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Duration 2 Days 12 CPD hours This course is intended for This course is recommended for administrators and engineers. Overview What you'll learn: Prepare the Azure environment for secure integration with Citrix DaaS. Deploy and manage Virtual Delivery Agent machines in Microsoft Azure using Machine Creation Services. Integrate Citrix Cloud and Citrix DaaS with Microsoft Azure Active Directory. Design Machine Catalogs and virtual machines on Microsoft Azure Resource Manager. Provide remote access with Citrix StoreFront and Citrix Gateway on Microsoft Azure. In this course you willLearn to deploy and manage your Citrix DaaS deployment on Microsoft Azure. Gain the skills to plan your machine catalog and virtual machine design based in Microsoft's public cloud and get hands-on practice deploying those machines using Machine Creation Services. You will also learn about additional Azure considerations including maintenance and power management which are critical in a cloud environment. For remote access, you will learn to configure Citrix StoreFront and Citrix Gateway on the Azure platform. This course focuses on Microsoft Azure as a Citrix Cloud resource location however concepts are relevant to both Citrix Cloud and fully managed Citrix DaaS sites. Module 1: Introduction to Citrix DaaS on Microsoft Azure Partnering for Success Module 2: Planning - Citrix DaaS Resource Location on Microsoft Azure Overview of Citrix DaaS Components Creating a Citrix DaaS Deployment Overview Module 3: Planning - Microsoft Azure Overview Azure Virtual Network Structure Azure Virtual Network Connectivity Azure Virtual Resources Azure Active Directory Identity and Access Management Azure Active Directory Options and Considerations Module 4: Planning - Deploying Citrix DaaS on Microsoft Azure Citrix DaaS Resource Locations in Azure Citrix DaaS Components in Azure Creating and Managing Workloads in an Azure Resource Location Module 5: Planning - Provide Access to End Users Providing Access to Resources in Citrix Cloud Citrix Gateway Deployment Options Deploying Citrix Gateway or ADC in Azure GSLB and StoreFront Optimal Gateway in Hybrid Environments Module 6: Rollout - Citrix DaaS Deployment on Microsoft Azure Citrix Workspace App Rollout Preparing Migration of End-Users to Workspace Platform Module 7: Managing - Citrix DaaS Workloads on Microsoft Azure Maintaining Citrix Gateway Backup and Monitoring in Azure Maintaining Master Images in Azure Monitoring VDAs in Manage Console and Azure Module 8: Optimize - Citrix DaaS on Microsoft Azure Managing Azure Costs Using Azure Pricing Calculator - Instructor Demo Student Exercise - Calculate a case Additional course details: Nexus Humans CWS-251 Implement Citrix DaaS on Microsoft Azure 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 CWS-251 Implement Citrix DaaS on Microsoft Azure 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 This course is intended for System administrators who are either new to JBoss or have experience with JBoss Enterprise Application Platform 5. Base experience with system administration on Microsoft Windows, UNIX, or Linux© operating systems. Understanding of hardware and networking. Note: No prior knowledge of Java, scripting, or JBoss Developer Studio is required. Overview Upon successful completion of this course, students will be able to take the Red Hat Certified JBoss Administration (RHCJA) Exam. In this course, you'll discover the best practices for installing and configuring Red Hat© JBoss© Enterprise Application Platform (JBoss EAP) 7. Through hands-on labs, you'll learn the essential, real-world tasks that you need to know as a system administrator to effectively deploy and manage applications on JBoss EAP. This course will help prepare you to take the Red Hat Certified Specialist in Enterprise Application Server Administration exam. 1 - OVERVIEW OF JBOSS ENTERPRISE APPLICATION PLATFORM Learn the concepts and terminology of JBoss© Enterprise Application Platform 6, and install and run a JBoss Enterprise Application Platform instance. 2 - CONFIGURE JBOSS ENTERPRISE APPLICATION PLATFORM IN STANDALONE MODE Understand the directory structure of standalone mode and the standalone.xml configuration file, and deploy an application onto a standalone server. 3 - CONFIGURE JBOSS ENTERPRISE APPLICATION PLATFORM IN DOMAIN MODE Set up a domain, including a domain controller managing multiple host controllers. Also learn how to deploy an application onto a domain. 