10761 Mac courses

Duration 3 Days 18 CPD hours This course is intended for This course is designed for IT professionals with baseline skills in computer hardware, software support, and development who want to learn how to design, develop, implement, operate, and manage Internet of Things devices and related systems. It is for those interested in learning more about embedded systems, microcontroller programming, IoT security, and the development life cycle for IoT projects. While students will gain hands-on experience assembling a prototype IoT device and using software development tools, these activities are closely guided, so previous experience in electronics assembly and programming are not required. This course prepares students for taking the CertNexus Certified Internet of Things (IoT) Practitioner (Exam ITP-110). Overview In this course, you will learn how to apply Internet of Things technologies to solve real-world problems. You will: Construct and program an IoT device. Communicate with an IoT device using wired and wireless connections. Process sensor input and control an actuator on an IoT device. Manage security, privacy, and safety risks on IoT projects. Plan an IoT prototyping and development project. In this course, you will learn general strategies for planning, designing, developing, implementing, and maintaining an IoT system through various case studies and by assembling and configuring an IoT device to work in a sensor network. You will create an IoT device based on an ESP8266 microcontroller, implementing various common IoT features, such as analog and digital sensors, a web-based interface, MQTT messaging, and data encryption. The instructor led course includes an exam voucher for the Certified Internet of Things Practitioner (CIoTP) exam (exam ITP-110). Planning an IoT Implementation Select a General Architecture for an IoT Project Identify Benefits and Challenges of IoT Constructing and Programming an IoT Device Select and Configure a Processing Unit Select a Microcontroller Power Source Use a Software Development Kit to Program an IoT Device Communicating with an IoT Device Communicate Using Wired Connections Communicate Using Wireless Connections Communicate Using Internet Protocols Processing IoT Data Process IoT Device Input and Output Process Data in the Cloud Provide Machine to Machine Communication Managing Risks on IoT Projects Identify IoT Security and Privacy Risks Manage IoT Security and Privacy Risks Manage IoT Safety Risks Undertaking an IoT Project Identify Real World Applications for IoT Follow the IoT Development Lifecycle Additional course details: Nexus Humans CertNexus Certified Internet of Things Practitioner (CIoTP) training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the CertNexus Certified Internet of Things Practitioner (CIoTP) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 3 Days 18 CPD hours This course is intended for This is an Introductory level course for experienced Linux system administrators, DevOps engineers, infrastructure automation engineers, and systems design engineers. Ideally students should have familiarity with basic Python scripting. Attendees without programming skills can follow along with the scripting portion of the labs. Overview This course is approximately 50% hands-on, combining expert lecture, real-world demonstrations and group discussions with machine-based practical labs and exercises. Working in a hands-on learning environment led by our expert practitioner attendees will explore how to: Describe Ansible concepts and install Red Hat Ansible Engine (optional - we can pre-install is as well if desired, depending on the audience) Deploy Ansible and Configure Ansible to manage hosts and run ad hoc Ansible commands. Implement playbooks Write a simple Ansible playbook and run it to automate tasks on multiple managed hosts. Manage variables and facts Write playbooks that use variables to simplify management of the playbook and facts to reference information about managed hosts. Implement task control; Manage task control, handlers, and task errors in Ansible playbooks. Deploy files to managed hosts Deploy, manage, and adjust files on hosts managed by Ansible. Manage large projects Write playbooks that are optimized for larger, more complex projects. Simplify playbooks with roles Use Ansible roles to develop playbooks more quickly and to reuse Ansible code. Troubleshoot Ansible Troubleshoot playbooks and managed hosts. Automate Linux administration tasks Automate common Linux system administration tasks with Ansible This lab-intensive course is geared toward those responsible for automation of configuration management; consistent and repeatable application deployment; provisioning and deployment of development, testing, and production servers; and integration with DevOps CI/CD workflows. Throughout the course you will explore core Ansible features such as automatic provisioning, configuration management, service deployment and operational processes. Ansible Overview Overview of Architecture Overview of Deployments Inventory Deploying Ansible Installing Configuration Files Running