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Welcome to April’s post announcing new training and certification updates — helping equip you and your teams with the skills to work with AWS services and solutions. This month, we launched 19 new digital training products on AWS Skill Builder, including two new AWS Digital Classroom courses (Digital Classroom – Developing Generative AI Applications on AWS and Digital Classroom – Security Engineering on AWS), nine new digital courses, two new AWS Partner courses (both include an Accreditation Badge to be awarded upon successful completion of the final assessment), and localized versions (Japanese, Korean, Simplified Chinese) of Exam Prep: AWS Certified Advanced Networking – Specialty. Missed our March course update? Check it out here. AWS Digital Classroom AWS Digital Classroom courses combine the depth of live classroom training with the convenience of digital learning. They provide comprehensive knowledge and skills enablement through recordings of expert instructors, demonstrations, hands-on labs, knowledge checks, and assessments. Enjoy flexibility in time, location, and pace, along with the ability to pause, rewind, and revisit content. AWS Digital Classroom is available as part of AWS Skill Builder Team subscription and AWS Skill Builder Individual annual subscription. This month we launched the following new courses: Digital Classroom – Developing Generative AI Applications on AWS Digital Classroom – Security Engineering on AWS AWS Certification exam preparation and updates Exam Prep Standard and Enhanced Courses for AWS Certified Advanced Networking – Specialty (ANS-C01) are now available in Japanese, Korean and Simplified Chinese (English is already available). The Standard version is available to anyone with an AWS Skill Builder account. Enhanced versions include additional prep materials such as hands-on exercises, flashcards, and additional exam-style questions, and are available with an AWS Skill Builder subscription. Free digital courses on AWS Skill Builder The following digital courses on AWS Skill Builder are free to all learners, along with 600+ free digital courses and learning plans. Fundamental Amazon Connect Customer Profiles Fundamentals Amazon Connect Instance Fundamentals Amazon Connect Chat and Messaging Fundamentals AWS for RISE with SAP Introduction Modernizing SAP Workloads on AWS Amazon Q Introduction Amazon Q Business Getting Started Intermediate Migration Evaluator – Gather Insights to Deliver a Migration Business Case Architecting SAP on AWS For AWS Partners Two new digital courses and badges are now available for AWS Partners. Upon successful completion of the final assessment for each AWS Partner: Modernizing SAP Workloads on AWS (Technical) and AWS Partner: Architecting SAP Workloads on AWS (Technical), you will be awarded a Specialized Learner Badge. Fundamental AWS Partner: Modernizing SAP Workloads on AWS (Technical) Intermediate AWS Partner: Architecting SAP Workloads on AWS (Technical) Digital Badges AWS Partner: Modernizing SAP (Specialized) AWS Partner: Architecting SAP (Specialized) View the full article

 Last week, we hosted Michael Tapia, Chief Technology Director at Clint ISD in Texas, and Kobe Brummet, Cybersecurity Technician at Hawkins School District in Tennessee, for a live webinar. Michael and Kobe volunteered to share with other K-12 tech pros how important cybersecurity and safety monitoring are for Google Workspace, Microsoft 365, and […] The post Cloud Monitor Automation Improves K-12 Cybersecurity Training & Awareness appeared first on ManagedMethods. The post Cloud Monitor Automation Improves K-12 Cybersecurity Training & Awareness appeared first on Security Boulevard. View the full article

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Cloud computing is the delivery of computing services, such as servers, storage, databases, networking, software, analytics, and intelligence, over the internet. It enables faster innovation, efficient resource usage, and economies of scale. It also reduces the need for hardware maintenance, software updates, and security patches. The demand for cloud skills is high and growing as more and more organizations adopt cloud-based solutions for their business needs. According to the latest forecast from Gartner, worldwide end-user spending on public cloud services is expected to reach $679 billion in 2024, a 20% growth from 2023. The report also predicts that by 2027, more than 70% of enterprises will use industry cloud platforms to accelerate their business initiatives. If you want to become a cloud expert and advance your career as a DevOps engineer, you need to learn the fundamentals, choose a platform, get hands-on experience, gain certifications, and continue on-the-job learning. In this article, we will guide you through these steps and help you achieve your cloud computing goals. Why cloud computing?Before diving into the details of how to learn cloud computing, let's first understand why cloud computing is so important for DevOps engineers. Cloud computing offers several advantages over traditional on-premises computing. Below are some of them: Cost-efficiency: Cloud computing eliminates the upfront cost of buying and maintaining hardware and software, as well as the operational cost of power, cooling, and security. You only pay for what you use, and you can scale up or down as needed.Scalability: It allows you to access unlimited resources on demand without worrying about capacity planning or provisioning. You can easily handle spikes in traffic, data, or workload and scale back when not needed.Performance: Cloud computing provides high-performance computing resources that are optimized for different types of workloads, such as compute-intensive, memory-intensive, or network-intensive. You can also leverage the global network of data centers and edge locations to reduce latency and improve user experience.Reliability: It ensures the availability and durability of your data and applications by replicating them across multiple servers and regions. You can also use backup, recovery, and failover features to prevent data loss and downtime.Security: Cloud computing offers built-in security measures, such as encryption, firewalls, identity and access management, and compliance standards. You can also use additional tools and services to enhance your security posture and protect your data and applications.Innovation: It enables you to experiment and innovate faster by providing access to the latest technologies and services. For instance, artificial intelligence, machine learning, big data, IoT, and serverless computing. You can also integrate and orchestrate different services to create new solutions and value propositions.As a DevOps engineer, you can leverage these benefits to deliver better products and services faster and more efficiently. Learn about Cloud ComputingTo learn cloud computing, you need to understand the basic concepts and principles that underpin it. You also need to familiarize yourself with the different types of cloud computing and the major cloud platforms that offer them. Types of Cloud ComputingThere are three main types of cloud computing, based on the level of abstraction and control they provide: Infrastructure as a Service (IaaS): This is the most basic type of cloud computing, where you rent servers, storage, and networking resources from a cloud provider. It gives you full control over the resources’ configuration and management. Examples of IaaS providers include Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP).Platform as a Service (PaaS): This is a type of cloud computing where you use a cloud provider's platform to develop, deploy, and run your applications without worrying about the underlying infrastructure. The cloud provider manages the servers, storage, and networking resources, as well as the operating system, middleware, and runtime environment. You only focus on the code and the logic of your applications. Examples of PaaS providers are AWS Elastic Beanstalk, Azure App Service, and Google App Engine.Software as a Service (SaaS): This is a type of cloud computing where you use a cloud provider's software applications over the internet without installing or maintaining them on your own devices. The cloud provider manages the infrastructure, platform, and application, and you only access them through a web browser or a mobile app. Examples of SaaS providers are Gmail, Salesforce, and Zoom.Check our article on “What is Cloud Computing” to learn more about cloud computing services, cloud computing deployment model, its advantages and limitations. Cloud PlatformsThere are many cloud platforms that offer different types of cloud computing services, but the top three that dominate the market are AWS, Azure, and GCP. These platforms have their own strengths and weaknesses, and you need to compare and contrast them to decide which one suits your needs and preferences. Below are some of the factors that you need to consider when choosing a cloud platform: Features and Services: Each cloud platform offers a variety of features and services, covering different domains and use cases, such as compute, storage, database, networking, security, analytics, AI, IoT, etc. You need to evaluate the quality, quantity, and diversity of the features and services that each platform offers and how they match your requirements and expectations.Pricing and Billing: The pricing and billing model are based on different parameters, such as resource type, usage, duration, region, etc. You need to understand the pricing and billing structure of each platform and how it affects your budget and spending. You also need to compare the cost-effectiveness and value proposition of each platform and how they align with your goals and outcomes.Documentation and Support: Go through their documentation to assess the support resources that each platform offers and how they help you learn and troubleshoot. You also need to consider the availability and responsiveness of the customer service and technical support that each platform provides.These are some of the factors you need to consider when choosing a cloud platform, but there may be others depending on your specific needs and preferences. You also need to recognize any gaps that you may have in your existing knowledge and skills before starting an in-depth learning journey. For example, you may need to brush up on your programming, scripting, or networking fundamentals or learn some new tools or frameworks that are relevant for cloud computing. Choose a Platform to Focus OnOnce you have a general understanding of cloud computing and its types, concepts, and platforms, you need to choose a platform to focus on for your learning. While it is possible to learn multiple cloud platforms, it is advisable to start with one platform initially and gain depth over breadth. This will help you master the core concepts and services of that platform and build confidence and competence in using them. The question then is, which platform should you choose? The answer depends on several factors, such as your personal interest, career goals, project requirements, employer preferences, etc. However, if you are looking for a general recommendation, we suggest picking AWS as your first cloud platform to learn. AWS is the oldest and largest cloud platform in the market, with a global presence and a dominant market share. According to a report by Synergy Research Group, AWS had a 31% share of the cloud infrastructure services market in Q4 2023, followed by Azure with 24% and GCP with 11%. AWS also had the highest annual revenue growth rate of 28% among the top three cloud platforms. AWS offers a comprehensive and diverse range of cloud services, covering almost every domain and use case imaginable, such as compute, storage, database, networking, security, analytics, AI, IoT, etc. It also has a rich and mature ecosystem of partners, customers, and developers who create and share valuable resources and solutions. It has a well-established and reputable certification program, which validates your cloud skills and knowledge and enhances your credibility and employability. Of course, this does not mean that AWS is the best or the only cloud platform to learn. Azure and GCP are also excellent cloud platforms with their own strengths and advantages, such as integration with Microsoft and Google products, respectively. You may also want to learn about other cloud platforms, such as IBM Cloud, Oracle Cloud, or Alibaba Cloud, depending on your specific needs and preferences. The important thing is to choose a platform that aligns with your learning objectives and outcomes and stick with it until you master it. How to Learn Cloud ComputingAfter choosing a cloud platform to focus on, you need to learn how to use it effectively and efficiently. There are many ways to learn cloud computing, but we recommend the following three steps: get hands-on experience with projects, gain cloud certifications, and continue on-the-job learning. Get Hands-On Experience with ProjectsThe best way to learn cloud computing is by doing it. You need to get hands-on experience with the cloud platform and its services by creating and deploying real-world projects. This will help you apply the concepts and principles that you learned and develop the skills and confidence that you need. You can start by following some tutorials or courses that guide you through the basics of the cloud platform and its services and show you how to create and deploy simple applications. However, you should not stop there. You should also create your own projects based on your own ideas and interests, and challenge yourself to use different services and features. Below are examples of projects that you can create and deploy on the cloud platform: Automate the infrastructure deployment of your applications using tools like Terraform, CloudFormation, or ARM templates. This will help you learn how to use infrastructure as code (IaC), which is a key skill for DevOps engineers.Build a full-stack web application using services like EC2, S3, RDS, DynamoDB, Lambda, API Gateway, etc. This will help you learn how to use different types of compute, storage, and database services and how to integrate and orchestrate them.Create a containerized application using services like Docker and orchestrate it using Kubernetes, EKS, AKS, or GKE. This will help you learn how to use containers and orchestration tools essential for microservices architectures and DevOps practices.Develop a serverless application using services like Lambda, Azure Functions, or Cloud Functions. This will help you learn how to use serverless computing, a popular and powerful paradigm for cloud development.Check out the following courses and articles to help you with the projects above: What is Infrastructure-as-Code (IaC)? To understand more about IaCCI/CD Learning Path, to learn more about integrating and orchestrationWhat is Containerization? To learn more about containerization You can use our Cloud playground, which gives you access to AWS, Azure, and Google Cloud in a controlled environment. They allow you to learn without fear of failure. Gain Cloud CertificationsCertifications validate technical proficiency and signal commitment. Cloud certifications can help you fill gaps in your learning and prepare you for real-world scenarios and challenges. There are many cloud certifications available, but we recommend you check our Cloud Learning Path for a comprehensive guide on the cloud certifications we offer. Whether you are interested in AWS, Azure, or GCP, we have a curated list of courses and resources to help you get started and advance your career in cloud computing. Continue Learning on the JobWith technology evolving relentlessly, cloud computing is never fully learned. Continuous learning is an absolute must. Participate in available company training programs or conferences to stay up to date on the latest tools and best practices. Seek opportunities to assist coworkers and learn new services through collaborations. Consider specializing further in emerging services by taking on side projects leveraging AI/ML, 5G, edge computing, or other disruptive innovations. ConclusionCloud computing is an invaluable skill for DevOps engineers, who need to develop, deploy, and operate applications in a fast and reliable manner. With focus and perseverance, you will establish the coveted experience and skillset to become a highly valued cloud expert. If you want to take your career to the next level, sign up on KodeKloud for free now and learn how to use cloud computing on the go. You can also check out our Cloud Learning Path to get started with cloud computing. Cloud Learning Path | KodekloudChart your Cloud learning journey with our expert-designed learning path and study roadmap.CloudView the full article