4 - CONFIGURE SERVERS Define a server group on a host, add servers to a server group, and deploy an application to a server group. 5 - USE THE CLI TOOL Learn how the command-line Interface tool can be used to script administrative tasks. 6 - THE DATASOURCE SUBSYSTEM Understand database connection pools in JBoss Enterprise Application Platform and how to configure the datasource subsystem. Learn how to deploy a Java? Database Connectivity (JDBC) driver and define a datasource. 7 - THE LOGGING SUBSYSTEM Configure the logging subsystem, including configuring the built-in handlers and loggers. 8 - THE MESSAGING SUBSYSTEM Understand JMS and HornetQ, including how to define and configure connection factories and destinations (topics and queues). 9 - THE SECURITY SUBSYSTEM Configure the security subsystem, including securing the management interfaces, securing an application, and securing a JMS destination. Also learn how to define an Lightweight Directory Access Protocol (LDAP) and database security realm. 10 - JVM CONFIGURATION Configure the JVM for both standalone and domain modes. 11 - MIGRATING APPLICATIONS TO JBOSS ENTERPRISE APPLICATION PLATFORM 6 Understand classpath and module dependencies, JPA issues, updating security settings, and other tips on how to migrate an application to JBoss Enterprise Application Platform 6. 12 - THE WEB SUBSYSTEM Configure the HTTP and HTTPS Connectors, set up an SSL connection, and configure an AJP Connector. 13 - INTRODUCTION TO CLUSTERING Set up JBoss Enterprise Application Platform 6 in a cluster in both standalone and domain mode.

Duration 3 Days 18 CPD hours This course is intended for This class is intended for the following customer job roles: Cloud architects, administrators, and SysOps personnel Cloud developers and DevOps personnel Overview This course teaches participants the following skills: Plan and implement a well-architected logging and monitoring infrastructure Define Service Level Indicators (SLIs) and Service Level Objectives (SLOs) Create effective monitoring dashboards and alerts Monitor, troubleshoot, and improve Google Cloud infrastructure Analyze and export Google Cloud audit logs Find production code defects, identify bottlenecks, and improve performance Optimize monitoring costs This course teaches you techniques for monitoring, troubleshooting, and improving infrastructure and application performance in Google Cloud. Guided by the principles of Site Reliability Engineering (SRE), and using a combination of presentations, demos, hands-on labs, and real-world case studies, attendees gain experience with full-stack monitoring, real-time log management and analysis, debugging code in production, tracing application performance bottlenecks, and profiling CPU and memory usage. Introduction to Google Cloud Monitoring Tools Understand the purpose and capabilities of Google Cloud operations-focused components: Logging, Monitoring, Error Reporting, and Service Monitoring Understand the purpose and capabilities of Google Cloud application performance management focused components: Debugger, Trace, and Profiler Avoiding Customer Pain Construct a monitoring base on the four golden signals: latency, traffic, errors, and saturation Measure customer pain with SLIs Define critical performance measures Create and use SLOs and SLAs Achieve developer and operation harmony with error budgets Alerting Policies Develop alerting strategies Define alerting policies Add notification channels Identify types of alerts and common uses for each Construct and alert on resource groups Manage alerting policies programmatically Monitoring Critical Systems Choose best practice monitoring project architectures Differentiate Cloud IAM roles for monitoring Use the default dashboards appropriately Build custom dashboards to show resource consumption and application load Define uptime checks to track aliveness and latency Configuring Google Cloud Services for Observability Integrate logging and monitoring agents into Compute Engine VMs and images Enable and utilize Kubernetes Monitoring Extend and clarify Kubernetes monitoring with Prometheus Expose custom metrics through code, and with the help of OpenCensus Advanced Logging and Analysis Identify and choose among resource tagging approaches Define log sinks (inclusion filters) and exclusion filters