, and graphs, and should be familiar with algorithms for sorting, searching, and optimizing performance.

At Jurysoft, we prioritize hiring developers with a sharp focus on problem-solving skills. Our developers are well-versed in writing efficient algorithms that can handle large datasets and complex tasks with ease.

4. Proficiency in Data Science and Machine Learning

Python is the language of choice for data science and machine learning, and a good developer should be comfortable using libraries like NumPy, Pandas, Matplotlib, SciPy, and Scikit-learn. With the rise of AI-driven applications, the ability to build predictive models and analyze big data is more valuable than ever.

If your project involves machine learning or AI, Jurysoft connects you with developers who are not only proficient in these libraries but also experienced in deploying machine learning models to production.

5. Cloud Computing Experience (AWS, Google Cloud, Azure)

In today’s world, cloud computing is essential for building scalable, high-performance applications. Python developers should have hands-on experience with major cloud platforms like AWS, Google Cloud, and Microsoft Azure. They should know how to deploy applications, manage databases, and integrate with cloud-native services like Lambda, S3, and Kubernetes.

Our developers at Jurysoft are cloud-savvy, ensuring your applications are optimized for cloud environments and can handle rapid scaling as your business grows.

6. Version Control (Git) Proficiency

Version control systems, especially Git, are essential for collaboration and managing project versions. Skilled developers should be proficient in using Git for branching, merging, and resolving conflicts. A strong Git workflow ensures that team members can work simultaneously on the same codebase without disrupting progress.

At Jurysoft, we emphasize the importance of a seamless development process. Our developers are experts in using Git to streamline collaboration and maintain code integrity throughout the development cycle.

7. Expert Testing and Debugging Skills

Writing code is only half the job; testing and debugging are what ensure the software works correctly and efficiently. Developers should be skilled in writing unit tests, conducting integration testing, and using frameworks like PyTest or unittest. Additionally, the ability to debug complex issues and optimize performance is essential.

With Jurysoft, you can be assured that the developers we provide are well-versed in testing best practices, ensuring your software is reliable and bug-free from the start.

8. Security Best Practices

Security is a growing concern for businesses, especially as cyber threats continue to evolve. Python developers should understand best practices for writing secure code, such as preventing SQL injection, cross-site scripting (XSS), and cross-site request forgery (CSRF). They should also be proficient in encryption, authentication, and secure API design.

At Jurysoft, we prioritize security across all our development projects. Our developers are trained in industry-standard security practices, ensuring your application is safe and protected from potential vulnerabilities.

9. Strong Communication and Collaboration Skills

While technical expertise is key, communication and collaboration are equally important. A great Python developer needs to work effectively with team members, product managers, and clients. They should be able to explain technical concepts clearly and provide updates on progress.

At Jurysoft, we not only focus on technical skills but also emphasize the importance of soft skills. Our developers are collaborative team players who can communicate effectively, ensuring smooth project execution and alignment with business goals.

10. Continuous Learning and Adaptability

Technology is always changing, and a great Python developer must be committed to learning new tools, techniques, and technologies. Whether it’s exploring new Python libraries, attending conferences, or taking online courses, the best developers are those who are always evolving with the industry.

At Jurysoft, we believe in fostering a culture of continuous improvement. Our developers are passionate about learning and staying up to date with the latest Python trends, ensuring they can apply the newest technologies to your project.

Why Choose Jurysoft for Your Python Developer Needs?

At Jurysoft, we understand that finding the right Python developer can be challenging. That's why we specialize in providing businesses with top-notch Python developers who are experts in the latest technologies and best practices.

Whether you need a developer for a short-term project, long-term partnership, or specialized task, Jurysoft can help you find the right match. We take pride in our rigorous hiring process, which ensures that our developers are not only highly skilled but also a great fit for your company culture.

From web development to machine learning and cloud computing, Jurysoft is your trusted partner for hiring Python developers who can take your projects to the next level.

Contact us today, and let us help you find the perfect Python developer for your team in 2025!

[innovativesjobs]

How to Prepare for Interviews for Senior Software Engineer Jobs

“Crack the Code: Mastering Your Interview for Senior Software Engineer Jobs”

Landing a position in Senior Software Engineer Jobs is no small feat. It requires not only exceptional technical skills but also the ability to demonstrate leadership, problem-solving prowess, and a deep understanding of software development principles. If you’re aiming to secure a role in Software Engineer Jobs at the senior level, you need a strategic approach to your interview preparation. Here’s a comprehensive guide to help you ace your interviews and land that dream job!

1. Understand the Role and Expectations

Before diving into preparation, it's crucial to understand what makes a great Senior Software Engineer. Here’s what recruiters typically look for:

Technical Expertise: Deep knowledge in programming languages (Java, Python, C++), algorithms, and data structures.

System Design Skills: Ability to design scalable, reliable, and efficient systems.

Leadership and Mentorship: Proven track record of leading teams, mentoring junior engineers, and driving projects to completion.

Problem-Solving Ability: Strong analytical skills and a knack for tackling complex technical challenges.

2. Revise Core Technical Skills

As a Senior Software Engineer, you must demonstrate a strong grasp of technical fundamentals. Here’s a focused approach:

Advanced Algorithms and Data Structures: Brush up on algorithms (sorting, searching, dynamic programming) and data structures (trees, graphs, heaps). Practice problems on platforms like LeetCode, HackerRank, or CodeSignal.

System Design: Master system design principles. Study case studies and practice designing scalable systems. Key areas include load balancing, caching, database sharding, and microservices architecture. Resources like Grokking the System Design Interview can be invaluable.

3. Hands-On Coding and Problem Solving

Coding interviews are a critical component of Senior Software Engineer Jobs. Here’s how to excel:

Mock Interviews: Participate in mock interviews with peers or use platforms like Pramp or Interviewing.io to simulate real interview scenarios. This helps you get comfortable with the format and receive feedback.

Coding Practice: Work on coding challenges regularly. Focus on solving problems that are likely to be asked in senior-level interviews. Use tools like LeetCode, Codeforces, or TopCoder.

4. Deep Dive into Technologies and Tools

Senior roles often require expertise in specific technologies. Here’s a breakdown:

Programming Languages: Ensure you are proficient in the languages commonly used in the industry. For instance, Java, Python, C++, or JavaScript.

Development Tools and Frameworks: Be well-versed in popular frameworks and tools relevant to your field. This might include Spring Boot for Java, Django for Python, or React for JavaScript.

DevOps and CI/CD: Familiarize yourself with DevOps practices, CI/CD pipelines, and tools like Jenkins, Docker, Kubernetes, or Terraform. Understanding these can give you an edge.

5. Showcase Your Problem-Solving Skills

Problem-solving is a core competency for senior roles. Here’s how to showcase it:

Real-World Problems: Prepare to discuss past projects and problems you’ve solved. Highlight your role, the challenges faced, and the impact of your solutions.

Technical Deep Dives: Be ready to dive deep into technical discussions. Explain your thought process, decisions, and trade-offs. Use the STAR method (Situation, Task, Action, Result) to structure your answers.

6. Prepare for Behavioral and Situational Questions

Senior positions often come with leadership and behavioral questions. Here’s how to prepare:

Leadership Experience: Be ready to discuss your experience in leading teams, mentoring peers, and driving projects. Use specific examples to demonstrate your leadership style and achievements.

Problem-Solving Scenarios: Expect situational questions that test your decision-making and problem-solving skills. Practice questions like, “How do you handle conflicts within your team?” or “Describe a time when you had to solve a complex technical problem.”

7. Demonstrate Your Soft Skills

Soft skills are crucial for senior roles. Here’s how to highlight them:

Communication Skills: Clearly articulate your thoughts and ideas. Practice explaining complex technical concepts to non-technical stakeholders.

Collaboration and Teamwork: Showcase your ability to work effectively in a team. Discuss your experience with cross-functional teams, code reviews, and collaborative projects.