Ad Hoc Commands Dynamic Inventory Playbooks Writing YAML Files Modules Variables and Inclusions Variables Facts Inclusions Task Control Constructing Flow Control Handlers Tags Handling Errors Jinja2 Templates Jinja2 Templates Jinja2 Templates Roles Role Structure Creating Roles Deploying Roles with Ansible Galaxy Optimizing Ansible Configuring Connection Types Configuring Delegation Configuring Parallelism Ansible Vault Configuring Ansible Vault Executing with Ansible Vault Troubleshooting Ansible Troubleshooting Playbooks Troubleshooting Managed Hosts Ansible Tower Ansible Tower overview Installing Account management Hosts Jobs Optional: Ansible in a DevOps Environment Provisioning Vagrant Machines Deploying Vagrant in a DevOps Environment Deploying Docker in a DevOps Environment Additional course details: Nexus Humans Introduction to Ansible: Automation with Ansible (TTDV7580) training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Introduction to Ansible: Automation with Ansible (TTDV7580) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 3 Days 18 CPD hours This course is intended for This course is geared for attendees with Intermediate IT skills who wish to learn Computer Vision with tensor flow 2 Overview This 'skills-centric' course is about 50% hands-on lab and 50% lecture, with extensive practical exercises designed to reinforce fundamental skills, concepts and best practices taught throughout the course. Working in a hands-on learning environment, led by our Computer Vision expert instructor, students will learn about and explore how to Build, train, and serve your own deep neural networks with TensorFlow 2 and Keras Apply modern solutions to a wide range of applications such as object detection and video analysis Run your models on mobile devices and web pages and improve their performance. Create your own neural networks from scratch Classify images with modern architectures including Inception and ResNet Detect and segment objects in images with YOLO, Mask R-CNN, and U-Net Tackle problems faced when developing self-driving cars and facial emotion recognition systems Boost your application's performance with transfer learning, GANs, and domain adaptation Use recurrent neural networks (RNNs) for video analysis Optimize and deploy your networks on mobile devices and in the browser Computer vision solutions are becoming increasingly common, making their way into fields such as health, automobile, social media, and robotics. Hands-On Computervision with TensorFlow 2 is a hands-on course that thoroughly explores TensorFlow 2, the brandnew version of Google's open source framework for machine learning. You will understand how to benefit from using convolutional neural networks (CNNs) for visual tasks. This course begins with the fundamentals of computer vision and deep learning, teaching you how to build a neural network from scratch. You will discover the features that have made TensorFlow the most widely used AI library, along with its intuitive Keras interface. You'll then move on to building, training, and deploying CNNs efficiently. Complete with concrete code examples, the course demonstrates how to classify images with modern solutions, such as Inception and ResNet, and extract specific content using You Only Look Once (YOLO), Mask R-CNN, and U-Net. You will also build generative dversarial networks (GANs) and variational autoencoders (VAEs) to create and edit images, and long short-term memory networks (LSTMs) to analyze videos. In the process, you will acquire advanced insights into transfer learning, data augmentation, domain adaptation, and mobile and web deployment, among other key concepts Computer Vision and Neural Networks Computer Vision and Neural Networks Technical requirements Computer vision in the wild A brief history of computer vision Getting started with neural networks TensorFlow Basics and Training a Model TensorFlow Basics and Training a Model Technical requirements Getting started with TensorFlow 2 and Keras TensorFlow 2 and Keras in detail The TensorFlow ecosystem Modern Neural Networks Modern Neural Networks Technical requirements Discovering convolutional neural networks Refining the training process Influential Classification Tools Influential Classification Tools Technical requirements Understanding advanced CNN architectures Leveraging transfer learning Object Detection Models Object Detection Models Technical requirements Introducing object detection A fast object detection algorithm YOLO Faster R-CNN ? a powerful object detection model Enhancing and Segmenting Images Enhancing and Segmenting Images Technical requirements Transforming images with encoders-decoders Understanding semantic segmentation Training on Complex and Scarce Datasets Training on Complex and Scarce Datasets Technical requirements Efficient data serving How to deal with data scarcity Video and Recurrent Neural Networks Video and Recurrent Neural Networks Technical requirements Introducing RNNs Classifying videos Optimizing Models and Deploying on Mobile Devices Optimizing Models and Deploying on Mobile Devices Technical requirements Optimizing computational and disk footprints On-device machine learning Example app ? recognizing facial expressions