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Learning the different AWS services and how they work can be a daunting task, especially if you’re new to the cloud. Last year, we wrote about how you can use AWS Solution Focused Immersion Days (SFID) to accelerate your team’s understanding of different aspects of AWS. There are many resources available to help you build your knowledge and skills, such as AWS Whitepapers and 600+ free digital learning courses and resources on AWS Skill Builder, our online learning center. Today, we want to introduce you to the resources that power SFIDs – AWS Workshops. AWS Workshops are free, self-guided tutorial experiences that give you hands-on experience with AWS services. Through technical step-by-step modules, created by teams at Amazon Web Services (AWS), any level of learner can build an understanding of AWS Cloud concepts along with practical skills and techniques. If you’re new to cloud, have no fear: there is plenty here for you too! What can I learn via an AWS Workshop? We have 1000+ AWS Workshops available today, with more being added and updated each week, across a range of topics – including generative artificial intelligence (AI), machine learning (ML), big data and analytics, serverless, databases, security, and more. If you’re looking for service-specific, domain-specific, or use-case focused workshops, we’ve got you covered. Check out “How to use IAM Policies” (service-specific) or “Use Generative AI to build a DevSecOps Chatbot” (use-case specific). Each AWS Workshop is based on common use-cases and customer and partner feedback. You can find a workshop by using the search toolbar at the top of the AWS Workshops homepage or by directly searching service names or use cases. What is the experience like? Your workshop is structured with step-by-step instructions, from how to set up your AWS environment in preparation for the workshop, to hands-on modules that cover sub-domains and use-cases for the workshop at hand. The learning is all self-paced, allowing you to gain hands-on experience in the AWS Management Console, CLI, and SDK, with the ability to stop and start as often as needed. The artifacts from these workshops can be used in your own AWS account and can even help set the foundation for future AWS projects and initiatives. Workshops vary by complexity and estimated time to completion, but there is no time limit. Short workshops take as little as one hour to complete, and deep dive workshops that walk through multiple services and concepts may take as long as six hours to complete. How to get started with AWS Workshops Step 1: Create an AWS account If you’re interested in learning using AWS Workshops, the first step is to create your own AWS account. When you open a new AWS account, take advantage of a few offers, including free trials for certain services, which are detailed in the AWS Free Tier. Please note that some workshops may incur small charges in your AWS account, depending on the resources that are provisioned, but many workshops deploy resources that are partially, if not entirely, covered under the AWS Free Tier. Please keep in mind that if you do not terminate resources from the workshops after completing them, you may incur unexpected charges in your AWS Account. We’ll cover how to clean up the resources provisioned in your AWS account by in Step 5. Step 2: Select your workshop Once you have an AWS account, go to AWS Workshops to start by searching for the topic you’d like to learn more about. For example, if you search “generative AI”, you should see AWS Workshops that leverage AWS generative AI services. See image 1 below. Workshops are categorized by technology domains and AWS services. Be sure to check that your topic is in either the “Categories” or “Tags” label. Sometimes, the search engine will identify workshops that minimally utilize the topic that you searched, so these workshops may not be a good fit based on what you’re interested in learning. As you’re reviewing the search results, keep in mind two things: 1/ the level of the workshop and 2/ the estimated time for completion. Each workshop is assigned a complexity level and there are four levels: 100, 200, 300, and 400. Level 100 are introductory-level focusing on a general overview of AWS services and features. Level 200 are intermediate-level and assume that the learner has an introductory level of knowledge on the topic and is ready to get deeper into the details of AWS services. Level 300 are advanced and dive deep into the selected topic, assuming the learner has familiarity with the topic but may not have any experience implementing a solution. Level 400 are expert-level and focus on advanced architectures and implementations. This level is typically best suited for a learner with experience implementing similar solutions. Each workshop has an estimated time for completion, assuming the learner will understand all instructions and can complete tasks accordingly. However, based on your level of AWS and technology-specific experience, this time could vary, and you are free to take as much time as you need to complete the workshop. Once you’ve chosen a workshop, click the “Get Started” button. Step 3: Set up the AWS Environment AWS Workshops can be run as part of an AWS event led by AWS Solutions Architects (such as an Immersion Day) or run in your own AWS account. In today’s blog, we’re focused on how to run the AWS Workshops in your own AWS account. There are tabs on the left side of the AWS Workshop interface that allow you to navigate through different parts of the workshop. Consistent tabs include: “Setup”, “How to Start”, and “Start Building” (or something similar). See image 2 below. To run the workshop environment in your own AWS account, you’ll select the “Self-Paced”, “Use Your Own AWS Account”, and “Customer-owned Account Setup” (or a similarly named tab). This step typically entails deploying specific per-requisite AWS resources that are necessary to complete the rest of the workshop. Don’t worry about having to keep track of resources that you create. At the end of each AWS Workshop, it will walk you through cleaning up all resources that you created. Step 4: Complete modules Each AWS Workshop may have one or more modules, each addressing a specific topic in the workshop. Some modules can be completed independent of one another; others must be completed in sequence. We recommend always completing all modules, in order, for a given AWS Workshop. Completing each module in sequence ensures that not only are all necessary resources created for subsequent modules, but also that you understand the broader concepts behind the workshop. Please note that some workshop modules may ask you to download and upload files. These files are created and secured by AWS workshop teams. Step 5: Cleanup At the end of each AWS Workshop, we want to ensure all provisioned resources are terminated so we can return your AWS account to its original configuration. In every AWS Workshop, there is a tab labelled “Cleanup” or “Clean Up Resources”. Be sure to follow the outlined steps to terminate all resources created throughout the AWS Workshop. This ensures no unexpected AWS charges or security risks present themselves in your AWS account. If you are looking for a more guided approach to AWS Workshops, please read about AWS Solutions Focused Immersion Days. We hope you get a chance to leverage AWS Workshops to learn more about how to use AWS and wish you the best of luck in your AWS journey. Additional resources In addition to AWS Workshops, you can get hands-on learning with AWS Skill Builder subscriptions for access to 195+ AWS Builder Labs, enhanced exam prep resources, AWS Cloud Quest, AWS Industry Quest, AWS Jam Journeys, and more. There’s something for every cloud learner, from brand new builder to experienced professional. Use the 7-day free trial of AWS Skill Builder Individual subscription* to access it all free. *terms and conditions apply View the full article

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Today’s options for best AI courses offer a wide variety of hands-on experience with generative AI, machine learning and AI algorithms.View the full article