Create metrics based on logs Define custom metrics Link application errors to Logging using Error Reporting Export logs to BigQuery Monitoring Network Security and Audit Logs Collect and analyze VPC Flow logs and Firewall Rules logs Enable and monitor Packet Mirroring Explain the capabilities of Network Intelligence Center Use Admin Activity audit logs to track changes to the configuration or metadata of resources Use Data Access audit logs to track accesses or changes to user-provided resource data Use System Event audit logs to track GCP administrative actions Managing Incidents Define incident management roles and communication channels Mitigate incident impact Troubleshoot root causes Resolve incidents Document incidents in a post-mortem process Investigating Application Performance Issues Debug production code to correct code defects Trace latency through layers of service interaction to eliminate performance bottlenecks Profile and identify resource-intensive functions in an application Optimizing the Costs of Monitoring Analyze resource utilization cust for monitoring related components within Google Cloud Implement best practices for controlling the cost of monitoring within Google Cloud

Duration 3 Days 18 CPD hours This course is intended for This course is ideal for developers and engineers including: Cloud administrators Cloud solution architects Customer sales engineers DevOps engineers Sales engineers Systems engineers Technical solutions architects Overview After completing the course, you should be able to: Explain business and technical challenges of going to the cloud Understand benefits of an application-centric hybrid cloud multicloud management platform Navigate Cisco CloudCenter Suite architecture Understand Cisco CloudCenter Suite administrative capabilities including cloud management, multitenancy, governance, and policy enforcement Describe application lifecycle management and provisioning in cloud Describe how to use Cisco CloudCenter Suite to manage the workloads in multicloud The course, Mulitcloud Management with Cisco© CloudCenter Suite (CLDCCS) v1.0 is an intensive training course that teaches you to securely design, automate, and deploy applications across multiple clouds while optimizing cost and compliance with comprehensive reporting, visibility, and policy-enforcement. Through a combination of lessons with hands-on lab exercises, you will learn to simplify the lifecycle management of multicloud applications, workflows, and their infrastructure Understanding Cloud Transitions Overview of Traditional IT Introducing Cisco CloudCenter Suite Cisco CloudCenter Suite Definition Setting Up Cisco CloudCenter Workload Manager Artifact Repository Overview and Configuration Understanding User Administration and Multitenancy in Cisco CloudCenter Suite Cisco CloudCenter Suite User Roles Grasping Application Modeling in Cisco CloudCenter Workload Manager Model an Application Identifying Resource Placement Callouts and Lifecycle Actions in Cisco CloudCenter Workload Manager Resource Placement and Validation Callout Understanding Application Deployment Framework in Cisco CloudCenter Workload Manager Workload Manager Application Parameters Exploring Application Services in Cisco CloudCenter Workload Manager Application Services Framework Integrating Cisco CloudCenter Workload Manager with Cisco Application-Centric Infrastructure Configure CloudCenter Workload Manager for Cisco ACI Introducing Application Management in Cisco CloudCenter Workload Manager Cisco CloudCenter Workload Manager Actions Library Exploring Advanced Features in CloudCenter Workload Manager Scheduling an Application in Cisco CloudCenter Workload Manager Comprehending Policies and Tagless Governance in CloudCenter Workload Manager Cisco CloudCenter Workload Manager Policies Introducing Action Orchestrator and Cost Optimizer in Cisco CloudCenter Suite Action Orchestrator in Cisco CloudCenter Suite Lab outline Explore Cisco CloudCenter Suite Admin GUI Discover Cisco CloudCenter Workload Manager GUI Create Cisco CloudCenter Workload Manager Repository Design Deployment Environments in Cisco CloudCenter Workload Manager Create Images in Cisco CloudCenter Workload Manager Form Cost Bundles and Usage Plans in Cisco CloudCenter Workload Manager Explore Multitenancy in Cisco CloudCenter Suite Model and Deploy Two-Tier Application Model and Deploy Multitier Application Perfect and Arrange