Duration 4 Days 24 CPD hours This course is intended for This course is geared for attendees with Intermediate IT skills who wish to learn Computer Vision with tensor flow 2 Overview This 'skills-centric' course is about 50% hands-on lab and 50% lecture, with extensive practical exercises designed to reinforce fundamental skills, concepts and best practices taught throughout the course. Working in a hands-on learning environment, led by our Computer Vision expert instructor, students will learn about and explore how to Build, train, and serve your own deep neural networks with TensorFlow 2 and Keras Apply modern solutions to a wide range of applications such as object detection and video analysis Run your models on mobile devices and web pages and improve their performance. Create your own neural networks from scratch Classify images with modern architectures including Inception and ResNet Detect and segment objects in images with YOLO, Mask R-CNN, and U-Net Tackle problems faced when developing self-driving cars and facial emotion recognition systems Boost your application's performance with transfer learning, GANs, and domain adaptation Use recurrent neural networks (RNNs) for video analysis Optimize and deploy your networks on mobile devices and in the browser Computer vision solutions are becoming increasingly common, making their way into fields such as health, automobile, social media, and robotics. Hands-On Computervision with TensorFlow 2 is a hands-on course that thoroughly explores TensorFlow 2, the brand-new version of Google's open source framework for machine learning. You will understand how to benefit from using convolutional neural networks (CNNs) for visual tasks. This course begins with the fundamentals of computer vision and deep learning, teaching you how to build a neural network from scratch. You will discover the features that have made TensorFlow the most widely used AI library, along with its intuitive Keras interface. You'll then move on to building, training, and deploying CNNs efficiently. Complete with concrete code examples, the course demonstrates how to classify images with modern solutions, such as Inception and ResNet, and extract specific content using You Only Look Once (YOLO), Mask R-CNN, and U-Net. You will also build generative adversarial networks (GANs) and variational autoencoders (VAEs) to create and edit images, and long short-term memory networks (LSTMs) to analyze videos. In the process, you will acquire advanced insights into transfer learning, data augmentation, domain adaptation, and mobile and web deployment, among other key concepts. Computer Vision and Neural Networks Computer Vision and Neural Networks Technical requirements Computer vision in the wild A brief history of computer vision Getting started with neural networks TensorFlow Basics and Training a Model TensorFlow Basics and Training a Model Technical requirements Getting started with TensorFlow 2 and Keras TensorFlow 2 and Keras in detail The TensorFlow ecosystem Modern Neural Networks Modern Neural Networks Technical requirements Discovering convolutional neural networks Refining the training process Influential Classification Tools Influential Classification Tools Technical requirements Understanding advanced CNN architectures Leveraging transfer learning Object Detection Models Object Detection Models Technical requirements Introducing object detection A fast object detection algorithm ? YOLO Faster R-CNN ? a powerful object detection model Enhancing and Segmenting Images Enhancing and Segmenting Images Technical requirements Transforming images with encoders-decoders Understanding semantic segmentation Training on Complex and Scarce Datasets Training on Complex and Scarce Datasets Technical requirements Efficient data serving How to deal with data scarcity Video and Recurrent Neural Networks Video and Recurrent Neural Networks Technical requirements Introducing RNNs Classifying videos Optimizing Models and Deploying on Mobile Devices Optimizing Models and Deploying on Mobile Devices Technical requirements Optimizing computational and disk footprints On-device machine learning Example app ? recognizing facial expressions

Duration 4 Days 24 CPD hours This course is intended for System administrators System engineers Migration engineers Migration architects Overview By the end of the course, you should be able to meet the following objectives: Describe core VMware HCX use cases and common triggers for mobility Describe the core components and features of VMware HCX Describe a real-life example of a VMware HCX project Identify all major Cloud Providers offering and supporting VMware HCX Describe the features of VMware HCX services Explain the different deployment types for VMware HCX and choose the correct components to deploy for a particular use case Understand the resource, network, and VMware ESXi™ and VMware vCenter requirements for VMware HCX Install and configure VMware HCX Understand, deploy, and manage the HCX Service Mesh Understand Network