8. Research the Company and Role

Understanding the company’s culture, products, and technologies is essential:

Company Research: Study the company’s website, recent projects, and news. Understand their tech stack, products, and market position.

Role-Specific Preparation: Review the job description carefully. Align your skills and experiences with the requirements. Prepare to discuss how you can contribute to their projects and goals.

9. Ask Insightful Questions

Asking thoughtful questions can set you apart:

About the Team: Inquire about the team structure, development processes, and current projects. Questions like, “What are the biggest challenges the team is facing?” or “How does the team handle code reviews?”

About Growth and Opportunities: Ask about career growth opportunities, learning and development programs, or future projects. Questions like, “What opportunities are there for professional development?” or “What are the next big projects the team is working on?”

10. Practice, Practice, Practice

The key to acing your interview is consistent practice:

Mock Interviews: Schedule regular mock interviews with peers or mentors. Use platforms like Interviewing.io or Pramp for real-time feedback.

Coding Practice: Dedicate time each day to coding practice. Solve problems on competitive coding sites and review your solutions.

Feedback Loop: Seek feedback on your coding and interview performance. Use this feedback to refine your approach and improve continuously.

[neckbeggar0-blog]

Is It Easy To Learn Selenium If I Don'T Know Java?

Learn Java.

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Content

Licensed Software Program Examination Automation Architect.

Automation Testing Resources.

Test Automation With Selenium Webdriver.

Leading Tips For Discovering Java Programming.

Pointer # 3: Chrome Devtools: Replicating Network Issues

Licensed Software Program Examination Automation Engineer.

Then, practice your skills with two jobs where you produce and control variables. Self-paced introductory Java programs are available along with professional certificate programs created to educate you progressed Java programming abilities and also prepare you for a job. Java - a high-level programming language - is among the most effective languages for finding out core coding skills as a result of its object-oriented technique to programming. Learning the Java programs software application will get you started on a course to coming to be a software program engineer, among the most sought-after roles in the field of computer technology. Java is a computer shows language developed by James Gosling at Sun Microsystems.

Automation Testing Resources.

My own personal experience with Java is that it in fact was rather challenging. Obviously, that will certainly vary from one person to another and will certainly also rely on whether this is the initial programs language you're finding out or otherwise. Prior to discovering Java, I discovered the fundamentals of internet growth such as HTML5 as well as CSS3. Nonetheless, contrasting both is like comparing apples to oranges.

Certificate course in Java is among the most prominent temporary work oriented program. Trainees that go with this program will definitely obtain a great work. The average salary provided to students that have a certification course in Java varies from INR 1,80,000 to INR 6,00,000 each year depending upon the experience and also knowledge of the trainee. One can claim that there are a lot of task opportunities in the field of Java and also candidates are likewise obtaining handsome salaries.

You will discover the Java code fundamentals such as object-oriented shows, analytical, event-driven programs, how to create ranges as well as much more. After discovering the syntax of Java, the next thing to do is to find out the principles. Because I really did not exercise enough, I fell short Java the initial time I took it. The primary factor being that I was so hectic with the other courses that I tried to stuff a whole week's well worth of shows and also discovering right into a solitary day. I made a poll in the Facebook group, Java Programmers, which is a popular team of over 100,000 Java developers ranging in experience from newbie to professional of greater than 10 years.

This is a detailed training course that includes a video of 72 hours bring all essential info that a Java programmer must recognize. This course uses thorough expertise about the Java Programs language. Additionally, we underwent guests' reviews to identify the best Java courses for you.

Python has always had a presence in the ability space and also is considered to be one of the most favorable language for Machine Learning, Expert System, IoT as well as a great deal more. It takes 10 lines of code to review from a data in Java. Various projects are supplied as component of the course to acquire boosted knowledge and also abilities in Java language. You will get access to the huge database, write-ups, and also video clips that will include abilities and also share experiences.

Examination Automation With Selenium Webdriver.

Access is provided to obtain understanding regarding 500+ programs. The program will certainly aid you get expertise in examining the CSV documents or Comma-Separated Worth data. The training course will certainly guide gain access to as well as transform pictures, web sites and other data using Java. Mentor goes back to square one degrees as well as devices like Eclipse and also Maven are shown which are vital for comprehending Java growth.

Why is Java better than Python?

Based on the report details, the top Quality Assurance and testing objective, for not only 2019 but the next years to come, is end-user satisfaction. The role of a QA engineer has evolved from finding defects to actually thinking as the end-user. Software testers need to focus more on the whole experience.

However this is inhibited, as well as using one browser per node is taken into consideration finest practice for optimal efficiency.

Below are some ideas to make your waits a lot more resistant.

They can additionally speed up your test by rendering any kind of rests or stops redundant as well as conquer slow-moving network and also cross-browser problems.

If they do fail, this makes certain that any kind of Dockers are promptly brought back or changed.

To produce a steady variation of the Grid for your CI pipeline, it's likewise possible to release your Grid onto Kubernetes or Throng.

Java is known for being simpler to learn and also use than its predecessor, C++. Nonetheless, software testen opleiding 's also understood for being slightly more challenging to learn than Python as a result of Java's fairly extensive syntax.

Then it definitely will not be hard, if you've already discovered either Python or C++ before finding out Java. Begin on a course to a job as a Java Developer or Java Software Application Designer with a professional certification program on edX. Select from any variety of initial Java courses and Java tutorials for beginners. Begin with among the basics programs from HKUST as they are basically a cost-free Java tutorial for newbies.

Which testing is in demand?

For Selenium IDE you don't need any prior java knowledge. But for the most commonly used Selenium webdriver using java. U require basic core java concepts like OOP(Object Oriented Programming).

Top Tips For Discovering Java Programming.

HTML is a markup language as well as CSS is a styling language for said markup so neither are actual programs languages like Java is. So it's not really reasonable to say that Java is a tough shows language to learn on that basis. In a survey of 324 Java programmers ranging from novice to specialist, the overwhelming action, regarding 75% of pollers, is that Java is not a difficult language to find out.

Does manual testing require coding?

No need of coding knowledge required for manual testing. For testing field you want skills to find different bugs ie. UI related bugs,functionality related bugs,performance related bugs,also you need good analytical skills and more important thing you need patience during testing.

Create A Junit Examination Course

Trainees having experience in this field will undoubtedly obtain a high salaried work. Nowadays, MNCs prepare to provide respectable salaries to knowledgeable candidates. The students are introduced to numerous fundamental and also innovative fundamentals of Java, like OOPs, Information Frameworks, Formulas, and so on . Growing a Tree Write your initial Java program from square one by presenting yourself to individuals and planting a tree for them. You'll practice developing a course, specifying the primary technique, and also arranging print declarations.

Tip # 3: Chrome Devtools: Simulating Network Conditions

Java was first launched in 1995 and also has actually given that turned into one of the most popular programs languages with an estimated 12 million developers utilizing it It can also be made use of for artificial intelligence, artificial intelligence, blockchain, RSS feeds, and also Java applications. The Java platform differs from a lot of other platforms in that it's a software-only platform that operates on top of various other hardware-based platforms. According to Oracle, Java can reduce costs, drive technology, as well as extra as the shows language of choice for IoT, venture design, enterprise applications, and also cloud computing.