Welcome to March’s post announcing new training and certification updates — helping equip you and your teams with the skills to work with AWS services and solutions. This month we launched eight new digital training products on AWS Skill Builder, including four new AWS Builder Labs and a free learning plan called, Generative AI Developer Kit. We also have three new, and one updated AWS Classroom Training courses—two of which have AWS Partner versions—including Developing Generative AI Applications on AWS. A reminder: registration is now open for the new AWS Certified Data Engineer – Associate exam. You can begin preparing with curated exam prep resources, created by the experts at AWS, on AWS Skill Builder. Missed our February course update? Check it out here. New AWS Skill Builder subscription features AWS Skill Builder subscriptions are available globally, including Mainland China as of this month, and unlock enhanced AWS Certification exam prep and hands-on AWS Cloud training including 1,000+ interactive learning and lab experiences like AWS Cloud Quest, AWS Industry Quest, AWS Builder Labs, and AWS Jam challenges. Select plans offer access to AWS Digital Classroom courses to dive deep with expert instruction. Try a 7-day free trail of Individual subscription. *terms and conditions apply AWS Builder Labs Migrate On-Premises Servers to AWS Using Application Migration Service (MGN) (60 min.) is an intermediate-level lab providing you an opportunity to learn how to use AWS Application Migration Service to migrate an existing workload to AWS. Migrate On-premises Databases to AWS Using AWS Database Migration Service (DMS) (75 min.) is an intermediate-level lab providing you an opportunity to learn how to use AWS Database Migration Service to migrate an existing database to Amazon Aurora. Data Modeling for Amazon Neptune (60 min.) is an intermediate-level lab providing you an opportunity to explore the process of modeling data with Amazon Neptune to meet prescribed use cases. Analyzing CloudWatch Logs with Kinesis Data Streams and Kinesis Data Analytics(4 hr.) is an advanced-level, challenge-based lab allowing you to learn how to use Amazon CloudWatch to collect Amazon Elastic Compute Cloud (EC2) system logs and use Amazon Kinesis to analyze the collected data. AWS Certification exam preparation and updates Now available: AWS Certified Data Engineer – Associate Registration is now open for the AWS Certified Data Engineer – Associate. Showcase your knowledge and skills in core data-related AWS services, implementing data pipelines, and providing high-quality data for business insights. Gain confidence going into exam day with trusted exam prep on AWS Skill Builder, including an Official Pretest, available now in all exam languages. Free digital courses on AWS Skill Builder The following digital courses on AWS Skill Builder are free to all learners, along with 600+ free digital courses and learning plans. Digital learning plan Generative AI Developer Kit (includes labs) (16h 30 min.) is a collection of curated courses, labs, and challenges to develop the skills needed to build generative AI applications. Software developers interested in leveraging large language models without fine-tuning will benefit from this collection. You’ll receive an overview of generative AI, learn to plan a generative AI project, get started with Amazon CodeWhisperer and Amazon Bedrock, learn the foundations of prompt engineering, and discover the architecture patterns to build generative AI applications using Amazon Bedrock and Langchain. Digital courses Decarbonization with AWS Introduction (15 min.) is a fundamental-level course that teaches you about AWS Customer Carbon Footprint Tool and other resources that can be used to advance your sustainability goals. You’ll learn how businesses use the AWS Customer Carbon Footprint Tool, how it helps you reduce your carbon footprint and achieve decarbonization goals with AWS, and considerations for using the tool for a variety of optimal usage and cost savings considerations. Amazon Redshift Introduction (15 min.) is a fundamental-level course that provides an introduction to Amazon Redshift, including its common uses and benefits. AWS Mainframe Modernization – Using Replatform Tools with Amazon AppStream (60 min.) is an intermediate-level course teaching the setup and usage of Micro Focus tools from OpenText, such as Enterprise Analyzer and Enterprise Developer, with Amazon AppStream 2.0. AWS Classroom Training Designing and Implementing Storage on AWS is a three-day, intermediate-level course teaching you to select, design, implement, and optimize secure storage solutions to save on time and cost, improve performance and scale, and accelerate innovation. You’ll explore AWS storage services and solutions for storing, accessing, and protecting your data. An expert AWS instructor will help you understand where, how, and when to take advantage of different storage services. Learn how to best evaluate the appropriate AWS storage service options to meet your use case and business requirements. Build Modern Applications with AWS NoSQL Databases is a one-day, intermediate-level course to help you understand how to build applications that involve complex data characteristics and millisecond performance requirements from your databases. You’ll learn to use purpose-built databases to build typical modern applications with diverse access patterns and real-time scaling needs. AnAWS Partner version is also available. Running Containers on Amazon Elastic Kubernetes Service (Amazon EKS) is an updated, three-day, intermediate-level course from an expert AWS instructor that teaches container management and orchestration for Kubernetes using Amazon EKS. You’ll build an Amazon EKS cluster, configure the environment, deploy the cluster, and add applications to your cluster. Learn how to also manage container images using Amazon Elastic Container Registry (ECR) and automate application deployment. Developing Generative AI Applications on AWS is a two-day, advanced-level course that teaches you the basics, benefits, and associated terminology of generative AI. An expert AWS instructor will guide you through planning a generative AI project and the foundations of prompt engineering to develop generative AI applications with AWS services. By the end of the course, you’ll have the skills needed to build applications that can generate and summarize text, answer questions, and interact with users using a chatbot interface. An AWS Partner version is also available. View the full article

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This article introduces six top-notch, free data science resources ideal for aspiring data analysts, data scientists, or anyone aiming to enhance their analytical skills.View the full article

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Research shows that developers complete tasks 55% faster at higher quality when using GitHub Copilot, helping businesses accelerate the pace of software development and deliver more value to their customers. We understand that adopting new technologies in your business involves thorough evaluation and gaining cross functional alignment. To jump start your organization’s entry into the AI era, we’ve partnered with engineering leaders at some of the most influential companies in the world to create a new expert-guided GitHub Learning Pathway. This prescriptive content will help organizational leaders understand: What can your business achieve using GitHub Copilot? How does GitHub Copilot handle data? What are the best practices for creating an AI governance policy? How can my team successfully roll out GitHub Copilot to our developers? Along the way, you’ll also get tips and insights from engineering leaders at ASOS, Lyft, Cisco, CARIAD (a Volkswagen Group company), and more who have used GitHub Copilot to increase operational efficiency, deliver innovative products faster, and improve developer happiness! Start your GitHub Copilot Learning Pathway Select your GitHub Learning Pathway NEW! AI-powered development with GitHub Copilot From measuring the potential impact of GitHub Copilot on your business to understanding the essential elements of a GitHub Copilot rollout, we’ll walk you through everything you need to find success with integrating AI into your businesses’ software development lifecycle. CI/CD with GitHub Actions From building your first CI/CD workflow with GitHub Actions to enterprise-scale automation, you’ll learn how teams at leading organizations unlock productivity, reduce toil, and boost developer happiness. Application Security with GitHub Advanced Security Protect your codebase without blocking developer productivity with GitHub Advanced Security. You’ll learn how to get started in just a few clicks and move on to customizing GitHub Advanced Security to meet your organization’s unique needs. Administration and Governance with GitHub Enterprise Configure GitHub Enterprise Cloud to prevent downstream maintenance burdens while promoting innersource, collaboration, and efficient organizational structures, no matter the size and scale of your organization. Learning Pathways are organized into three modules: Essentials modules introduce key concepts and build a solid foundation of understanding. Intermediate modules expand beyond the basics and detail best practices for success. Advanced modules offer a starting point for building deep expertise in your use of GitHub. We are hard at work developing the next GitHub Copilot Learning Pathway module, which will include a deep dive into the nitty-gritty of working alongside your new AI pair programmer. We’ll cover best practices for prompt engineering and using GitHub Copilot to write tests and refactor code, among other topics. Are you ready to take your GitHub skills to the next level? Get started with GitHub Learning Pathways today.