Multitier Application on Docker Model and Deploy Application on Kubernetes Cloud Deploy Application in Hybrid Cloud Arrange Application Using Automated Resource Placement Perform Lifecycle Actions on Deployed Applications Create User-Defined Parameters and Explore Macros Understand Application Services in Cisco CloudCenter Workload Manage Benchmark, Schedule, and Share Applications in Cisco CloudCenter Workload Manager Continuous Integration/Continuous Delivery (CI/CD) Project Board Manage Policies in Cisco CloudCenter Workload Manager Manage System Tags and Governance in Cisco CloudCenter Workload Manager Explore Action Orchestrator Explore Cost Optimizer Additional course details: Nexus Humans Cisco Multicloud Management with Cisco CloudCenter Suite (CLDCCS) v1.0 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 Cisco Multicloud Management with Cisco CloudCenter Suite (CLDCCS) v1.0 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 ideal for developers, engineers, and others including: Cloud administrators , Cloud solution architects , Customer sales engineers , DevOps engineers , Sales engineers , Systems engineers, Technical solutions architects. Overview After taking this course, you should be able to: Explain business and technical challenges of going to the cloud Understand benefits of an application-centric hybrid cloud multicloud management platform Navigate Cisco CloudCenter Suite architecture Understand Cisco CloudCenter Suite administrative capabilities including cloud management, multi-tenancy, governance, and policy enforcement Describe application lifecycle management and provisioning in cloud Describe how to use Cisco CloudCenter Suite to manage the workloads in multicloud The course, Mulitcloud Automation and Orchestration with Cisco CloudCenter Suite (CLDAO) v1.0 teaches you how to configure simplified orchestration and workflow automation that provides seamless integration within the Cisco© CloudCenter suite. Through lessons and hands-on experiences, you will learn to use the tools of the CloudCenter Suite to streamline business processes, automate tasks, and increase efficiency in business processes. Introducing Cisco CloudCenter Suite Action Orchestrator Cisco CloudCenter Suite Architecture Defining Action Orchestrator User Management and Security Considerations Cisco CloudCenter Suite User Management and Security Defining Cisco CloudCenter Suite Action Orchestrator Adapters Action Orchestrator Adapter Creation Examining Action Orchestrator Integrations and Supported APIs Cisco CloudCenter Suite Action Orchestrator APIs

Duration 3 Days 18 CPD hours This course is intended for This advanced course is for IT professionals tasked with administering a Spectrum Scale system. Overview Please see Overview This course is intended for IT professionals tasked with administering a Spectrum Scale system. It includes information on installing, configuring and monitoring a Spectrum Scale cluster. Migrating to IBM Spectrum Scale 4.2Spectrum Scale 4.2 GUIMulti-clusterClustered NFSCluster Export Services for multi-protocol supportSMB Protocol SupportNFS Support in CES; Ganesha overview/performanceActive File ManagementAFM-Based Disaster Recovery (DR) and Asynchronous DRPlanning LTFS and GPFS environment for data archivingFile Placement OptimizerIBM© GPFS-FPO and integration with GPFS Hadoop connectorIBM© Spectrum Scale Call HomeMonitoring and performance tuningFlash Cache metadata migration

Duration 3 Days 18 CPD hours This course is intended for Data Science for Marketing Analytics is designed for developers and marketing analysts looking to use new, more sophisticated tools in their marketing analytics efforts. It'll help if you have prior experience of coding in Python and knowledge of high school level mathematics. Some experience with databases, Excel, statistics, or Tableau is useful but not necessary. Overview By the end of this course, you will be able to build your own marketing reporting and interactive dashboard solutions. The course starts by teaching you how to use Python libraries, such as pandas and Matplotlib, to read data from Python, manipulate it, and create plots, using both categorical and continuous variables. Then, you'll learn how to segment a population into groups and use different clustering techniques to evaluate customer segmentation.As you make your way through the course, you'll explore ways to evaluate and select the best