[austaliablogserviceexpert]

How to become a gardener

Gardeners are required to do a lot of physical labor. In addition to managing plants and other garden necessities, a gardener should be able to handle small and large machinery safely. Depending on the role, a gardener can also provide guidance and training to management, as well as perform basic maintenance tasks. Candidates must have at least two years experience to become a gardener. They should also have strong technical knowledge, be able to operate basic hand tools and light machinery, and have excellent interpersonal skills. A gardener is responsible for maintaining the health of a cluster by watering it and fertilizing it. The branches and dead plants are removed and then composted for future uses. The debris from these processes can be used to create fertilizer. A gardener tends to seventy two trees, seven hundred and twenty five acres of turf grass, as well as approximately seven thousand shrubs. This work involves using a variety of hand and power tools. A gardener must deploy kubectl to manage pods and clusters. This tool allows users to monitor the health of their clusters. The app provides a central dashboard that allows users to keep track of all aspects related to their cluster. It allows operators and teams to collaborate on issues and collaborate on projects. They can also track and manage their deployments. It also offers a host of other features, such as a centralized data dashboard, which lets users view relevant information. Gardeners can manage all types of green spaces efficiently. Common tasks include weeding and deadheading, as well as pruning. Other tasks include creating and managing a dedicated Namespace and administering infrastructure account secret information, monitoring cluster health, and monitoring it. A gardener should also be familiar with the different types of plants and how they are identified. He should also know how to use chemicals and equipment. A gardener must be familiar with kubectl in order to perform these tasks. A gardener will usually implement an inception approach to Kubernetes. By using the kubectl command line tool, a gardener can configure and manage the cluster. He must also manage the secrets of the infrastructure accounts. An experienced gardener should be able to use the kubectl command to install the kubectl application. The key to implementing a proper inception strategy is to use a separate controller for each pod. A gardener's job involves performing various tasks to maintain a garden. They often plant flowers and other plants, prune plants, and prune trees. They also monitor the cluster and their health. They may also use tools for managing infrastructure account secrets. They can use the command kubectl to create and run Kubernetes containers. These are the main benefits of Gardener. Gardeners can use kubectl for managing clusters on multiple clouds. The Gardener command line tool is essential for monitoring a cluster. The Gardener dashboard is a dashboard that allows users to monitor the health of each cluster. It's a central dashboard that allows operators and teams collaborate. It is easy to use and includes many other features. A dashboard allows administrators to keep track of the status of the entire cluster and track issues. The user can even customize the appearance of the dashboard, which allows them to customize it. To deploy Gardener, you will need the Gardener command-line tool. The kubectl tool is a centralized tool for managing Kubernetes clusters. It has a central dashboard that allows users to monitor cluster health, and collaborate on issues. It is also useful for managing account secrets and infrastructure accounts. It provides a snapshot of the current state of the cluster and detailed information for managers and operators. The Gardener can monitor the health and performance of each component of a cluster through a single interface. A Gardener installation requires the kubectl command line tool. The kubectl tool provides monitoring and management of Kubernetes clusters. It can also manage infrastructure accounts, and other secrets. The kubectl command line tool allows users to monitor and manage the clusters. Operators need a centralized dashboard to monitor the health of their clusters. It helps them manage the health of their clusters. It also provides them with relevant data.

[solaceinfotechpvtltd]

Best Machine Learning Software and Tools To Learn in 2019

Data scientists need an efficient and also effective machine learning software, tools or framework. For developing the system with the required training data to erase the drawbacks and make the machine or device intelligent. Just a well-characterized software can develop a productive machine. However, nowadays we develop our machine such that, we don’t need to give any instructions about the surroundings. The machine can act by itself, and also it can understand the environment. So we don’t need to guide it. Let us see the top 10 best machine learning software and tools.

Top 10 best machine learning software and tools-

1. Apache Mahout-

Apache Mahout is a mathematically expressive Scala DSL and a distributed linear algebra framework. It is a free and open source venture of the Apache Software Foundation. The aim of this framework is to implement an algorithm rapidly for data scientists, mathematicians and also statisticians.

Features-

This framework used to build scalable algorithms.

Implementing machine learning techniques such as clustering, recommendation, and classification, collaborative filtering.

It includes matrix and vector libraries.

Run on top of Apache Hadoop using the MapReduce paradigm.

2. Shogun-

It is an open source machine learning library. This tool is written in C++. Literally, it provides data structures and also algorithms for machine learning problems. It supports many languages like Python, R, Octave, Java, C#, Ruby, Lua, etc. Shogun is easy combination of multiple data representations, algorithm classes and general purpose tools for rapid prototyping of data pipelines.

Features-

For large scale learning, this tool can be used.

Mainly, it focuses on kernel machines like support vector machines for classification and regression problems.

Allows linking to other machine learning libraries like LibSVM, LibLinear, SVMLight, LibOCAS, etc.

It can process a vast amount of data like 10 million samples.

It provides interfaces for Python, Lua, Octave, Java, C#, Ruby, MatLab, and R.

3. Amazon Machine learning-

It is a robust and cloud-based machine learning software which can be used by all skill levels of developers. For building machine learning models and generating predictions, this managed service can be used. It integrates data from multiple sources: Amazon S3, Redshift or RDS.

Features-

Amazon Machine Learning provides visualization tools and wizards.

AML supports binary classification, multi-class classification, and regression.

It also allows users to create a data source object from the MySQL database.

It permits users to create a data source object from data stored in Amazon Redshift.

4. Google cloud ML engine-

Cloud Machine Learning Engine is a managed service that allows developers and data scientists to build and run superior machine learning models in production. Cloud ML Engine offers training and prediction services, which can be used together or individually. It has been used by enterprises to solve problems ranging from identifying clouds in satellite images, ensuring food safety, and responding four times faster to customer emails.

Features-

It provides ML model building, training, predictive modeling, and deep learning.

Cloud ML Engine has deep integration with our managed notebook service and our data services for machine learning.

Training and Online Prediction support multiple frameworks to train and serve classification, regression, clustering, and dimensionality reduction models.

The two services namely training and prediction can be used jointly or independently.

This software is used by enterprises, i.e., detecting clouds in a satellite image, responding faster to customer emails.

It can be used to train a complex model.

5. Accord.Net-

It is a .Net machine learning framework combined with audio and image processing libraries written in C#. This framework consists of multiple libraries for large number of applications, i.e., statistical data processing, pattern recognition, and linear algebra. It includes the Accord.Math, Accord.Statistics, and Accord.MachineLearning.

Features-

This framework is used for developing production-grade computer vision, computer audition, signal processing, and statistics applications.

It includes more than 40 parametric and non-parametric estimation of statistical distributions.

Also contains more than 35 hypothesis tests including one way and two-way ANOVA tests, non-parametric tests like Kolmogorov-Smirnov test and many more.

It has more than 38 kernel functions.

6. Apache Spark MLlib-

It is a machine learning library. Apache Spark MLlib runs on Hadoop, Apache Mesos, Kubernetes, standalone, or in the cloud. It can access data from multiple data sources. It has several algorithms are like – logistic regression, naive Bayes, generalized linear regression, K-means, and many more. Its workflow utilities are Feature transformations, ML Pipeline construction, ML persistence, etc.

Features–

It is easy to use.

Apache Spark MLlib can be usable in Java, Scala, Python, and R.

MLlib fits into Spark’s APIs and inter-operates with NumPy in Python and R libraries.

Hadoop data source like HDFS, HBase, or local files can be used. So it is easy to plug into Hadoop workflows.

It contains high-quality algorithms and outperforms better than MapReduce.

7. Apple’s Core ML-

Apple’s Core ML is a machine learning framework which helps to integrate machine learning models into your app. You have to drop the ml model file into your project, and the Xcode create an Objective-C or Swift wrapper class automatically. Using the model is straightforward. It can leverage each CPUs and GPUs for maximum performance.

Features:

This library acts as a foundation for domain-specific frameworks and functionality.

Core ML supports Computer Vision for image analysis, Natural Language for natural language processing, and GameplayKit for evaluating learned decision trees.

It builds on top of low-level primitives.

8. TensorFlow-

TensorFlow is most popular and lovable by machine learning users. It’s an open source machine learning library which helps you to develop your ML models. Google team developed TensorFlow. It has a flexible tools, libraries, and resources that allows researchers and developers to build and deploy machine learning applications.

Features:

An end-to-end deep learning system.

Build and train ML models effortlessly using intuitive high-level APIs like Keras with eager execution.

Highly flexible.

Performs numerical computations using data flow graphs.

Run on CPUs or GPUs

Run on mobile computing platforms.