Extension and Traffic Engineering Create Network Extension and enable Mobility Optimized Networking Understand WAN Optimization Understand the different migration types and be able to choose the best one for different applications and workloads Incorporate VMware HCX into a disaster recovery strategy Design a VMware HCX deployment for different use cases Manage the lifecycle of VMware HCX This four-day course gives you knowledge and practical exercises sufficient to manage VMware HCX© and to migrate virtual machines using VMware HCX. The course focuses on configuration and management of VMware HCX. The course equips system administrators with the knowledge, skills, and abilities to achieve competence in migrating virtual machines. Course Introduction Introductions and course logistics Course objectives Introduction to VMware HCX Describe workload mobility challenges that VMware HCX addresses Recognize use cases for VMware HCX Identify all major Cloud providers offering and supporting VMware HCX HCX Services and Deployment Types Describe the functions of VMware HCX components Recognize the services provided by VMware HCX Recognize when to use different deployment types for VMware HCX Be able to choose which components to install and configure for a different VMware HCX service HCX Deployment Identify the resource, network, and ESXi/VMware vCenter server requirements for VMware HCX Understand the VMware vCenter user roles and access requirements Describe the installation workflow Install, activate, and configure VMware HCX manager Understand the compute and network profile requirements for VMware HCX and its services Create site pair, compute, and network profiles Describe and manage the HCX Service Mesh Create and configure a HCX Service Mesh Network Extension Describe network extension use case and benefits Compare the HCX-Network extension service with other solutions Examine Network Extension capabilities and topology Create a Network Extension Describe network traffic packet flow Describe Mobility Optimized Networking Enable Mobility Optimized Networking Describe the TCP Flow Conditioning and Application path resiliency feature of VMware HCX Recognize the key benefits of TCP flow conditioning and Application path resiliency Describe WAN optimization Workload Mobility Describe different migration types Recognize the limitation of each migration method and consideration when planning a migration Understand Bulk and Replication Assisted VMware HCX© vMotion© migration methods Migrate a VM using Bulk migration Describe cold and vMotion migration method Migrate a VM using HCX vMotion migration Examine non VMware vSphere© workload migration Migrate a VM using an OS assisted migration method Business Continuity and Disaster Recovery Examine disaster recovery concepts Describe disaster recovery networks Plan and create disaster recovery networks Describe VM protection operations Protect, recover, and test recovery and reverse replication of a VM Understand VMware HCX and SRM integration and value HCX Lifecycle Management Backup and restore the VMware HCX manager Locate and access VMware HCX logs Troubleshoot VMware HCX Plan for VMware HCX manager and component updates Customer Design Scenarios Design a VMware HCX deployment Choose workload mobility methods for the migration Discuss customer requirements and proposed design Discuss components, services, and migration methods for the scenario

Duration 3 Days 18 CPD hours This course is intended for Application developers who want to build cloud-native applications or redesign existing applications that will run on Google Cloud Platform Overview This course teaches participants the following skills: Use best practices for application development. Choose the appropriate data storage option for application data. Implement federated identity management. Develop loosely coupled application components or microservices. Integrate application components and data sources. Debug, trace, and monitor applications. Perform repeatable deployments with containers and deployment services. Choose the appropriate application runtime environment; use Google Container Engine as a runtime environment and later switch to a no-ops solution with Google App Engine flexible environment. Learn how to design, develop, and deploy applications that seamlessly integrate components from the Google Cloud ecosystem. This course uses lectures, demos, and hands-on labs to show you how to use Google Cloud services and pre-trained machine learning APIs to build secure, scalable, and intelligent cloud-native applications. Best Practices for Application Development Code and environment management. Design and development of secure, scalable, reliable, loosely coupled application components and microservices. Continuous integration and delivery. Re-architecting applications for the cloud. Google Cloud Client Libraries, Google Cloud SDK, and Google Firebase SDK How to set up and use Google Cloud Client Libraries, Google Cloud SDK, and Google Firebase SDK. Lab: Set up Google Client Libraries, Cloud SDK, and Firebase SDK on a Linux instance and set up application