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We’re back with the February course launches and certification updates from AWS Training and Certification to equip you and your teams with the skills to work with AWS services and solutions. This month we launched 22 new digital training products on AWS Skill Builder, including new AWS Digital Classroom courses for annual subscribers, five new solution assignments to build generative AI skills via AWS Cloud Quest, and new prep courses for the AWS Certified Data Engineer – Associate exam. Don’t forget to try the 7-day free trial of AWS Skill Builder Individual subscription* for access to our most immersive, hands-on trainings, including 195+ AWS Builder Labs, enhanced exam prep resources, AWS Cloud Quest, AWS Industry Quest, AWS Jam Journeys, and more. There’s something for every cloud learner, from brand new builder to experienced professional. *terms and conditions apply New Skill Builder subscription features The following new AWS Skill Builder features require an Individual or Team subscription. Individuals can try for free with a 7-day free trial. AWS Digital Classroom Get access to a catalog of AWS Classroom Training courses that have the flexibility of digital training with the depth of classroom training. Available with an annual subscription for individuals or teams, learn more about AWS Digital Classroom and subscribe today — and for a limited time, receive $150 off your annual Individual plan. AWS Cloud Quest AWS Cloud Quest has added five solution assignments to build practical generative AI skills within Machine Learning, Serverless Developer, Solutions Architect, and Security roles. Learn to generate images from text descriptions, create chatbots powered by large language models, use generative AI to build cloud infrastructure, and monitor compute resources using AI-generated code. These hands-on assignments will teach you how to leverage services like Amazon CodeWhisperer, Amazon Lex V2, and Amazon SageMaker for applied generative AI and automation. AWS Certification exam prep and updates Three AWS Certifications are retiring AWS Certification will retire three specialty certifications and their corresponding AWS Skill Builder Exam Prep trainings in April 2024: AWS Certified Data Analytics – Specialty on April 9, 2024; and AWS Certified Database – Specialty and AWS Certified: SAP on AWS – Specialty on April 30, 2024. If you plan to earn these credentials, be sure to take your exam prior to their retirement dates. Exam prep resources Exam Prep Standard Course: AWS Certified Data Engineer – Associate (DEA-C01 – English) (6 hours) is a free digital course designed to prepare you for the AWS Certified Data Engineer – Associate (DEA-C01) exam. During this course you’ll follow a step-by-step plan to prepare, gauging your understanding of topics and concepts from each task statement grouped by exam domains. Become an AWS Skill Builder subscriber and access an enhanced subscription-only 13-hour Exam Prep Enhanced Course: AWS Certified Data Engineer – Associate (DEA-C01 – English) that includes hands-on exercises and exam-style questions to reinforce your knowledge and identify learning gaps. You’ll explore learning strategies to identify incorrect responses to help you determine your readiness to take the exam with the AWS Certification Official Pretest. Exam Prep Official Pretest: AWS Certified Data Engineer – Associate (DEA-C01) (2 hours) helps you prepare for the AWS Certified Data Engineer – Associate (DEA-C01) exam. Gain confidence going into exam day with an official, full-length pretest created by the experts at AWS. Take an AWS Certification Official Pretest to focus your preparation where you need it most, and assess your exam readiness. Exam Prep Official Pretest: AWS Certified Cloud Practitioner (CLF-C02) is now available in French, Italian, German, Spanish-Spain, Traditional Chinese and Indonesian (English, Japanese, Korean, Portuguese, Simplified Chinese, and Spanish LatAm already available). Free digital courses on AWS Skill Builder The following digital courses are free within AWS Skill Builder, along with 600+ other digital courses, learning plans, and resources. Fundamental courses AWS Skill Builder Learner Guide (15 min.) teaches new users how to navigate through AWS Skill Builder and what content types are available to learners. AWS for SAP Fundamentals (45 min.) teaches you the essentials of SAP architecture and provides an understanding of various AWS adoption scenarios for SAP, licensing options, and the AWS support frameworks specific to SAP workloads on AWS. You’ll acquire a foundational knowledge of the basics involved in operating SAP in the AWS Cloud. AWS Mainframe Modernization Refactor with AWS Blu Age Getting Started (60 min.) teaches you the functionality, technical architecture, key use cases and cost structure of AWS Mainframe Modernization Refactor with AWS Blu Age. AWS Mainframe Modernization Replatform with Micro Focus Getting Started (60 min.) teaches you the functionality, technical architecture, key use cases and cost structure of AWS Replatform with Micro Focus. Intermediate courses Containerize and Run .NET Applications on Amazon EKS Windows Pods (2 hours) teaches you Kubernetes, an open-source system for automating deployment, scaling, and managing containerized applications. It also covers Amazon Elastic Kubernetes Service (Amazon EKS), a managed service to run a Kubernetes workload on AWS without the need to install, operate, and maintain your own Kubernetes cluster. Amazon QuickSight Advanced Business Intelligence Authoring (Part 1) (90 min.) teaches you how to author business intelligence experiences using Amazon QuickSight. In this first course of a two-part series, you’ll dive into advanced authoring capabilities in QuickSight, gain expertise in data connectivity, data preparation, and customized highly formatted dashboard building. Amazon QuickSight Advanced Business Intelligence Authoring (Part 2) (90 min.) teaches you how to author business intelligence experiences using Amazon QuickSight. In this second course of a two-part series, you’ll gain practical knowledge on building interactivity, including filters, actions, navigation, and sheets, QuickSight security, QuickSight Q, forecasting, paginated reporting, and data export. AWS Mainframe Modernization – Using MicroFocus Managed Runtime Environment (60 min.) teaches you to build an AWS Replatform with Micro Focus environment using an AWS CloudFormation template to deploy and test an application. AWS Mainframe Modernization – Using Refactor Tools (60 min.) teaches you to setup AWS Blu Insights and use code import and transformation features to refactor Mainframe application code. Amazon Timestream – Data Modeling Techniques (60 min.) teaches you about the significance of efficiently modeling data for your time series workloads using Amazon Timestream. You’ll be introduced to various Timestream features and how to use them for different scenarios. At the end of this course you’ll be able to implement high-performance data models for Amazon Timestream. AWS Training for Partners AWS Partner: SAP on AWS (Technical) (3.5 hours) teaches you key architecture patterns for SAP on AWS, with emphasis on designing, migrating, implementing, and managing SAP solutions. You’ll also gain an understanding of SAP HANA on AWS, and high availability and disaster recovery scenarios. Successfully complete the final assessment and you’ll earn a Credly Accreditation Badge. View the full article

Amazon Q is a generative-AI powered assistant that helps customers answer questions, provide summaries, generate content, and complete tasks based on data in their company repository. It also exists as a learning tool for AWS users who want to ask questions about services and best practices in the cloud. Amazon Q is integrated into AWS tools to assist readers and builders in learning services quickly, troubleshooting in the AWS Management Console, and much more, essentially working as an “AWS assistant” as users build. To use Amazon Q, you just need to sign into your AWS account and enter a question into the text bar in the Amazon Q panel. Amazon Q then generates a response to the question including a section with sources, that link to its references. After you receive a response, you can optionally leave feedback by using the thumbs-up and thumbs-down icons to strengthen the capabilities of the tool. In this blog, we’ll share how you, whether you’re technical or not, can use Amazon Q to accelerate and streamline your journey of learning how to build with AWS services. Use Amazon Q for AWS Documentation assistant Often, the first step in learning a new service is through that service’s front page and its documentation. These resources provide you with a foundation before you progress into hands on learning through building. As your cloud journey continues, documentation becomes an important tool in troubleshooting and customizing your workload. It’s no surprise though that many readers find AWS whitepapers and documentation long and complicated. As you read through a page you may run into an unknown technical term or an unfamiliar service feature. Rather than gear switching between multiple documents, you can now use the Amazon Q assistant to ask questions and get answers in real time! Just look for the Q icon on the right-hand side of any public AWS whitepaper, service front page, or documentation guide. You can see in the below example, while reading about best practices for snapshotting database clusters in Amazon Aurora, we want to understand if it is possible to automate the process. By asking Q, “Can I run automated snapshots on Amazon Aurora?” we receive concise details as well as link to the reference pages to learn more. I can ask quick clarifying questions and also receive targeted resources for further reading. Use the Amazon Q assistant to ask questions and get answers in real time! Just look for the Q icon on the right-hand side of any public AWS whitepaper, service front page, or documentation guide. As mentioned previously, Amazon Q is also available on each AWS service page. Below you can see we are on the Amazon Simple Storage Service (S3) service page and open up Amazon Q icon, which can also be found bottom right of the page. You are able to choose one of the prompts to get started or start asking Amazon Q service-specific questions in order to learn more about S3. By leveraging the Amazon Q chatbot to ask clarifying questions in real time, you no longer have to leave the page to dive deeper, providing a mechanism to help you remain focused. AWS Console assistant Your next step after reading documentation is likely to start building in the AWS Console. We often see that learners are kinesthetic and like to build as a way to better digest content, whether it’s through workshops, independent experimentation, or a guided in-person session. In these situations, there can often be more gear-shifting and/or getting lost in reading when a question arises mid-build. Now, you can find Amazon Q AWS expert in the console and ask your questions through the build process. Currently, Amazon Q AWS expert is in “preview” release and the use of expert assistant for AWS is available for no additional charges during the preview. This allows you to chat with the AWS expert Amazon Q assistant in the AWS Management Console, documentation, and AWS website. You can check out the additional details. You can find Amazon Q AWS expert in the AWS Management Console and ask your questions through the build process. After logging into the AWS Console, regardless of the service, you’ll find the Amazon Q icon on the right-hand side. The chatbot here functions in the same way as described above. Just type out your questions and Amazon Q will generate an answer with sources cited. In the console, learners have the opportunity to ask Amazon Q questions about AWS services, best practices, and even software development with the AWS SDKs and AWS CLI. Amazon Q in the console can generate short scripts or code snippets to help you get started using the AWS SDKs and AWS CLI. The following are example questions that demonstrate how Amazon Q can help you build on AWS and learn quickly: What’s the maximum runtime for an Amazon Lambda function? When should I put my resources in an Amazon VPC? What’s the best container service to use to run my workload if I need to keep my costs low? How do I list my Amazon S3 buckets? How do I create and host a website on AWS? In the console, you can ask Amazon Q questions about AWS services, best practices, and even software development with the AWS SDKs and AWS CLI. Amazon Q in the console can generate short scripts or code snippets to help you get started using the AWS SDKs and AWS CLI. Conclusion Whether you have just started reading about the cloud, or have been using AWS for a decade, keeping pace with the advances in cloud is a continuous learning journey. The more streamlined the process to ask clarifying questions during reading or building, the more efficient this journey becomes. In service of this, Amazon Q can help cut down the time it takes to find the right documentation and get your questions answered. If you have an AWS account, you can start using Amazon Q on any public documentation or in the AWS Console today. AWS sees security as top priority and have integrated responsible AI into the development of services like Amazon Q. We adhere to the AWS Responsible AI policy and we expect users to follow the same code of conduct. View the full article