Efficiently train and deploy the model in the cloud.

9. Azure Machine Learning Studio-

Microsoft Azure Machine Learning Studio is a collaborative, drag-and-drop tool used to build, test, and deploy predictive analytics solutions on your data. This tool publishes models as web services that may be consumed by custom apps or BI tools.

Read more at- https://solaceinfotech.com/blog/best-machine-learning-software-and-tools/

[doorrepcal33169]

Building complex systems? We’ve got you covered at Velocity San Jose

The O'Reilly Velocity Conference in San Jose will cover what you need to know to build high-performance, resilient, and secure systems.

Let’s face it, your systems aren't getting any less complex, and the list of skills you need to build and maintain them keeps growing. Modern systems pose a number of thorny challenges: they are inherently complex and span multiple technologies, groups, and sometimes different organizations altogether. Most poignantly, they tend to fail in the most unexpected and spectacular ways. At Velocity this year, we’ve identified three primary areas of focus to help you build and run the systems that power modern businesses: performance, resilience, and security.

Performance

The larger your applications get, the harder it is to understand their performance and troubleshoot problems. This increased complexity in applications and services requires new methods for monitoring and improved observability. Here are some sessions designed to help you tackle performance issues:

Architecting a postmortem: Teams need to perform too. Etsy’s Will Gallego explores postmortems used at large tech companies with real-world examples of failure scenarios and debunks myths regularly attributed to failures.

Think local: Reducing coordination and improving performance when designing around distributed state Learn strategies for avoiding coordination and relying on local knowledge wherever possible and tips for using in-memory state instead of the typical approach of using external data stores.

Moving enterprise Java applications to Kubernetes Heptio’s Kris Nova takes you through the process of migrating a monolithic Java application to running in Kubernetes using a prototype Java application that has been purposely designed to be hard to run cloud natively as an example.

Gaining efficiency with time series in ELK In this case study, learn how NS1 was able to reduce infrastructure, maintenance, and operational costs while simultaneously increasing throughput and visibility of key metrics by leveraging Elasticsearch as a time series database.

Containers: Let's get fancy: Go beyond getting started with containers on AWS with Amazon’s Abby Fuller and get the guidance you need to solve harder issues.

Resilience

Building and running complex systems that are both fast and reliable requires teams and applications that work well—and work well together. The cultural shift is evident: software engineers and system administrators are breaking down walls as they move toward shared responsibilities, thereby quickening the pace of software development and delivery. Here are some sessions to help you build resilient systems to withstand Black Friday sales, scaling, and, well, people:

Crossing the serverless fireswamp: Symphonia’s Mike Roberts leads you on a warts-and-all journey through some of the limitations of a serverless approach and shares a practical set of techniques for dealing with them.

How to monitor your database: Don’t make the same mistakes Baron did! VividCortex CEO Baron Shwartz shares the framework he’s developed over the years for monitoring databases, which breaks monitoring into a holistic approach that’s easy to understand and makes it obvious what kinds of data are useful for what purposes.  

From dandelion to tree: Scaling Slack: In this case study, learn how Slack scaled by rearchitecting its system with lazy loading, a publish/subscribe model, and an edge cache service.

Principia SLOdica: A treatise on the metrology of service level objectives: Google's Jamie Wilkinson offers an overview of SLOs and error budgets, as well as advice on how the implementation of that changes as systems scale, and the tools you’ll need once the alerts themselves no longer tell you what part is broken.

A retrospective on retrospectives: How to be a nonexpert expert in system resilience: Do companies that aren’t unicorns need to become experts in human factors and experts in their software stack in order to engineer reliable systems? Jessica DeVita tells the story of how a team at Microsoft challenged themselves to retrospect their retrospectives and shares what they learned about applying human factors ideas to software development.

Security

Security can no longer be bolted on at the end of projects. Learn how to incorporate security best practices into your system architecture from the ground up into every layer of your applications. Here's a session lineup packed with case studies, techniques, and ideas you’ll want to bring back to your team:

How to establish a high-severity incident management program: Gremlin’s Tammy Butow leads this three-hour tutorial on how to create a high-severity incident management program and measure its success.

Attack trees: Security modeling for Agile teams: Learn a new approach to reviewing systems along with real-life examples to help you prioritize where to focus your security efforts.

You want to step outside? What our fight against phishing taught us and how it can help you: In this case study from Google, explore data from a study on phishing and learn about the effectiveness of phishing prevention tools.

Design for security: Serena Chen shares four strategies that apply design thinking to security problems, pinpointing which practices work and which are detrimental.

Kubernetes security best practices: Google’s Ian Lewis shares the easiest and best ways to improve the security of your Kubernetes clusters.

Wait, there's more...

Some topics require more than 40 minutes to master, which is why we’re offering a number of in-person, expert-led trainings, like Mastering continuously deployed serverless applications and Docker: Up and Running. And if your team needs to be on the same page with new technology, you’ll want to check out the 2-day and 1-day trainings on new tools like Habitat and Nomad, and our crash courses on getting started with Kubernetes and R (the programming language you want to learn to get more from your data).

At Velocity San Jose, we’ll cover the technologies, tools, and issues that you’re tackling on the job every day, or soon will be—like networking Kubernetes, going serverless, improving observability, and managing teams. Between the great networking, fun events, and enlightening keynotes, you’ll find actionable takeaways and intriguing case studies in every session. We look forward to seeing you in San Jose this June. You’ll leave with new ideas, proven best practices, and an expanded network of friends and mentors to help you tackle your next project and advance your career.

Continue reading Building complex systems? We’ve got you covered at Velocity San Jose.

from FEED 10 TECHNOLOGY https://ift.tt/2GeLQUM

[repmywind02199]

Building complex systems? We’ve got you covered at Velocity San Jose

Building complex systems? We’ve got you covered at Velocity San Jose

The O'Reilly Velocity Conference in San Jose will cover what you need to know to build high-performance, resilient, and secure systems.

Let’s face it, your systems aren't getting any less complex, and the list of skills you need to build and maintain them keeps growing. Modern systems pose a number of thorny challenges: they are inherently complex and span multiple technologies, groups, and sometimes different organizations altogether. Most poignantly, they tend to fail in the most unexpected and spectacular ways. At Velocity this year, we’ve identified three primary areas of focus to help you build and run the systems that power modern businesses: performance, resilience, and security.

Performance

The larger your applications get, the harder it is to understand their performance and troubleshoot problems. This increased complexity in applications and services requires new methods for monitoring and improved observability. Here are some sessions designed to help you tackle performance issues:

Architecting a postmortem: Teams need to perform too. Etsy’s Will Gallego explores postmortems used at large tech companies with real-world examples of failure scenarios and debunks myths regularly attributed to failures.

Think local: Reducing coordination and improving performance when designing around distributed state Learn strategies for avoiding coordination and relying on local knowledge wherever possible and tips for using in-memory state instead of the typical approach of using external data stores.

Moving enterprise Java applications to Kubernetes Heptio’s Kris Nova takes you through the process of migrating a monolithic Java application to running in Kubernetes using a prototype Java application that has been purposely designed to be hard to run cloud natively as an example.

Gaining efficiency with time series in ELK In this case study, learn how NS1 was able to reduce infrastructure, maintenance, and operational costs while simultaneously increasing throughput and visibility of key metrics by leveraging Elasticsearch as a time series database.

Containers: Let's get fancy: Go beyond getting started with containers on AWS with Amazon’s Abby Fuller and get the guidance you need to solve harder issues.

Resilience

Building and running complex systems that are both fast and reliable requires teams and applications that work well—and work well together. The cultural shift is evident: software engineers and system administrators are breaking down walls as they move toward shared responsibilities, thereby quickening the pace of software development and delivery. Here are some sessions to help you build resilient systems to withstand Black Friday sales, scaling, and, well, people:

Crossing the serverless fireswamp: Symphonia’s Mike Roberts leads you on a warts-and-all journey through some of the limitations of a serverless approach and shares a practical set of techniques for dealing with them.