credentials. Overview of Data Storage Options Overview of options to store application data. Use cases for Google Cloud Storage, Cloud Firestore, Cloud Bigtable, Google Cloud SQL, and Cloud Spanner. Best Practices for Using Cloud Firestore Best practices related to using Cloud Firestore in Datastore mode for:Queries, Built-in and composite indexes, Inserting and deleting data (batch operations),Transactions,Error handling. Bulk-loading data into Cloud Firestore by using Google Cloud Dataflow. Lab: Store application data in Cloud Datastore. Performing Operations on Cloud Storage Operations that can be performed on buckets and objects. Consistency model. Error handling. Best Practices for Using Cloud Storage Naming buckets for static websites and other uses. Naming objects (from an access distribution perspective). Performance considerations. Setting up and debugging a CORS configuration on a bucket. Lab: Store files in Cloud Storage. Handling Authentication and Authorization Cloud Identity and Access Management (IAM) roles and service accounts. User authentication by using Firebase Authentication. User authentication and authorization by using Cloud Identity-Aware Proxy. Lab: Authenticate users by using Firebase Authentication. Using Pub/Sub to Integrate Components of Your Application Topics, publishers, and subscribers. Pull and push subscriptions. Use cases for Cloud Pub/Sub. Lab: Develop a backend service to process messages in a message queue. Adding Intelligence to Your Application Overview of pre-trained machine learning APIs such as Cloud Vision API and Cloud Natural Language Processing API. Using Cloud Functions for Event-Driven Processing Key concepts such as triggers, background functions, HTTP functions. Use cases. Developing and deploying functions. Logging, error reporting, and monitoring. Managing APIs with Cloud Endpoints Open API deployment configuration. Lab: Deploy an API for your application. Deploying Applications Creating and storing container images. Repeatable deployments with deployment configuration and templates. Lab: Use Deployment Manager to deploy a web application into Google App Engine flexible environment test and production environments. Execution Environments for Your Application Considerations for choosing an execution environment for your application or service:Google Compute Engine (GCE),Google Kubernetes Engine (GKE), App Engine flexible environment, Cloud Functions, Cloud Dataflow, Cloud Run. Lab: Deploying your application on App Engine flexible environment. Debugging, Monitoring, and Tuning Performance Application Performance Management Tools. Stackdriver Debugger. Stackdriver Error Reporting. Lab: Debugging an application error by using Stackdriver Debugger and Error Reporting. Stackdriver Logging. Key concepts related to Stackdriver Trace and Stackdriver Monitoring. Lab: Use Stackdriver Monitoring and Stackdriver Trace to trace a request across services, observe, and optimize performance.

Duration 3 Days 18 CPD hours This course is intended for This course is for Azure Administrators who migrate and manage SAP solutions on Azure. Azure Administrators manage the cloud services that span storage, networking, and compute cloud capabilities, with a deep understanding of each service across the full IT lifecycle. They take end-user requests for new cloud applications and make recommendations on services to use for optimal performance and scale, as well as provision, size, monitor and adjust as appropriate. This role requires communicating and coordinating with vendors. Azure Administrators use the Azure Portal and as they become more proficient they use PowerShell and the Command Line Interface. Overview After completing this course, students will be able to: Migrate and SAP HANA, S/4HANA, SAP NetWeaver to Azure Leverage Azure Portal, Cloud Shell, Azure PowerShell, CLI, and Resource Manager Use intersite connectivity features including VNet Peering and VNet-to-VNet connections Work with Azure Active Directory (AAD) and Azure AD Connect As an IT Professionals experienced in SAP solutions, you will discover how to leverage Azure resources that include deployment and configuration of virtual machines, virtual networks, storage accounts, and Azure AD that includes implementing and managing hybrid identities. You will also be introduced to concepts, scenarios, procedures, and hands-on labs that will empower you to best plan and implement migration and operation of an SAP solution on Azure. You will also receive guidance on subscriptions, create and scale virtual machines, implement storage solutions, configure virtual networking, back up and share data, connect Azure and on-premises sites, manage network traffic, implement Azure Active Directory, secure identities, and monitor your solution. Introduction Contains an overview of the SAP and Microsoft partnership. Foundations of SAP on Azure Contains brief lessons on Azure compute, Azure storage, Azure networking, SAP HANA for Azure (Large Instances), identity services, governance and manageability, backup and data protection services, and migration services. SAP Certified Offerings