Kubernetes and Docker are essential technologies for anyone working in DevOps or cloud-native application development. Mastering these technologies can greatly benefit your career growth in DevOps. This article provides an overview of Kubernetes and Docker, why they are important to learn, and resources to get started. Key Takeaways Learning Docker and Kubernetes are essential for DevOps and cloud-native application development.Docker pioneered software containerization, and Kubernetes improved containerized application deployment and management.Consistent Environments, Agile Deployments, Health Monitoring, and Zero Downtime Updates are major advantages of Docker-Kubernetes integration.Why developers and DevOps professionals should learn Docker and KubernetesThe rise of cloud computing has cemented Kubernetes as a must-learn technology for developers and DevOps professionals in the tech industry today. Major tech trends, such as concurrency and cloud computing, have continually reshaped the landscape. The focus now lands squarely on newer innovations like containers and serverless computing. Docker pioneered containers, allowing developers to package applications into lightweight, portable capsules. But Kubernetes takes container orchestration to the next level. It has revolutionized application deployment by enabling rapid, seamless software releases with zero downtime. For developers, knowing the fundamentals of Kubernetes is essential because application deployment and orchestration issues are increasingly common in today's dynamic tech landscape. Kubernetes not only empowers you to navigate these challenges effectively but also bolsters your reputation and overall effectiveness in the field. Understanding Docker ContainersDocker enables containerization, a method of packaging software applications and their dependencies, into a single, portable unit called a container. This container encompasses all elements required for an application to run, including code, runtime, system tools, libraries, and settings. Such encapsulation guarantees consistency across various environments, simplifying the development, deployment, and scaling of applications. Benefits of using Docker in DevOps workflowsBelow are some of the benefits of using Docker in DevOps workflows: Consistent environments - Docker containers create isolated, reproducible environments that remain consistent regardless of the underlying infrastructure. This consistency eliminates issues that can arise when moving applications between different environments..Faster setup - Docker is lightweight and fast to spin up compared to VMs. This accelerates processes like onboarding new developers, provisioning test servers, and setting up staging.Infrastructure efficiency - Containers share the OS kernel and have a minimal footprint. This allows for the packing of more apps per host, thus reducing infrastructure costs.Enables microservices - Docker's granularity makes it easy to break monoliths into independent microservices. This improves scalability and maintainability.Portability - Docker containers can run on any infrastructure - desktop, data center, or cloud - without the need for any additional configuration.Improved collaboration - Using Docker repos allows teams to easily share and reuse containers for faster application development.Step-by-step guide on installing DockerGetting started with Docker is quick and easy. The basic process involves the following: Download Docker: Download the Docker Desktop installer suitable for your operating system from the official Docker website.Begin Installation: Double-click the downloaded installer to start the installation.Verify Installation: Once installed, open a command-line interface (e.g., Command Prompt, PowerShell) and run the following command to verify the installation:docker run hello-worldExpected Output: If successful, it should give an output similar to this:Getting Started with KubernetesKubernetes is a platform that automates the deployment, scaling, and management of containerized applications. It helps you efficiently organize and schedule workloads across clusters of hosts. Key components of Kubernetes architectureKubernetes works by organizing various components to assist with different aspects of container deployment and management. These key components include: Pods: Pods serve as a collective space where containers running applications can seamlessly collaborate and share resources. It is the smallest deployable unit that represents a single instance of a running process in a cluster.Nodes: Nodes are the individual machines (virtual or physical) in the cluster where pods run. They are the worker units responsible for executing tasks.Master Node: The master node is a critical control point overseeing the entire cluster. It coordinates communication between nodes and maintains the desired state of the cluster..Control Plane: The control plane is the brain of the Kubernetes cluster. It comprises several vital components:API Server: The API server acts as the front end for the Kubernetes control plane, validating and processing requests.Scheduler: The scheduler assigns workloads to nodes, considering factors like resource availability.Controller Manager: The controller manager enforces cluster policies, continually working to bring the current state to the desired state.etcd: etcd is a distributed key-value store storing the cluster's configuration and state.Below is an image of the Kubernetes architecture: Kubernetes ArchitectureSetting up a Kubernetes clusterA Kubernetes cluster can be set up on the Cloud or on a local machine. To set up a cluster on your local machine, you can use tools such as Kubeadmin or minikube. For a detailed walkthrough on setting up a Kubernetes cluster locally, check out our blog post: How to Setup a Kubernetes Cluster with Minikube & Kubeadm Alternatively, you can set up a Kubernetes cluster on your chosen cloud service. Some of the most popular managed Kubernetes services include Amazon EKS, Azure Kubernetes Service (AKS), and Google Kubernetes Engine (GKE). The setup process process includes tasks such as defining resources and handling infrastructure. Docker and Kubernetes IntegrationDocker and Kubernetes work seamlessly together. As an open container runtime standard, Kubernetes is designed to natively support Docker containers. This seamless integration enables deploying Docker containers onto the pods within a Kubernetes cluster. Advantages of combining Docker and Kubernetes in DevOps practicesBelow are the advantages of combining Docker and Kubernetes in DevOps practices: Consistent Environments - Docker's containerization provides a uniform application environment across the development, testing, and production stages.Agile Deployments - Kubernetes enables swift and automated deployments of applications containerized with Docker, promoting agility in the development and release process.Health Monitoring - Kubernetes continuously monitors the status of containers within the cluster to ensure optimal performance and reliability.Zero Downtime Updates - Kubernetes supports rolling updates, ensuring zero downtime when upgrading your containerized application.Easy Scalability - Kubernetes autoscaling mechanisms make scaling applications based on user traffic easy. The supported autoscaling mechanisms include:Horizontal Autoscaling: Adjusts the number of containers dynamically based on demand.Vertical Autoscaling: Adjusts the resources allocated to containers based on demand.Cluster Autoscaling: Adjusts the number of nodes in the cluster dynamically to accommodate changing resource requirements.Deploying Docker containers on a Kubernetes cluster Let's walk through a simple deployment example to see orchestration concepts first-hand. We'll be deploying the popular Nginx web server in a Docker container onto a Kubernetes cluster. Pull Nginx Container ImageTo start, we need to pull the Nginx container image from Docker Hub. Open your terminal and run the following command: docker pull nginxCreate Kubernetes DeploymentNow, let's create a Kubernetes Deployment named "my-nginx" with the Nginx container image by running the following command: kubectl create deployment my-nginx --image=nginxViewing the deploymentCheck the deployment details, including replica counts and pod statuses, using: kubectl get deploymentsScaling the deploymentTo check the current replica count and scale the deployment to 5 container instances, use the following commands: kubectl scale deployment my-nginx --replicas=5Scale out to 5 container instances Viewing the deployment has been scaled.Check the pods available to ensure the application has been scaled: kubectl get podsYou should see 5 pods. The names of all pods should start with ‘my-nginx…’ Rolling updateNow, let's perform a rolling update by updating the Nginx version to 1.19. Execute the following commands: kubectl set image deployment my-nginx nginx=nginx:1.19Update nginx version by image tag kubectl rollout status deployment my-nginxCheck rollout status These commands update the container image and ensure a smooth, rolling update without downtime. Learning Resources To get started with Docker and Kubernetes, you need to dive into the key concepts. I recommend you start with the following resources: The Role of Docker in DevOps Kubernetes Learning CurveDocker Learning Path 10 Best Kubernetes Courses to Start Learning Online in 2022Docker vs. Containerd: A Quick Comparison (2023)The Ultimate Docker Certification (DCA) Guide for 2022Kubernetes Removed Docker What Happens NowBest Practices and TipsWhen working with Docker and Kubernetes, adopting best practices and implementing effective strategies is crucial for successful containerized applications. At the same time, there are a few common pitfalls that you should avoid. Common Pitfalls to Avoid When Working With Docker And Kubernetes Here are some common pitfalls to avoid when working with Docker and Kubernetes: Inadequate Resource Allocation: Ensure proper resource allocation for containers to prevent resource contention and performance issues.Ignoring Image Size: Be mindful of image size. Large container images can slow down deployment and consume more resources, resulting in unnecessary costs.Overlooking Security Best Practices: Implement security measures such as image scanning, least privilege principles, and regular updates to avoid vulnerabilities.Tips for Optimizing Performance and Efficiency in Containerized EnvironmentsBelow are some tips that will help you in optimizing your containerized environment: Efficient Image Builds: Optimize Dockerfiles for efficient image builds. Leverage multi-stage builds and minimize layer sizes for faster and smaller images.Horizontal Scaling: Design applications for horizontal scalability. Use Kubernetes' horizontal pod autoscaling to dynamically adjust the number of running instances based on demand.Health Probes and Readiness Checks: Implement proper health probes and readiness checks in Kubernetes to ensure that only healthy containers receive traffic, enhancing application reliability. To learn more about probes, check out this blog: Kubernetes Readiness Probe: A Simple Guide with ExamplesResource Limits and Requests: Set resource limits and request parameters to prevent resource starvation and ensure predictable performance.Log Aggregation: Implement centralized log aggregation for better visibility into containerized applications. This will make troubleshooting and monitoring much easier and faster.Stay Updated: Latest Trends in Kubernetes and DockerThe Docker and Kubernetes landscape continues to evolve rapidly, with new innovative features and tools being released frequently. Recent innovations have mainly focused on simplifying management workflows, enhanced security features, deeper cloud integration, and new approaches to app portability across environments. Staying up-to-date on the latest trends and innovations will enable you to take full advantage of the latest capabilities and best practices for building, shipping, and running applications with Docker and Kubernetes. Sign up for KodeKloud's exclusive Kubernetes and Docker courses Access a wealth of resources and hands-on labs to solidify your skills. Start your journey towards becoming a certified DevOps professional by becoming a KodeKloud member for free. View the full article