How to monitor your database: Don’t make the same mistakes Baron did! VividCortex CEO Baron Shwartz shares the framework he’s developed over the years for monitoring databases, which breaks monitoring into a holistic approach that’s easy to understand and makes it obvious what kinds of data are useful for what purposes.  

From dandelion to tree: Scaling Slack: In this case study, learn how Slack scaled by rearchitecting its system with lazy loading, a publish/subscribe model, and an edge cache service.

Principia SLOdica: A treatise on the metrology of service level objectives: Google's Jamie Wilkinson offers an overview of SLOs and error budgets, as well as advice on how the implementation of that changes as systems scale, and the tools you’ll need once the alerts themselves no longer tell you what part is broken.

A retrospective on retrospectives: How to be a nonexpert expert in system resilience: Do companies that aren’t unicorns need to become experts in human factors and experts in their software stack in order to engineer reliable systems? Jessica DeVita tells the story of how a team at Microsoft challenged themselves to retrospect their retrospectives and shares what they learned about applying human factors ideas to software development.

Security

Security can no longer be bolted on at the end of projects. Learn how to incorporate security best practices into your system architecture from the ground up into every layer of your applications. Here's a session lineup packed with case studies, techniques, and ideas you’ll want to bring back to your team:

How to establish a high-severity incident management program: Gremlin’s Tammy Butow leads this three-hour tutorial on how to create a high-severity incident management program and measure its success.

Attack trees: Security modeling for Agile teams: Learn a new approach to reviewing systems along with real-life examples to help you prioritize where to focus your security efforts.

You want to step outside? What our fight against phishing taught us and how it can help you: In this case study from Google, explore data from a study on phishing and learn about the effectiveness of phishing prevention tools.

Design for security: Serena Chen shares four strategies that apply design thinking to security problems, pinpointing which practices work and which are detrimental.

Kubernetes security best practices: Google’s Ian Lewis shares the easiest and best ways to improve the security of your Kubernetes clusters.

Wait, there's more...

Some topics require more than 40 minutes to master, which is why we’re offering a number of in-person, expert-led trainings, like Mastering continuously deployed serverless applications and Docker: Up and Running. And if your team needs to be on the same page with new technology, you’ll want to check out the 2-day and 1-day trainings on new tools like Habitat and Nomad, and our crash courses on getting started with Kubernetes and R (the programming language you want to learn to get more from your data).

At Velocity San Jose, we’ll cover the technologies, tools, and issues that you’re tackling on the job every day, or soon will be—like networking Kubernetes, going serverless, improving observability, and managing teams. Between the great networking, fun events, and enlightening keynotes, you’ll find actionable takeaways and intriguing case studies in every session. We look forward to seeing you in San Jose this June. You’ll leave with new ideas, proven best practices, and an expanded network of friends and mentors to help you tackle your next project and advance your career.

Continue reading Building complex systems? We’ve got you covered at Velocity San Jose.

https://ift.tt/2GeLQUM

[labexio]

Mastering Kubernetes: A Comprehensive Guide to Kubernetes Skill Tree Free

Kubernetes has become an essential tool for modern developers and IT professionals aiming to manage containerized applications effectively. With its robust features and scalability, Kubernetes empowers organizations to automate deployments, manage workloads, and optimize resource utilization. Leveraging the Kubernetes Skill Tree can be a game-changer for mastering Kubernetes concepts and achieving seamless Kubernetes integration in your projects.

Why Kubernetes Matters

Kubernetes, also known as K8s, is an open-source platform designed to manage containerized workloads and services. It automates deployment, scaling, and operations, providing the flexibility needed for dynamic environments. Whether you're running a small project or managing large-scale enterprise applications, Kubernetes offers unmatched reliability and control.

Navigating the Kubernetes Skill Tree

The Kubernetes Skill Tree is an innovative approach to structured learning, breaking down complex topics into manageable, progressive steps. It allows learners to advance through foundational, intermediate, and advanced concepts at their own pace. Key areas of focus in the Kubernetes Skill Tree include:

Foundational Concepts

Understanding Kubernetes architecture and components.

Learning about nodes, pods, and clusters.

Basics of YAML files for deployment configuration.

Core Operations

Deploying applications with Kubernetes.

Managing scaling and resource allocation.

Monitoring and maintaining workloads.

Advanced Techniques

Setting up CI/CD pipelines with Kubernetes.

Leveraging Helm charts for application management.

Implementing security best practices.

This structured approach helps learners build a strong foundation while gradually mastering advanced Kubernetes capabilities.

Exploring the Kubernetes Playground

Hands-on practice is critical to understanding Kubernetes, and the Kubernetes Playground provides an ideal environment for experimentation. This interactive platform allows developers to test configurations, deploy applications, and debug issues without affecting production systems.

Benefits of the Kubernetes Playground include:

Safe Experimentation: Try new ideas without fear of breaking live systems.

Real-World Scenarios: Simulate deployment and scaling challenges in a controlled environment.

Collaboration: Work alongside team members to solve problems and share knowledge.

By incorporating regular practice in the Kubernetes Playground, learners can reinforce their understanding of concepts and gain confidence in applying them to real-world projects.

Streamlining Kubernetes Integration

One of the most critical aspects of Kubernetes adoption is ensuring seamless Kubernetes integration with existing systems and workflows. Integration can involve connecting Kubernetes with cloud services, on-premise systems, or third-party tools.

Steps to effective Kubernetes integration include:

Assessing Requirements: Identify the systems and services to integrate with Kubernetes.

Configuring Networking: Ensure proper communication between Kubernetes clusters and external services.

Automating Workflows: Use tools like Jenkins, GitLab CI/CD, and Terraform for automated deployments.

Monitoring Performance: Implement tools such as Prometheus and Grafana for real-time monitoring and alerts.

Successful integration not only enhances operational efficiency but also unlocks Kubernetes’ full potential for managing complex applications.

Reinforcing Knowledge with Kubernetes Exercises

Learning Kubernetes isn’t just about theoretical knowledge; it’s about applying concepts to solve real-world problems. Kubernetes exercises offer practical scenarios that challenge learners to deploy, scale, and troubleshoot applications.

Examples of valuable Kubernetes exercises include:

Deploying a multi-container application.

Scaling a web application based on traffic spikes.

Implementing role-based access control (RBAC).

Debugging a failed deployment.

These exercises simulate real challenges faced by developers and operations teams, ensuring learners are well-prepared for professional environments.

The Future of Kubernetes

As cloud-native technologies evolve, Kubernetes continues to grow in importance. Organizations increasingly rely on it for flexibility, scalability, and innovation. By mastering the Kubernetes Skill Tree, leveraging the Kubernetes Playground, and performing hands-on Kubernetes exercises, professionals can stay ahead of the curve.

Whether you're an aspiring developer or an experienced IT professional, Kubernetes provides endless opportunities to enhance your skill set and contribute to cutting-edge projects. Begin your journey today and unlock the power of Kubernetes for modern application management.

[megatechcrunch]

The O'Reilly Velocity Conference in San Jose will cover what you need to know to build high-performance, resilient, and secure systems.

Let’s face it, your systems aren't getting any less complex, and the list of skills you need to build and maintain them keeps growing. Modern systems pose a number of thorny challenges: they are inherently complex and span multiple technologies, groups, and sometimes different organizations altogether. Most poignantly, they tend to fail in the most unexpected and spectacular ways. At Velocity this year, we’ve identified three primary areas of focus to help you build and run the systems that power modern businesses: performance, resilience, and security.

Performance

The larger your applications get, the harder it is to understand their performance and troubleshoot problems. This increased complexity in applications and services requires new methods for monitoring and improved observability. Here are some sessions designed to help you tackle performance issues:

Architecting a postmortem: Teams need to perform too. Etsy’s Will Gallego explores postmortems used at large tech companies with real-world examples of failure scenarios and debunks myths regularly attributed to failures.