on Azure Contains lessons on general prerequisites (SAP support in public cloud environments), deployment options of Azure for SAP workloads, SAP product-specific support for Azure, operating System support of Azure for SAP workloads, storage support of Azure for SAP workloads, networking support for SAP, database support for SAP, high availability and disaster recovery support for SAP, and monitoring requirements for SAP. Lab : Online Lab: Implementing Linux clustering on Azure VMs Lab : Online Lab: Implementing Windows clustering on Azure VMs SAP on Azure Reference Architecture Contains lessons on SAP NetWeaver with AnyDB, SAP S4 HANA, and SAP HANA on Azure (Large Instances) on Azure VMs. Planning for Implementing SAP Solutions on Azure Contains lessons on Azure VM compute, network, and storage considerations. As well as Azure VM high availability and disaster recovery, Azure VM backup considerations, Azure VM monitoring considerations, Azure VM security considerations, and Azure VM authentication and access control considerations. Planning for Migrating SAP Workloads to Azure Contains lessons on strategies for migrating SAP systems to Microsoft Azure and SAP a workload planning and deployment checklist. Implementing Azure VM-based SAP Solutions Contains lessons on Azure VM deployment methodologies, single-instance implementations (2-tier or 3-tier), implementing HA SAP NetWeaver with AnyDB on Azure VMs, implementing HA SAP HANA on Azure VMs, configure the Azure Enhanced Monitoring Extension for SAP, and implementing AD and Azure AD-based authentication. Module 8-Deploying HANA Large Instances (HLI) Contains a lesson on implementing HANA Large Instances (HLI). Migrating SAP Workloads to Azure Contains lessons on migration options, DMO methodologies, cloud migration options, and Very Large Database Migration to Azure. Lab : Online Lab-Implement SAP architecture on Azure VMs running Linux Lab : Online Lab-Implement SAP architecture on Azure VMs running Windows Maintaining SAP on Azure Contains lessons on, remote management, performing backups and restores, OS and workload updates, vertical and horizontal scaling, and Disaster Recovery (DR). Monitoring and Troubleshooting SAP on Azure Contains lessons on monitoring Azure VMs, monitoring SAP HANA on Azure (Large Instances), and integrating SAP solutions with Microsoft cloud services.

Duration 2 Days 12 CPD hours This course is intended for System architects, system administrators, IT managers, VMware partners, and individuals responsible for implementing and managing vSphere architectures who want to deploy vSphere 8.0 into their existing vSphere environment. Overview By the end of the course, you should be able to meet the following objectives: Recognize the importance of key features and enhancements in vSphere 8.0 Describe vCenter Server, VMware ESXi, storage, virtual machine, and security enhancements in vSphere 8.0 Describe the purpose of vSphere Distributed Services Engine Update an ESXi host equipped with a Data Processing Unit (DPU) using vSphere Lifecycle Manager Identify devices supported for system storage on ESXi 8.0 Recognize enhancements to VM hardware compatibility settings VMware vSphere Memory Monitoring and Remediation and the improvements to vSphere DRS Recognize the new Virtual Non-Uniform Memory Access (vNUMA) topology settings of a VM in vSphere Client Use vSphere Lifecycle Manager and Auto Deploy to manage the configuration specifications for the hosts in a cluster Recognize the vSphere Lifecycle Manager and Auto Deploy enhancements in vSphere 8.0 Recognize the cloud benefits that VMware vSphere+ brings to on-premises workloads Recognize technology that is discontinued or deprecated in vSphere 8.0 In this two-day course, you explore the new features and enhancements following VMware vCenter Server 8.0 and VMware ESXi 8.0. Real-world use-case scenarios, hands-on lab exercises, and lectures teach you the skills that you need to effectively implement and configure VMware vSphere 8.0. Course Introduction Introductions and course logistics Course objectives Artificial Intelligence and Machine Learning Describe how device groups support AI and ML in vSphere 8 Describe how device virtualization extensions support AI and ML in vSphere 8 vSphere Distributed Services Engine Describe the benefits of Distributed Services Engine Explain how Distributed Services Engine works Recognize use cases for Distributed Services Engine Install ESXi on a host equipped with a DPU View DPU information in vSphere Client Add an ESXi host equipped with a DPU to a cluster Update an ESXi host equipped with a DPU using vSphere Lifecycle Manager Create a vSphere Distributed Switch for network offloads Add a host with a DPU to the vSphere Distributed Switch Configure a VM to use Uniform Passthrough Mode vSphere and vCenter Management Review the improvements to the communication between vCenter and ESXi hosts Review the enhancements to the vCenter recovery process ESXi Enhancements Describe the function of the central configuration store in ESXi Explain how ConfigStore affects your interaction with ESXi configuration files