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AWS Secrets Manager serves as a centralized and user-friendly solution for effectively handling access to all your secrets within the AWS cloud environment. It simplifies the process of rotating, maintaining, and recovering essential items such as database credentials and API keys throughout their lifecycle. A solid grasp of the AWS Secrets Manager concept is a valuable asset on the path to becoming an AWS Certified Developer. In this blog, you are going to see how to retrieve the secrets that exist in the AWS Service Manager with the help of AWS Lambda in virtual lab settings. Let’s dive in! What is a Secret Manager in AWS? AWS Secrets Manager is a tool that assists in safeguarding confidential information required to access your applications, services, and IT assets. This service makes it simple to regularly change, oversee, and access things like database credentials and API keys securely. Consider the AWS Secrets Manager example, users and applications can retrieve these secrets using specific APIs, eliminating the necessity of storing sensitive data in plain text within the code. This enhances security and simplifies the management of secret information. AWS Secrets Manager Pricing AWS Secrets Manager operates on a pay-as-you-go basis, where your costs are determined by the number of secrets you store and the API calls you make. The service is transparent, with no hidden fees or requirements for long-term commitments. Additionally, there is a 30-day AWS Secrets Manager free tier period, which begins when you store your initial secret, allowing you to explore AWS Secrets Manager without any charges. Once the free trial period ends, you will be billed at a rate of $0.40 per secret each month, and $0.05 for every 10,000 API calls. AWS Secrets Manager Vs Parameter Score What are AWS Lambda functions? AWS Lambda is a service for creating applications that eliminates the need to manually set up or oversee servers. AWS Lambda functions frequently require access to sensitive information like certificates, API keys, or database passwords. It’s crucial to keep these secrets separate from the function code to prevent exposing them in the source code of your application. By using an external secrets manager, you can enhance security and avoid unintentional exposure. Secrets managers offer benefits like access control, auditing, and the ability to manage secret rotation. It’s essential not to store secrets in Lambda configuration environment variables, as these can be seen by anyone with access to view the function’s configuration settings. Architecture Diagram for retrieving secretes in AWS Secrets Manager with AWS Lambda When Lambda invokes your function for the first time, it creates a runtime environment. First, it runs the function’s initialization code, which includes everything outside of the main handler. After that, Lambda executes the function’s handler code, which receives the event payload and processes your application’s logic. For subsequent invocations, Lambda can reuse the same runtime environment. To access secrets, you have a couple of options. One way is to retrieve the secret during each function invocation from within your handler code. This ensures you always have the most up-to-date secret, but it can lead to longer execution times and higher costs, as you’re making a call to the secret manager every time. There may also be additional costs associated with retrieving secrets from the Secret Manager. Another approach is to retrieve the secret during the function’s initialization process. This means you fetch the secret once when the runtime environment is set up, and then you can reuse that secret during subsequent invocations, improving cost efficiency and performance. The Serverless Land pattern example demonstrates how to retrieve a secret during the initialization phase using Node.js and top-level await. If the secret might change between invocations, make sure your handler can verify the secret’s validity and, if necessary, retrieve the updated secret. Another method to optimize this process is to use Lambda extensions. These extensions can fetch secrets from Secrets Manager, cache them, and automatically refresh the cache based on a specified time interval. The extension retrieves the secret from Secrets Manager before the initialization process and provides it via a local HTTP endpoint. Your function can then get the secret from this local endpoint, which is faster than direct retrieval from Secrets Manager. Moreover, you can share the extension among multiple functions, reducing code duplication. The extension takes care of refreshing the cache at the right intervention to ensure that your function always has access to the most recent secret, which enhances reliability. Guidelines to retrieve secrets stored in AWS Secrets Manager with AWS Lambda To retrieve the secrets retained in the AWS Secret Manager with the help of AWS Lambda, you can follow these guided instructions: First, you need to access the Whizlabs Labs library. Click on guided labs on the left side of the lab’s homepage and enter the lab name in the search lab tab. Now, you have found the guided lab for the topic you have entered in the search tab. By clicking on this lab, you can see the lab overview section. Upon reviewing the lab instructions, you may initiate the lab by selecting the “Start Lab” option located on the right side of the screen. Tasks involved in this guided lab are as follows: Task 1: Sign in to the AWS Management Console Start by accessing the AWS Management Console and set the region to N. Virginia a.You need to ensure that you do not edit or remove the 12-digit Account ID in the AWS Console. Copy your username and password from the Lab Console, then paste them into the IAM Username and Password fields in the AWS Console. Afterward, click the ‘Sign in’ button. Task 2: Create a Lambda Function Navigate to the Lambda service. Create a new Lambda function named “WhizFunction” with the runtime set to Python 3.8. Configure the function’s execution role and use the existing role named “Lambda_Secret_Access.” Adjust the function’s timeout to 2 minutes. Adjust the function’s timeout to 2 minutes. Task 3: Write a Lambda to Hard-code Access Keys Develop a Lambda function that creates a DynamoDB table and inserts items. This code will include hard-coded access keys. Download the code provided in the lab document. Replace the existing code in the Lambda function “WhizFunction” with the code from “Code1” in the downloaded zip file. Make sure to change the AWS Access Key and AWS Secret Access Key as instructed in the lab document. Deploy the code and configure a test event named “WhizEvent.” Run the test to create a DynamoDB table with i followed by configuration of the test event. Now click on the save button and click the test button to execute the code. The DynamoDB table was created successfully with some data fields. Task 4: View the DynamoDB Table in the Console Access the DynamoDB service by searching service in the top left corner. In the “Tables” section, you will find a table named “Whizlabs_stud_table1.” You can view the items within the table by selecting the table and clicking “Explore table items.” Task 5: Write a Lambda Code to Return Table Data Modify the Lambda function “WhizFunction” to write code that retrieves data from the DynamoDB table. Replace the existing code with the code from “Code2” in the lab document, making the necessary AWS Access Key and AWS Secret Access Key changes. Deploy the code and execute a test to enable the Lambda function to return data from the table. Task 6: Create a Secret Manager to Store Access Keys Access AWS Secrets Manager and make sure you are in the N. Virginia Region. Create a new secret by specifying it as “Other Type of Secret.” Enter the Access Key and Secret Access Key as key-value pairs. Choose the default encryption key. Name the secret “whizsecret” and proceed with the default settings. Review and store the secret and copy the Secret ARN for later use. Task 7: Write a Lambda to Create DynamoDB Items Using Secrets Manager Modify the Lambda function to create a new DynamoDB table and insert items by retrieving access keys from Secrets Manager. Replace the code with the code from “Code3” in the lab document, updating the Secret ARN. Deploy the code and run a test to create the DynamoDB table and items securely. Task 8: View the DynamoDB Table in the Console Access the DynamoDB service. In the “Tables” section, you will find a table named “Whizlabs_stud_table2.” To view the items, select the table and click “Explore table items.” Task 9: Write a Lambda Code to View Table Items Using Secrets Manager. Modify the Lambda function to write code that fetches table items securely using access and secret keys stored in Secrets Manager. Replace the code with the code from “Code4” in the lab document, updating the Secret ARN. Deploy the code and execute a test to securely access and view table items. Task 10: Cleanup AWS Resources Finally, you can delete the Lambda function “WhizFunction.” Delete both DynamoDB tables created. Delete the secret “whizsecret” from AWS Secrets Manager. Schedule its deletion with a waiting period of 7 days to ensure cleanup. Finally, end the lab by signing out from the AWS Management console. Also Read : Free AWS Developer Associate Exam Questions FAQs How much does the AWS Secret Manager parameter store cost? Parameter Store doesn’t incur any extra costs. However, there is a maximum limit of 10,000 parameters that you can store. What can be stored in AWS secrets manager? AWS Secrets Manager serves as a versatile solution for storing and managing a variety of sensitive information. This includes but is not limited to database credentials, application credentials, OAuth tokens, API keys, and various other secrets essential for different aspects of your operations. It’s important to note that several AWS services seamlessly integrate with Secrets Manager to securely handle and utilize these confidential data points throughout their entire lifecycle. What is the length limit for the AWS secrets manager? In the Secrets Manager console, data is stored in the form of a JSON structure, consisting of key/value pairs that can be easily parsed by a Lambda rotation function. AWS Secret manager limits range from 1 character to 65536 characters. Also, it’s important to note that the tag key names in Secrets Manager are case-sensitive. What are the benefits of AWS Secrets Manager? Secrets Manager provides a secure way to save and oversee your credentials. It makes the process of modifying or rotating your credentials easy, without requiring any complex code or configuration adjustments. Instead of embedding credentials directly in your code or configuration files, you can opt to store them safely using Secrets Manager. What is the best practice for an AWS secrets manager? You can adhere to the below listed AWS Secrets Manager best practices to carry out the secret storing in a better way: Make sure that the AWS Secrets Manager service applies encryption for data at rest by using Key Management Service (KMS) Customer Master Keys (CMKs). Ensure that automatic rotation is turned on for your Amazon Secrets Manager secrets. Also, confirm that the rotation schedule for Amazon Secrets Manager is set up correctly. Conclusion Hope this blog equips you with the knowledge and skills to effectively manage secrets within AWS, ensuring the protection of your critical data. Following the above AWS Secrets Manager tutorial steps can help to access the sensitive information stored in Secret Manager securely with the usage of AWS Lambda. You can also opt for AWS Sandbox to play around with the AWS platform. View the full article

DevOps training in pune 1. Improvement:- Within this DevOps point, the event of code occurs constantly. In this segment, the whole development way is split into little development cycles This rewards the DevOps staff to accelerate applications development and delivery technique. 2. Testing:- QA team utilize tools such as selenium to recognize and fix bugs inside the new part of code. 3. Integration:- Within this phase, new operation is incorporated with all the famous code, and testing occurs. Continuous development is only possible as a result of constant testing and integration. 4. Deployment:- Within this section, the installation method occurs continuously. It is done in this manner that any changes made any time inside the code, should not impact the operation of high traffic sites. 5. Tracking:- Within this part, the performance group can lookout of this improper system behaviour or bugs which are located in creation. At Sevenmentor Greatest DevOps Training in Pune are completely predicated on live jobs from USA Client at which you'll acquire live environment through the program development life cycle. DevOps classes in pune Other Significant Reasons are: Reproducibility: At the Software development process Version is all about so the earlier version could be revived anytime depending on your interest. Maintainability: Fault tolerance is less fewer attempts are necessary for retrieval in case of a brand new release crashing or scrutinizing the present system. Time to market: You understand that the DevOps methodology is quicker than any other conventional methodology. DevOps raise the speed to market around 50 percent through compact software shipping. Greater Quality: DevOps is a integration of Developer and IT Operation team therefore that it enables the staff to give enhanced quality of program development as it integrates infrastructure problems. It assists in the reduction of flaws throughout the lifecycle. Resiliency: The Operational condition of this software process is much more secure when compared to other procedures, protected, and modifications are auditable. Cost Performance the majority of those DevOps tools are open source and it's readily available online. As a result of this cost efficacy from the applications development process that's obviously an aspiration of all IT firms' management. DevOps courses in pune