Think local: Reducing coordination and improving performance when designing around distributed state Learn strategies for avoiding coordination and relying on local knowledge wherever possible and tips for using in-memory state instead of the typical approach of using external data stores.

Moving enterprise Java applications to Kubernetes Heptio��s Kris Nova takes you through the process of migrating a monolithic Java application to running in Kubernetes using a prototype Java application that has been purposely designed to be hard to run cloud natively as an example.

Gaining efficiency with time series in ELK In this case study, learn how NS1 was able to reduce infrastructure, maintenance, and operational costs while simultaneously increasing throughput and visibility of key metrics by leveraging Elasticsearch as a time series database.

Containers: Let's get fancy: Go beyond getting started with containers on AWS with Amazon’s Abby Fuller and get the guidance you need to solve harder issues.

Resilience

Building and running complex systems that are both fast and reliable requires teams and applications that work well—and work well together. The cultural shift is evident: software engineers and system administrators are breaking down walls as they move toward shared responsibilities, thereby quickening the pace of software development and delivery. Here are some sessions to help you build resilient systems to withstand Black Friday sales, scaling, and, well, people:

Crossing the serverless fireswamp: Symphonia’s Mike Roberts leads you on a warts-and-all journey through some of the limitations of a serverless approach and shares a practical set of techniques for dealing with them.

How to monitor your database: Don’t make the same mistakes Baron did! VividCortex CEO Baron Shwartz shares the framework he’s developed over the years for monitoring databases, which breaks monitoring into a holistic approach that’s easy to understand and makes it obvious what kinds of data are useful for what purposes.  

From dandelion to tree: Scaling Slack: In this case study, learn how Slack scaled by rearchitecting its system with lazy loading, a publish/subscribe model, and an edge cache service.

Principia SLOdica: A treatise on the metrology of service level objectives: Google's Jamie Wilkinson offers an overview of SLOs and error budgets, as well as advice on how the implementation of that changes as systems scale, and the tools you’ll need once the alerts themselves no longer tell you what part is broken.

A retrospective on retrospectives: How to be a nonexpert expert in system resilience: Do companies that aren’t unicorns need to become experts in human factors and experts in their software stack in order to engineer reliable systems? Jessica DeVita tells the story of how a team at Microsoft challenged themselves to retrospect their retrospectives and shares what they learned about applying human factors ideas to software development.

Security

Security can no longer be bolted on at the end of projects. Learn how to incorporate security best practices into your system architecture from the ground up into every layer of your applications. Here's a session lineup packed with case studies, techniques, and ideas you’ll want to bring back to your team:

How to establish a high-severity incident management program: Gremlin’s Tammy Butow leads this three-hour tutorial on how to create a high-severity incident management program and measure its success.

Attack trees: Security modeling for Agile teams: Learn a new approach to reviewing systems along with real-life examples to help you prioritize where to focus your security efforts.

You want to step outside? What our fight against phishing taught us and how it can help you: In this case study from Google, explore data from a study on phishing and learn about the effectiveness of phishing prevention tools.

Design for security: Serena Chen shares four strategies that apply design thinking to security problems, pinpointing which practices work and which are detrimental.

Kubernetes security best practices: Google’s Ian Lewis shares the easiest and best ways to improve the security of your Kubernetes clusters.

Wait, there's more...

Some topics require more than 40 minutes to master, which is why we’re offering a number of in-person, expert-led trainings, like Mastering continuously deployed serverless applications and Docker: Up and Running. And if your team needs to be on the same page with new technology, you’ll want to check out the 2-day and 1-day trainings on new tools like Habitat and Nomad, and our crash courses on getting started with Kubernetes and R (the programming language you want to learn to get more from your data).

At Velocity San Jose, we’ll cover the technologies, tools, and issues that you’re tackling on the job every day, or soon will be—like networking Kubernetes, going serverless, improving observability, and managing teams. Between the great networking, fun events, and enlightening keynotes, you’ll find actionable takeaways and intriguing case studies in every session. We look forward to seeing you in San Jose this June. You’ll leave with new ideas, proven best practices, and an expanded network of friends and mentors to help you tackle your next project and advance your career.

Continue reading Building complex systems? We’ve got you covered at Velocity San Jose.

from All - O'Reilly Media https://ift.tt/2GeLQUM

[labexio]

Mastering Docker with LabEx: Your Gateway to Seamless Containerization

Docker has revolutionized how developers and IT professionals manage, deploy, and scale applications. Its containerization technology simplifies workflows, enhances scalability, and ensures consistent environments across development and production. At LabEx, we provide an intuitive platform to learn and practice Docker commands, making the journey from beginner to expert seamless. Here's how LabEx can empower you to master Docker.

What is Docker?

Docker is an open-source platform that automates the deployment of applications inside lightweight, portable containers. These containers bundle everything needed to run an application, including libraries, dependencies, and configurations, ensuring smooth operation across various computing environments.

With Docker, you can:

Eliminate environment inconsistencies.

Accelerate software delivery cycles.

Enhance resource utilization through container isolation.

Why Learn Docker?

Understanding Docker is crucial for anyone working in modern software development or IT operations. Proficiency in Docker opens opportunities in DevOps, cloud computing, and microservices architecture. Key benefits of learning Docker include:

Streamlined Development Workflow: Develop, test, and deploy applications efficiently.

Scalability and Portability: Run your containers across any environment without additional configuration.

Integration with DevOps Tools: Use Docker with CI/CD pipelines for continuous integration and deployment.

LabEx: The Ultimate Online Docker Playground

At LabEx, we provide an interactive Docker Playground that caters to learners of all levels. Whether you're just starting or looking to refine advanced skills, LabEx offers a structured approach with real-world projects and practical exercises.

Features of LabEx Docker Playground

Hands-On Learning: Dive into real-world Docker scenarios with guided tutorials. LabEx's environment allows you to practice essential Docker commands and workflows, such as container creation, image management, and network configuration.

Interactive Labs: Gain practical experience with our Online Docker Playground. From running basic commands to building custom images, every exercise reinforces your understanding and builds your confidence.

Comprehensive Course Material: Our content covers everything from basic Docker commands to advanced topics like container orchestration and integration with Kubernetes.

Project-Based Approach: Work on projects that mimic real-life scenarios, such as deploying microservices, scaling applications, and creating automated workflows.

Community Support: Collaborate and learn with a global community of tech enthusiasts and professionals. Share your progress, ask questions, and exchange insights.

Essential Skills You’ll Learn

By completing the Docker Skill Tree on LabEx, you’ll master key aspects, including:

Container Management: Learn to create, manage, and remove containers effectively.

Image Building: Understand how to build and optimize Docker images for efficiency.

Networking and Security: Configure secure communication between containers.

Volume Management: Persist data across containers using volumes.

Integration with CI/CD Pipelines: Automate deployments for faster delivery.

Why Choose LabEx for Docker Training?

Flexible Learning: Learn at your own pace, with no time constraints.

Practical Focus: Our labs emphasize doing, not just reading.

Cost-Effective: Access high-quality training without breaking the bank.

Real-Time Feedback: Immediate feedback on your exercises ensures you're always improving.

Kickstart Your Docker Journey Today

Mastering Docker opens doors to countless opportunities in DevOps, cloud computing, and application development. With LabEx, you can confidently acquire the skills needed to thrive in this container-driven era. Whether you're a developer, IT professional, or student, our platform ensures a rewarding learning experience.

[labexio]

Master Coding Skills with LabEx: Your Gateway to Tech Excellence

In today’s fast-paced digital age, staying ahead in technology requires mastering a variety of tools and languages. LabEx is the ultimate platform for tech enthusiasts, developers, and learners to sharpen their coding skills and excel in the competitive world of technology. Whether you're an absolute beginner or an experienced developer, LabEx offers a wealth of resources tailored to meet your learning needs.

What Makes LabEx Stand Out?