Recognize the supported system storage partition configuration on ESXi 8.0 Identify devices supported for system storage on ESXi 8.0 Configure an RDMA host local device on ESXi vSphere Storage Describe the vSAN Express Storage Architecture Recognize the benefits of using vSAN Express Storage Architecture Describe the benefits of using NVMe Recognize the support for NVMe devices in vSphere Guest OS and Workloads Review the enhancements of the latest virtual hardware versions Describe the features introduced with virtual hardware version 20 Create a snapshot of a VM with an NVDIMM device Resource Management View energy and carbon emission metrics in vRealize Operations Manager Describe the VMware vSphere Memory Monitoring and Remediation (vMMR) functionality Describe how vMMR enhances the performance of vSphere DRS Security and Compliance Describe how to handle vTPM secrets when cloning a VM Manage OVF templates for VMs that are configured with vTPM Deploy an OVF template with vTPM Describe the enhancements to trusted binary enforcement in ESXi Describe ESXi 8 enhanced security features vSphere Lifecycle Manager Describe the enhancements to life cycle management of standalone ESXi hosts Manage the configuration profiles of ESXi hosts in a cluster with vSphere Lifecycle Manager Use Auto Deploy to boot a host with the desired image and configuration specifications Upgrade multiple ESXi hosts in a cluster in parallel Stage an ESXi host image prior to remediation Auto Deploy Manage custom host certificates using Auto Deploy vSphere with Tanzu Describe the features of the Tanzu Kubernetes Grid 2.0 offering Announcing vSphere+ Describe the functionality and benefits of vSphere+

Duration 3 Days 18 CPD hours This course is intended for Experienced system administrators and cloud administrators who are already familiar with vRealize Automation Overview By the end of the course, you should be able to meet the following objectives: Learn installation best practices and troubleshoot installation failures Verify the correct DNS configuration Examine main logs and collect log bundles Examine the Kubernetes pods in the vRealize Automation architecture Troubleshoot common errors that prevent successful deployments Troubleshoot YAML code errors in VMware cloud templates Troubleshoot cloudConfig code errors in VMware cloud templates Troubleshoot VMware Identity Manager™ configuration errors Troubleshoot common errors in VMware vRealize Orchestrator™ workflows Use the vRealize Orchestrator debugger Use log outputs from vRealize Orchestrator Troubleshoot problems in custom resources Troubleshoot problems in resource actions Troubleshoot action-based extensibility (ABX) actions Integrate vRealize Automation with VMware vRealize Log Insight™ Integrate vRealize Automation with VMware vRealize Operations Manager™ Use VMware vRealize Lifecycle Manager™ to troubleshoot vRealize Automation problems with licenses and certificates Configure and replace certificates This three-day, hands-on training course provides you with the advanced knowledge, skills, and tools to achieve competency in troubleshooting VMware vRealize Automation™. vRealize Automation can be used to automate the delivery of virtual machines, applications, and personalized IT services across different data centers and hybrid cloud environments. This course will enable you to troubleshoot common problems with hands-on lab problems. Course Introduction Introductions and course logistics Course objectives Troubleshooting vRealize Automation Installation Issues vRealize Automation installation overview vRealize Automation installation best practices Troubleshooting installation failures vRealize Automation General Troubleshooting Verifying the DNS configuration settings in vRealize Automation and vSphere Examining the main logs in the user interface Collecting a log bundle Using vracli commands Examining the pods in the vRealize Automation Kubernetes architecture Dumping a log from a vRealize Automation Kubernetes pod Stopping and restarting a vRealize Automation Kubernetes pod vRealize Automation Cloud Templates and Deployment Troubleshooting Overview of provisioning and placement workflows Examining a deployment history Troubleshooting deployment issues Using deployment Dev mode Troubleshooting YAML code Troubleshooting problems with cloudConfig vRealize Automation Identity Manager Architecture and Cluster Architecture Authentication workflow in vRealize Automation Connector high availability for the authentication Architecture of a VMware Identity Manager cluster Key VMware Identity Manager commands and log files Troubleshooting a VMware Identity Manager problem Key vRealize Automation components Architecture of the vRealize Automation cluster vRealize Automation node failover scenario vRealize Automation cluster shutdown and startup process Virtual machine provisioning workflow Troubleshooting vRealize Orchestrator Workflows Overview of vRealize Orchestrator and vRealize Automation communications Using the vRealize Orchestrator debugger Using vRealize Orchestrator log output Troubleshooting vRealize Orchestrator binding errors