Full Online Computer Science Database and Internet Career Course Part 1 Introduction to Computers and Operating Systems Chapter 1 The General Purpose Computer and Numbers Used 1.1 External Physical Components of a General Purpose Computer 1.2 Typing 1.3 Motherboard 1.4 Counting in Different Bases 1.5 Converting a Number from One Base to Another 1.6 Conversion from Base 10 to Base 2 1.7 Problems Chapter 2 Boolean Algebra and Its Related Computer Components 2.1 Basic Boolean Operators 2.2 Two Operand Truth Table and Their Electronic Components 2.3 Boolean Postulates 2.4 Boolean Properties 2.5 Simplification of Compound Expressions 2.6 Minimum Sum of Products 2.7 Problems Chapter 3 Binary Number Operations in the Microprocessor 3.1 Introduction 3.2 Addition of Binary Numbers 3.3 Two’s Complement and Its Subtraction of Binary Numbers 3.4 Multiplication of Binary Numbers 3.5 Division of Binary Numbers 3.6 Arithmetic Operations with Software and Hardware 3.7 Logic Operations in the Microprocessor 3.8 ASCII Character Set and Its Code Values 3.9 Floating Point Number Representation 3.10 Number Prefixes in Computing 3.11 Problems Chapter 4 The 6502 Microprocessor Assembly Language Tutorial 4.1 Introduction 4.2 Data Transfer Instructions 4.3 Arithmetic Operations 4.4 Logical Operations 4.5 Shift and Rotate Operations 4.6 Relative Addressing Mode 4.7 Indexed Addressing and Indirect Addressing Separately 4.8 Indexed Indirect Addressing 4.9 Increment, Decrement, and Test-BITs Instructions 4.10 Compare Instructions 4.11 Jump and Branch Instructions 4.12 The Stack Area 4.13 Subroutine Call and Return 4.14 A Count Down Loop Example 4.15 Translating a Program 4.16 Interrupts 4.17 Summary of the 6502 Main Addressing Modes 4.18 Creating a String with the 6502 µP Assembly Language 4.19 Creating an Array with the 6502 µP Assembly Language 4.20 Problems Chapter 5 The Commodore-64 Operating System in Assembly Language 5.1 Introduction 5.2 The Two Complex Interface Adapters 5.3 Keyboard Assembly Language Programming 5.4 Channel, Device Number, and Logical File Number 5.5 Opening a Channel, Opening a Logical File, Closing a Logical File, and Closing All I/O Channels 5.6 Sending the Character to the Screen 5.7 Sending and Receiving Bytes for Disk Drive 5.8 The OS SAVE Routine 5.9 The OS LOAD Routine 5.10 The Modem and RS-232 Standard 5.11 Counting and Timing 5.12 The ¯IRQ and ¯NMI Requests 5.13 Interrupt Driven Background Program 5.14 Assembly and Compilation 5.15 Saving, Loading, and Running a Program 5.16 Booting for Commodore-64 5.17 Problems Chapter 6 Modern Computer Architecture Basics With Assembly Language 6.1 Introduction 6.2 Motherboard Block Diagram of Modern PC 6.3 The x64 Computer Architecture Basics 6.4 The 64-Bit ARM Computer Architecture Basics 6.5 Instructions and Data 6.6 The Harvard Architecture 6.7 Cache Memory 6.8 Processes and Threads 6.9 Multiprocessing 6.10 Paging 6.11 Problems Solutions to Each Chapter Problems Solutions to the Problems of Chapter 1 of the Full Online Computer Science Dataset and Internet Career Course from the Beginning Solutions to the Problems of Chapter 2 of the Full Online Computer Science Dataset and Internet Career Course from the Beginning Solutions to the Problems of Chapter 3 of the Full Online Computer Science Dataset and Internet Career Course from the Beginning Solutions to the Problems of Chapter 4 of the Full Online Computer Science Dataset and Internet Career Course from the Beginning Solutions to the Problems of Chapter 5 of the Full Online Computer Science Dataset and Internet Career Course from the Beginning Solutions to the Problems of Chapter 6 of the Full Online Computer Science Dataset and Internet Career Course from the Beginning View the full article

Dynatrace is a software intelligence company that provides application performance management (APM), artificial intelligence for operations (AIOps), cloud infrastructure monitoring, and digital experience management solutions. Here’s a breakdown of what Dynatrace offers: Application Performance Management (APM): Dynatrace monitors and optimizes the performance of applications. This ensures that software applications run smoothly and efficiently. APM tools can help identify bottlenecks, slowdowns, or failures in software applications. Artificial Intelligence for Operations (AIOps): Dynatrace uses AI to automatically detect, diagnose, and prioritize anomalies in software applications and infrastructure. This helps organizations to proactively address issues before they impact users or the business. Cloud Infrastructure Monitoring: As organizations move to cloud-based infrastructures, monitoring the performance and health of these environments becomes critical. Dynatrace provides insights into cloud platforms, containers, and orchestration tools. Digital Experience Monitoring: This involves understanding how users are experiencing an application. For instance, if a user encounters a slow-loading webpage or an error during a checkout process on an e-commerce site, this impacts their digital experience. Dynatrace can track and optimize these user experiences across web, mobile, and other digital channels. Automation and Integration: Dynatrace can be integrated into CI/CD pipelines to ensure that performance issues are caught early in the development lifecycle. This aids in the automation of the software delivery process, ensuring that applications are not only functionally correct but also optimized for performance. Full-Stack Monitoring: One of the hallmarks of Dynatrace is its ability to provide insights from the application layer down to the infrastructure, covering the entire technology stack. This holistic view ensures that no aspect of an application’s performance is overlooked. OneAgent: This is Dynatrace’s proprietary monitoring agent that collects data from the various components of an application and its infrastructure. OneAgent simplifies the data collection process, making it easier to gain insights into the system’s performance. How DevOpsSchool’s dynatrace course are best? DevOpsSchool’s Dynatrace courses are highly rated by students and are considered to be among the best in the industry. Here are some of the reasons why: Comprehensive and up-to-date curriculum: The courses cover all aspects of Dynatrace, from basic concepts to advanced features. The curriculum is also regularly updated to reflect the latest changes to the Dynatrace platform. Experienced and knowledgeable instructors: The instructors at DevOpsSchool are experienced Dynatrace professionals with a deep understanding of the platform. They are also passionate about teaching and helping students learn. Interactive and hands-on training: The courses are designed to be interactive and hands-on, with plenty of opportunities for students to practice what they are learning. This helps students to develop the skills and knowledge they need to use Dynatrace effectively in their jobs. Real-world case studies and examples: The courses use real-world case studies and examples to illustrate the concepts and features of Dynatrace. This helps students to understand how Dynatrace can be used to solve real-world problems. Affordable pricing: The Dynatrace courses at DevOpsSchool are very affordable, especially when compared to other training providers. In addition to the above, DevOpsSchool also offers the following benefits: Flexible training options: DevOpsSchool offers both online and in-person training options. This allows students to choose the format that best suits their needs and schedule. Lifetime support: DevOpsSchool provides lifetime support to all of its students. This means that students can contact the instructors with any questions or problems they have, even after they have completed the course. How DevOpsSchool’s training would help dynatrace certification? “DevOpsSchool” is known as a training and tutorial platform that offers various IT and DevOps-related courses. If DevOpsSchool provides training specifically tailored to Dynatrace, then such training can indeed be beneficial for those aiming to achieve Dynatrace certification or enhance their skills in using the Dynatrace platform. Here’s how a DevOpsSchool training (or any reputable training program) might help in preparing for a Dynatrace certification: Curriculum Alignment: A good training program will have its curriculum aligned with the certification’s objectives, ensuring that students cover all the necessary topics. Hands-on Labs: Practical experience is invaluable. DevOpsSchool’s training might provide hands-on labs where students can practice setting up, configuring, and using Dynatrace in real-world scenarios. Expert Instructors: A knowledgeable instructor can provide insights, best practices, and clarifications that might not be available in standard study materials. Study Materials: Apart from the training sessions, supplementary materials like notes, slide decks, and references can be provided for a holistic learning experience. Mock Exams: Simulated exams can help students get a feel for the certification test, allowing them to gauge their preparedness and adjust their study approach if needed. Interactive Q&A: During the training, having the chance to ask questions and interact with the instructor and peers can help clarify doubts and enhance understanding. Real-World Scenarios: A good training session will often discuss real-world scenarios, challenges, and solutions, which can be crucial for applying knowledge in practical situations and might also be touched upon in the certification exam. Continuous Updates: The world of IT and APM tools like Dynatrace evolves rapidly. Regularly updated training materials ensure that students are preparing with the latest information and best practices. Community & Networking: Joining a course like one from DevOpsSchool might provide opportunities to network with fellow professionals, share experiences, and learn from others. Post-Training Support: Some training providers offer support even after the training session is over. This can be in the form of doubt-clearance, forums, or additional resources. The post Best Dynatrace online training and certification appeared first on DevOpsSchool.com. View the full article