LabEx is not just another coding platform. It combines hands-on experience, expert guidance, and a variety of interactive features that make learning effective and enjoyable. Here are some unique aspects that set LabEx apart:

Interactive Learning Labs: LabEx offers a range of interactive labs that simulate real-world coding environments. These labs are designed to let learners practice coding in a hands-on manner, helping them bridge the gap between theoretical knowledge and practical application.

Comprehensive Skill Trees: With structured skill trees, learners can progress systematically from foundational concepts to advanced techniques in various programming languages and technologies. Whether you're exploring Linux commands, mastering Python network scans, or practicing Docker commands, LabEx has skill trees for every interest.

Real-World Projects: The platform emphasizes project-based learning, allowing users to apply their knowledge to real-world scenarios. These projects are not only engaging but also help learners build a portfolio to showcase their expertise to potential employers.

Beginner-Friendly Environment: LabEx understands the challenges beginners face. The platform features step-by-step tutorials, easy-to-navigate interfaces, and beginner-friendly challenges to help new learners gain confidence and develop essential coding skills.

Courses and Tools on LabEx

LabEx provides a diverse range of tools and courses tailored for learners with various goals:

Programming Languages: Courses for Python, JavaScript, Rust, and more. These courses cover everything from basic syntax to complex problem-solving.

Cloud Computing: Gain expertise in cloud platforms like Alibaba Cloud with skill labs designed to prepare you for industry-recognized certifications.

DevOps Tools: Explore cutting-edge DevOps technologies like Docker and Kubernetes through hands-on exercises and guided tutorials.

Data Science and AI: Learn data manipulation, visualization, and AI techniques using interactive tools and projects.

Why Choose LabEx?

Learn at Your Own Pace

One of the platform’s biggest advantages is its self-paced learning approach. Whether you have a few minutes or several hours to spare, LabEx allows you to learn according to your schedule without feeling overwhelmed.

Global Community and Support

Join a thriving global community of developers and learners. Participate in discussions, share insights, and gain inspiration from peers worldwide. Additionally, LabEx’s dedicated support team ensures users have access to help whenever needed.

Affordable Learning Opportunities

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LabEx is more than just a learning platform—it's a career-building hub. By completing its courses and certifications, learners can demonstrate their expertise to employers and advance their professional journeys.

Whether you want to build dynamic websites, create robust backend systems, or dive into cloud computing, LabEx equips you with the skills to thrive in the tech world. Start your journey today and transform your passion for technology into a rewarding career with LabEx.

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August 09, 2020 at 10:00PM - The Ultimate DevOps Mastery Bundle (94% discount) Ashraf

The Ultimate DevOps Mastery Bundle (94% discount) Hurry Offer Only Last For HoursSometime. Don't ever forget to share this post on Your Social media to be the first to tell your firends. This is not a fake stuff its real.

Amazon Web Services is the leader in providing cloud computing solutions to corporate environments, thus creating a large demand for certified AWS professionals. This course aims to prepare you for the AWS Certified Solutions Architect Professional exam, offered to advanced developers who have already passed the Associate Certification. Passing this exam will give you an influential certification that will very likely prove quite lucrative.

Access 28 lectures & 1.5 hours of content 24/7

Fully prepare for the AWS Certified Solutions Architect Professional Examination

Cover Virtual Private Cloud (VPC), simple queue service, data pipelines, CloudFront, & more

Discuss AMR service, direct connection, elastic load balancers, & more

Explore theoretical concepts like AWS global infrastructure, AWS cloud pricing principles, AWS Whitepapers, & more

Databases are critical tools for web-based companies, and Redis is one of the fastest growing NoSQL database solutions today, already playing a supporting role in companies like Twitter and Github. Over this tutorial, you’ll learn this open-source data structure server from the absolute basics to more advanced use. Given the current escalation of Redis in the internet world, now’s a great time to get up to speed.

Access 31 lectures & 3 hours of content 24/7

Understand how to install & use Redis

Learn the different data structures, various clients, & different key-value pair commands

Build a functional working task manager w/ NodeJS & Redis

Incorporate Twitter Bootstrap to design the task manager

Amazon Web Services is the best cloud computing solution available, and architects are always in demand to implement and maintain cloud system architecture. These certified professionals make outstanding money to deliver top-notch solutions. In this course, you’ll start your journey towards that goal, covering all the material you’ll need to pass the AWS Solutions Architect – Associate Certification Exam.

Access 30 lectures & 2.5 hours of content 24/7

Prepare for the AWS Solutions Architect – Associate Certification Exam

Explore EC2 instances, S3 bucket, & more

Learn about Amazon’s various databases like RDS, DynamoDB, Elasticache, Redshift, & DMS

Understand how to design a highly available & fault tolerant system

Select appropriate AWS services based on select requirements

Discover the EC2 Dashboard & other related technologies like AMI images, security groups, & auto scaling groups

System administrators are essential contributors to IT departments and are compensated accordingly. This course will teach you all you need to know to administer a Linux/UNIX system, including tips and tricks from professionals on potential pitfalls along your way. Over these 24 hours, you’ll learn everything you need to jump into the lucrative world of Linux system administration.

Access 108 lectures & 24 hours of content 24/7

Dive into the basics of Linux system administration

Understand scripting, package management, kernel & shells & more

Manage system processes, users & software

Learn how to secure your system, manage the network & debug

Discuss administration challenges sourced from professionals in the banking, healthcare & financial industries

Hadoop is perhaps the most important big data framework in existence, used by major data-driven companies around the globe. Hadoop and its associated technologies allow companies to manage huge amounts of data and make business decisions based on analytics surrounding that data. This course will take you from big data zero to hero, teaching you how to build Hadoop solutions that will solve real world problems – and qualify you for many high-paying jobs.

Access 43 lectures & 10 hours of content 24/7

Learn how technologies like Mapreduce apply to clustering problems

Parse a Twitter stream Python, extract keywords w/ Apache Pig, visualize data w/ NodeJS, & more

Set up a Kafka stream w/ Java code for producers & consumers

Explore real-world applications by building a relational schema for a health care data dictionary used by the US Department of Veterans Affairs

Log collections & analytics w/ the Hadoop distributed file system using Apache Flume & Apache HCatalog

The Certified Information Systems Security Professional (CISSP) certification is one of the most widely sought credentials for IT security professionals around the globe. This vendor neutral certificate validates a proven knowledge in technical and managerial skills, and can instantly make your resume jump out. This course will study you up to ace the CISSP certification and turn over a brand new career leaf.

Access 45 lectures & 8.5 hours of content 24/7

Explore confidentiality, integrity & availability concepts

Master privacy protection, data security controls, information & asset classification, & more

Engineer security process & models effectively

Discuss software development security

Dive into security control testing & penetration testing

Data structures and algorithms are the basic building blocks of any software engineering. As with most things, understanding the conceptual cornerstones are vital to becoming the best software engineer you can be. This comprehensive course takes a holistic approach to data structures and algorithms, allowing you to separate yourself from the job-searching pack.

Access 103 lectures & 7.5 hours of content 24/7

Learn the five major categories of algorithms: cryptography, compiler theory, signal processing, data analysis, & graph databases

Understand recursion & its relationship to concurrency & ADTs

Explore the relationship between trees & rotation operations used in balancing

Examine data structure & algorithms through practical examples

Discover Fermat’s theorem, parsing grammars w/ stacks & queues, & related tools like AST based parsers

Docker is an open-source tool that allows developers to wrap their code into small containers or packets, allowing it to then be shipped to and deployed on any other system. It’s an incredible valuable, unique tool that allows software to operate at peak performance anywhere without creating virtual machines. To be direct: companies pay good money for Docker-literate pros. In this course, you’ll learn Docker starting with the absolute basics, and cover it right through to an advanced level.