Troubleshooting vRealize Orchestrator logic errors Troubleshooting vRealize Orchestrator payload errors Troubleshooting custom resource errors Troubleshooting resource action errors Troubleshooting Action Based Extensibility (ABX) Actions Overview of ABX actions Troubleshooting ABX actions vRealize Automation Integration with vRealize Tools Integrating vRealize Automation and vRealize Log Insight Integrating vRealize Automation and vRealize Operations Manager Using vRealize Operations Manager to monitor vRealize Automation vRealize Automation Certificate Management Managing vRealize Automation certificates Creating certificate requests with vRealize Lifecycle Manager Using Microsoft Certificate Services to create vRealize Automation certificates Replacing vRealize Automation certificates Additional course details:Notes Delivery by TDSynex, Exit Certified and New Horizons an VMware Authorised Training Centre (VATC) Nexus Humans VMware vRealize Automation: Troubleshooting [V8.6] training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the VMware vRealize Automation: Troubleshooting [V8.6] course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 5 Days 30 CPD hours This course is intended for System administrators, IT security administrators, IT security engineers, and other professionals responsible for designing, implementing, maintaining, and managing the security of Red Hat Enterprise Linux systems and ensuring their compliance with the organization's security policies. Be a Red Hat Certified Engineer (RHCE©), or demonstrate equivalent Red Hat Enterprise Linux knowledge and experience. Overview Students that complete this course should be able to demonstrate these skills: - Analyze and remediate system compliance using OpenSCAP and SCAP Workbench, employing and customizing baseline policy content provided with Red Hat Enterprise Linux. - Monitor security-relevant activity on your systems with the kernel's audit infrastructure. - Explain and implement advanced SELinux techniques to restrict access by users, processes, and virtual machines. - Confirm the integrity of files and their permissions with AIDE. - Prevent unauthorized USB devices from being used with USBGuard. - Protect data at rest but provide secure automatic decryption at boot using NBDE. - Proactively identify risks and misconfigurations of systems and remediate them with Red Hat Insights. - Analyze and remediate compliance at scale with OpenSCAP, Red Hat Insights, Red Hat Satellite, and Red Hat Ansible Tower. This course is ideal for security administrators and system administrators who need to manage the secure operation of servers running Red Hat© Enterprise Linux©, whether deployed on physical hardware, as virtual machines, or as cloud instances. Maintaining security of computing systems is a process of managing risk through the implementation of processes and standards backed by technologies and tools. In this course, you will discover and understand the resources that can be used to help you implement and comply with your security requirements. This course is based on Red Hat Enterprise Linux 7.5, Red Hat Satellite 6.3, Red Hat Ansible© Engine 2.5, Red Hat Ansible Tower 3.2, and Red Hat Insights. 1 - MANAGE SECURITY AND RISK Define strategies to manage security on Red Hat Enterprise Linux servers. 2 - AUTOMATE CONFIGURATION AND REMEDIATION WITH ANSIBLE Remediate configuration and security issues with Ansible Playbooks. 3 - PROTECT DATA WITH LUKS AND NBDE Encrypt data on storage devices with LUKS and use NBDE to manage automatic decryption when servers are booted. 4 - RESTRICT USB DEVICE ACCESS Protect system from rogue USB device access with USBGuard. 5 - CONTROL AUTHENTICATION WITH PAM Manage authentication, authorization, session settings, and password controls by configuring pluggable authentication modules (PAMs). 6 - RECORD SYSTEM EVENTS WITH AUDIT Record and inspect system events relevant to security, using the Linux kernel's audit subsystem and supporting tools. 7 - MONITOR FILE SYSTEM CHANGES Detect and analyze changes to a server's file systems and their contents using AIDE. 8 - MITIGATE RISK WITH SELINUX Improve security and confinement between processes by using SELinux and advanced SELinux techniques and analyses. 9 - MANAGE COMPLIANCE WITH OPENSCAP Evaluate and remediate a server's compliance with security policies by using OpenSCAP. 10 - AUTOMATE COMPLIANCE WITH RED HAT SATELLITE Automate and scale your ability to perform OpenSCAP checks and remediate compliance issues using Red Hat Satellite. 11 - ANALYZE AND REMEDIATE ISSUES WITH RED HAT INSIGHTS Identify, detect, and correct common issues and security vulnerabilities with Red Hat Enterprise Linux systems by using Red Hat Insights. 12 - PERFORM A COMPREHENSIVE REVIEW Review the content covered in this course by completing hands-on review exercises. Additional course details: Nexus Humans Red Hat Security - Linux in Physical, Virtual, and Cloud (RH415) training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Red Hat Security - Linux in Physical, Virtual, and Cloud (RH415) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.