In the dynamic world of DevOps and system administration, command-line proficiency is a crucial skill. Bash, one of the most widely used command-line shells - and the default for most Unix-based systems, including popular Linux distributions - offers immense power and versatility. Mastering Bash scripting can give you a competitive edge in the automation-reliant field of DevOps. This blog post, based on the Advanced Bash Scripting course offered by KodeKloud, serves as a comprehensive guide to mastering Bash scripting. Understanding Bash ScriptingBash scripts are essentially command-line programs written in the Bash shell language. They are used to automate tasks and execute commands in a series. Bash scripts simplify complex tasks and are often used in system administration and programming. The scripts are executed in a terminal window, and they can be created using any text editor. Why Advanced Bash Scripting?With bash scripting, you can write scripts that can perform complex operations, manipulate data, and interact with the system. It is a versatile language that can be used on almost any platform, making it an excellent choice for system administrators and developers. Learning bash scripting is an investment in your future, as it can help you work more efficiently and effectively. The KodeKloud CourseKodeKloud offers a comprehensive course on Advanced Bash Scripting, designed to equip learners with the knowledge and skills to effectively utilize Bash. The course covers Bash scripting conventions and best practices, working with variables, functions, and parameter expansions, understanding streams, and managing input/output redirection, among other topics. The course is tailored for visual learners seeking an engaging and up-to-date learning experience. It balances theory and practice perfectly to ensure learners easily grasp Bash’s intricate concepts. From a theory perspective, the course explores widely discussed concepts like using curly braces for variable expansion, file descriptors, and what POSIX compliance means, along with its implications for syntax choice. From the practical perspective, it includes guides for modern Bash features, including associative arrays using key-value pairs for accessing array elements, introductory tutorials for popular command-line utilities like awk and sed, and Labs for practicing each learned concept to complement the learning experience. By mastering the concepts covered in this course, you will enhance your Bash proficiency and gain the confidence to write superior and more robust scripts. You'll understand how to create, read and debug scripts. Additionally, you’ll master how to implement script logging and error handling. Enroll in the Advance Bash Scripting Course! The Power of Bash ScriptingBash scripts can help automate a wide range of tasks and manage system configurations, making your work more efficient and reliable. By taking the KodeKloud course, you will develop practical skills in Bash scripting, including writing robust scripts that follow best practices. You will also learn how to manage input/output redirection, work with variables and functions, and use parameter expansions. These valuable skills will enable you to effectively use Bash scripting in your own work. Advanced Bash Scripting ConceptsIn addition to learning practical skills in Bash scripting, the KodeKloud course covers advanced concepts that allow users to leverage the full power of Bash. These concepts include associative arrays that use key-value pairs to access array elements as well as introductory tutorials for popular command-line utilities like awk and sed. With this knowledge, users can perform complex text-processing tasks using Bash scripts. Career Opportunities with Bash Scripting MasteryBy mastering Bash scripting, you will be well-positioned to pursue career opportunities in software development, IT management, and DevOps engineering. It will open up unparalleled career opportunities, allowing you to prosper in the system administration and DevOps fields. Whether you're automating deployments, managing system configurations, or writing complex data analysis scripts, mastery of Bash scripting will be a valuable asset. Enroll Now! ConclusionIn conclusion, Bash scripting is a powerful tool that every DevOps professional and system administrator should master. The KodeKloud Advanced Bash Scripting course provides a comprehensive guide to mastering its application, covering everything from the basics to advanced concepts. So, are you ready to enhance your DevOps or SysAdmin skills and gain command-line mastery? Enroll in the KodeKloud course today and unlock the power of Advanced Bash Scripting! Here's to your DevOps journey! New to Linux and Scripting? Start with our beginner courses: Linux Basics CourseShell Scripts for BeginnersWant to certify your Linux skills? Check out our certification exam preparation courses: Linux Foundation Certified System Administrator (LFCS)Linux Professional Institute LPIC-1 Exam 101Red Hat Certified System Administrator(RHCSA) SUBSCRIBE to gain access to this comprehensive course as well as 65+ additional courses on Linux, DevOps, AWS, Azure, GCP, Kubernetes, Docker, Ansible, Terraform, Python, and more. Join us on this transformative educational adventure and unlock the power of the bash scripts. View the full article

Exciting news for all DevOps enthusiasts committed to DevOps Mastery! KodeKloud’s highly anticipated Free Week is back, offering everything in the standard plan for free - for an entire week. The Free Week Starts From 25th September - 1st October. This includes access to our library of 70+ specialized DevOps courses covering 29 focused areas, 300+ hands-on DevOps labs from a total of 500+ specialized labs, and the freedom to experiment in our Playgrounds. Plus, get a taste of the KodeKloud Engineer Pro 2.0 - a groundbreaking platform that provides real hands-on experience with project tasks on actual systems. At KodeKloud, we're dedicated to Fostering Excellence in DevOps. We understand the importance of hands-on, practical learning in the ever-evolving tech landscape. That's why we invite both newcomers and seasoned professionals to join this event. Whether you're embarking on your DevOps journey or are a seasoned expert, this is your golden opportunity to elevate your skills. Click here to sign up for the Free Week now! Learning PathsIf you don’t already know where your goal posts are, then perhaps it’s time to branch out and look at our learning paths and see what speaks to you. We believe that everyone should have access to the best resources to hone their skills and propel their careers forward. Linux PathDive into advanced Linux concepts using our top-tier resources. As you journey towards mastery, consider the promising career of a System Administrator. Kubernetes PathFor all Kubernetes aficionados, KodeKloud acknowledges your commitment to mastering this pivotal orchestration tool. As Kubernetes continues to reign supreme in the cloud-native ecosystem, enhancing your expertise is paramount. You could even consider a career as a Kubernetes Administrator, or Kubernetes Developer. IaC PathOur curated courses are designed to unlock advanced IaC practices, tools, and techniques. Remember, mastering IaC is about efficiently designing, deploying, and maintaining scalable and resilient infrastructure. Let's embark on this journey together! HashiCorp PathHashiCorp's suite is revolutionizing modern infrastructure and cloud management. KodeKloud's offers a deep dive into tools like Terraform, Vault, Consul, and more. Our handpicked courses provide advanced insights and best practices, positioning you at the forefront of infrastructure automation and security. CI/CD PathCI/CD is transforming the DevOps and software development landscape. KodeKloud is your exclusive opportunity to amplify your CI/CD expertise. Our in-depth courses are tailored to give you a competitive edge in CI/CD practices. Mastering CI/CD streamlines software delivery and accelerates innovation. Cloud PathClick on each logo to explore their complete learning path. The cloud world's titans - AWS, Azure, and GCP - are reshaping industries globally. During KodeKloud's Free Week dive deep into these leading cloud platforms with our expertly crafted courses. Echoing real-world implementations and challenges, our roadmap empowers you to navigate the intricate landscapes of AWS, Azure, and GCP. Harness the vastness of the cloud and set the stage for a cloud-powered future. DevOps PathDevOps is at the heart of KodeKloud. Our entire existence is so we can create all the DevOps Engineers the market can handle. Our refined DevOps learning path offers the most comprehensive and cutting-edge DevOps content. Dive into our reservoir of knowledge and hands-on experience, ensuring you're at the vanguard of the industry. Explore our DevOps Engineer learning path and discover why DevOps isn't just our specialty, but our pride and joy. Cultivate Your Cloud Mastery with KodeKloud's Free WeekRecognizing the pivotal role of cloud technologies in modern DevOps practices, we've meticulously designed a Cloud Learning Path. As the tech landscape evolves, mastering cloud skills becomes indispensable for digital transformation excellence. Seize the opportunity during KodeKloud's Free Week to embark on a hands-on cloud mastery journey. Our Cloud Learning Path encompasses a spectrum of courses, from cloud computing fundamentals to intricate topics like container orchestration and serverless architecture. Click here to sign up for the Free Week! Hear From Industry Leaders during Free Week "Breaking Barriers: Navigating Tech Transitions and Flourishing in Tech Communities" with Julia Furst.When? September 25th, 7:30 PM IST Passionate tech advocate with years of industry experience. Recognized for her contributions to tech communities. A guiding light for many navigating tech transitions. Join Julia for a candid chat where she'll share her insights about thriving in tech communities and navigating tech transitions. If you've ever faced challenges in the tech world or are curious about making a transition, Julia's session promises to be enlightening. "Journeying Through the Cloud: From Maker to Multiplier, Kubernetes, and Beyond" with Natan Yellin:When? September 27th, 8:00 PM IST Deep expertise in Kubernetes and cloud ecosystems. Passionate about sharing insights and driving innovation. Natan's blend of stories and learnings is something you won't want to miss! "From Physical to Virtual: The Evolution of Data Protection in the Age of Kubernetes" with Geoff Burke.When? September 28th, 7:30 PM IST Expert in data protection and virtualization. Renowned for his insights into the evolution of data protection in modern tech environments. Join Geoff as he delves deep into the transformation of data protection from its traditional physical roots to the virtual landscapes of today. If you're keen on understanding how Kubernetes is reshaping the way we think about data protection, Geoff's session is a must-attend. "Unleashing WebAssembly: Surfing the Next Cloud-Native Wave with Live Demos" with Saiyam Pathak:When? September 29th, 7:30 PM IST Known for his deep dives into the latest tech trends and cloud-native solutions. If you've ever been curious about WebAssembly and its place in the cloud-native ecosystem, Saiyam's session promises to be a thrilling ride. Get ready for a blend of in-depth knowledge and live demonstrations that will spark your curiosity and drive your passion for DevOps! ConclusionIn conclusion, KodeKloud's Free Week embodies our commitment to Cultivating DevOps Mastery. It's a golden opportunity for professionals to elevate their expertise and delve into the nuances of modern DevOps practices. With full access to our premium courses and labs, participants can immerse themselves in hands-on learning experiences, harnessing the latest tools and methodologies. Our exclusive webinars and expert sessions further illuminate the evolving landscape of the industry. We invite every passionate professional to harness this chance and embark on a transformative journey with KodeKloud's Free Week. What are you waiting for? Sign up for the Free Week now! View the full article