Access 61 lectures & 8 hours of content 24/7

Get a basic intro to DevOps, containerization, & a background of Docker

Download & install Docker, learn its command line, & understand the container environment

Build a container from scratch & understand how a Docker container operates

Note all the facets of a Docker container, from storage, networking, types, memory, & more

Docker is a transcendent tool for those who transfer, install, and manage software applications on a regular basis. The advent of Kubernetes, however, has somehow made containerizing and automating applications even easier. In this course designed for students of all skill levels, you’ll learn Docker, the world’s leading software containerization platform, and become a master of automating deployment, scaling, and management of containerized applications using Kubernetes.

Access 35 lectures & 4.5 hours of content 24/7

Install Docker & a Kubernetes cluster from scratch

Learn how to run & manage containers effectively

Create Kubernetes pods, deployments, & services

Build Docker images & configure Docker Hub from scratch

Deploy a multi-component software application efficiently & easily

from Active Sales – SharewareOnSale https://ift.tt/2TXmDdk https://ift.tt/eA8V8J via Blogger https://ift.tt/3adeFSo #blogger #bloggingtips #bloggerlife #bloggersgetsocial #ontheblog #writersofinstagram #writingprompt #instapoetry #writerscommunity #writersofig #writersblock #writerlife #writtenword #instawriters #spilledink #wordgasm #creativewriting #poetsofinstagram #blackoutpoetry #poetsofig

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March 16, 2020 at 10:00PM - The Ultimate DevOps Mastery Bundle (91% discount) Ashraf

The Ultimate DevOps Mastery Bundle (91% discount) Hurry Offer Only Last For HoursSometime. Don't ever forget to share this post on Your Social media to be the first to tell your firends. This is not a fake stuff its real.

Amazon Web Services is the leader in providing cloud computing solutions to corporate environments, thus creating a large demand for certified AWS professionals. This course aims to prepare you for the AWS Certified Solutions Architect Professional exam, offered to advanced developers who have already passed the Associate Certification. Passing this exam will give you an influential certification that will very likely prove quite lucrative.

Access 28 lectures & 1.5 hours of content 24/7

Fully prepare for the AWS Certified Solutions Architect Professional Examination

Cover Virtual Private Cloud (VPC), simple queue service, data pipelines, CloudFront, & more

Discuss AMR service, direct connection, elastic load balancers, & more

Explore theoretical concepts like AWS global infrastructure, AWS cloud pricing principles, AWS Whitepapers, & more

Databases are critical tools for web-based companies, and Redis is one of the fastest growing NoSQL database solutions today, already playing a supporting role in companies like Twitter and Github. Over this tutorial, you’ll learn this open-source data structure server from the absolute basics to more advanced use. Given the current escalation of Redis in the internet world, now’s a great time to get up to speed.

Access 31 lectures & 3 hours of content 24/7

Understand how to install & use Redis

Learn the different data structures, various clients, & different key-value pair commands

Build a functional working task manager w/ NodeJS & Redis

Incorporate Twitter Bootstrap to design the task manager

Amazon Web Services is the best cloud computing solution available, and architects are always in demand to implement and maintain cloud system architecture. These certified professionals make outstanding money to deliver top-notch solutions. In this course, you’ll start your journey towards that goal, covering all the material you’ll need to pass the AWS Solutions Architect – Associate Certification Exam.

Access 30 lectures & 2.5 hours of content 24/7

Prepare for the AWS Solutions Architect – Associate Certification Exam

Explore EC2 instances, S3 bucket, & more

Learn about Amazon’s various databases like RDS, DynamoDB, Elasticache, Redshift, & DMS

Understand how to design a highly available & fault tolerant system

Select appropriate AWS services based on select requirements

Discover the EC2 Dashboard & other related technologies like AMI images, security groups, & auto scaling groups

System administrators are essential contributors to IT departments and are compensated accordingly. This course will teach you all you need to know to administer a Linux/UNIX system, including tips and tricks from professionals on potential pitfalls along your way. Over these 24 hours, you’ll learn everything you need to jump into the lucrative world of Linux system administration.

Access 108 lectures & 24 hours of content 24/7

Dive into the basics of Linux system administration

Understand scripting, package management, kernel & shells & more

Manage system processes, users & software

Learn how to secure your system, manage the network & debug

Discuss administration challenges sourced from professionals in the banking, healthcare & financial industries

Hadoop is perhaps the most important big data framework in existence, used by major data-driven companies around the globe. Hadoop and its associated technologies allow companies to manage huge amounts of data and make business decisions based on analytics surrounding that data. This course will take you from big data zero to hero, teaching you how to build Hadoop solutions that will solve real world problems – and qualify you for many high-paying jobs.

Access 43 lectures & 10 hours of content 24/7

Learn how technologies like Mapreduce apply to clustering problems

Parse a Twitter stream Python, extract keywords w/ Apache Pig, visualize data w/ NodeJS, & more

Set up a Kafka stream w/ Java code for producers & consumers

Explore real-world applications by building a relational schema for a health care data dictionary used by the US Department of Veterans Affairs

Log collections & analytics w/ the Hadoop distributed file system using Apache Flume & Apache HCatalog

The Certified Information Systems Security Professional (CISSP) certification is one of the most widely sought credentials for IT security professionals around the globe. This vendor neutral certificate validates a proven knowledge in technical and managerial skills, and can instantly make your resume jump out. This course will study you up to ace the CISSP certification and turn over a brand new career leaf.

Access 45 lectures & 8.5 hours of content 24/7

Explore confidentiality, integrity & availability concepts

Master privacy protection, data security controls, information & asset classification, & more

Engineer security process & models effectively

Discuss software development security

Dive into security control testing & penetration testing

Data structures and algorithms are the basic building blocks of any software engineering. As with most things, understanding the conceptual cornerstones are vital to becoming the best software engineer you can be. This comprehensive course takes a holistic approach to data structures and algorithms, allowing you to separate yourself from the job-searching pack.

Access 103 lectures & 7.5 hours of content 24/7

Learn the five major categories of algorithms: cryptography, compiler theory, signal processing, data analysis, & graph databases

Understand recursion & its relationship to concurrency & ADTs

Explore the relationship between trees & rotation operations used in balancing

Examine data structure & algorithms through practical examples

Discover Fermat’s theorem, parsing grammars w/ stacks & queues, & related tools like AST based parsers

Docker is an open-source tool that allows developers to wrap their code into small containers or packets, allowing it to then be shipped to and deployed on any other system. It’s an incredible valuable, unique tool that allows software to operate at peak performance anywhere without creating virtual machines. To be direct: companies pay good money for Docker-literate pros. In this course, you’ll learn Docker starting with the absolute basics, and cover it right through to an advanced level.

Access 61 lectures & 8 hours of content 24/7

Get a basic intro to DevOps, containerization, & a background of Docker

Download & install Docker, learn its command line, & understand the container environment

Build a container from scratch & understand how a Docker container operates

Note all the facets of a Docker container, from storage, networking, types, memory, & more

Docker is a transcendent tool for those who transfer, install, and manage software applications on a regular basis. The advent of Kubernetes, however, has somehow made containerizing and automating applications even easier. In this course designed for students of all skill levels, you’ll learn Docker, the world’s leading software containerization platform, and become a master of automating deployment, scaling, and management of containerized applications using Kubernetes.

Access 35 lectures & 4.5 hours of content 24/7

Install Docker & a Kubernetes cluster from scratch

Learn how to run & manage containers effectively

Create Kubernetes pods, deployments, & services

Build Docker images & configure Docker Hub from scratch

Deploy a multi-component software application efficiently & easily

from Active Sales – SharewareOnSale https://ift.tt/38VVeLt https://ift.tt/eA8V8J via Blogger https://ift.tt/2TZlzEl #blogger #bloggingtips #bloggerlife #bloggersgetsocial #ontheblog #writersofinstagram #writingprompt #instapoetry #writerscommunity #writersofig #writersblock #writerlife #writtenword #instawriters #spilledink #wordgasm #creativewriting #poetsofinstagram #blackoutpoetry #poetsofig