segmentation approach, and go on to create a linear regression model on customer value data to predict lifetime value. In the concluding sections, you'll gain an understanding of regression techniques and tools for evaluating regression models, and explore ways to predict customer choice using classification algorithms. Finally, you'll apply these techniques to create a churn model for modeling customer product choices. Data Preparation and Cleaning Data Models and Structured Data pandas Data Manipulation Data Exploration and Visualization Identifying the Right Attributes Generating Targeted Insights Visualizing Data Unsupervised Learning: Customer Segmentation Customer Segmentation Methods Similarity and Data Standardization k-means Clustering Choosing the Best Segmentation Approach Choosing the Number of Clusters Different Methods of Clustering Evaluating Clustering Predicting Customer Revenue Using Linear Regression Understanding Regression Feature Engineering for Regression Performing and Interpreting Linear Regression Other Regression Techniques and Tools for Evaluation Evaluating the Accuracy of a Regression Model Using Regularization for Feature Selection Tree-Based Regression Models Supervised Learning: Predicting Customer Churn Classification Problems Understanding Logistic Regression Creating a Data Science Pipeline Fine-Tuning Classification Algorithms Support Vector Machine Decision Trees Random Forest Preprocessing Data for Machine Learning Models Model Evaluation Performance Metrics Modeling Customer Choice Understanding Multiclass Classification Class Imbalanced Data Additional course details: Nexus Humans Data Science for Marketing Analytics 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 Data Science for Marketing Analytics 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 3 Days 18 CPD hours This course is intended for This intermediate course is for all computer professionals who will use z/OS UNIX. Overview Discuss the role of z/OS in an open systems environmentIdentify the basic terms used in z/OS UNIXDefine the components of z/OS UNIXExplain major functions provided in z/OS UNIXDiscuss opportunities for applications in a z/OS UNIX environmentIdentify z/OS base elements and optional features that make up z/OS UNIXUse the two interactive interfaces available to access the services This course describes how open standards are implemented in a z/OS system by z/OS UNIX. UNIX System Services are introduced, and the role of z/OS as a server in the open systems environment is discussed. Day 1 Welcome and introduction Unit 1. z/OS UNIX overview Unit 2. Introduction to z/OS UNIX Unit 3. Hierarchical file system Exercises Day 2 Unit 4. z/OS UNIX shell and utilities Unit 5. z/OS UNIX shell commands Unit 6. Working with the shell Unit 7. Functions in z/OS UNIX Exercises Day 3 Unit 8. Working with the z/OS UNIX environment Exercises

Duration 5 Days 30 CPD hours This course is intended for Typical candidates for this course are IT professionals who deploy Aruba WLAN with advanced features and individuals who need a basic understanding of AirWave. Overview Upon completion of this course, students will be able to:Explain the integration Mobility Masters and Mobility controllersDescribe redundancy giving the user seamless failoverSetup secure guest access using MultizoneExplain the uses and advantages of clusteringDescribe user mobility in the wireless spectrumIntegrate voice over WiFi and give QOSExplain how roles are assigned to users wireless or wiredLearn to setup remote access using RAPs or VIADescribe how to create a mesh clusterLearn the advantages given to AirGroup when leveraged on an Aruba networkIntegrating wire users into the security given to wireless usersLearn how to use AirWave to monitor the health of the networkLearn how to use AirWave to troubleshoot clientExplain AirWave?s Visual RF feature as well as alerts and triggers This course teaches the knowledge, skills and practical experience required to set up and configure advanced features on Aruba WLAN utilizing the AOS 8.X architecture and features. This course includes lectures and labs which provide the technical understanding and hands-on experience of configuring a redundant Mobility Master with two controllers and two APs. Participants will learn how install a redundant Aruba WLAN network with clustering while using many features like Multizone for guest access, voice optimization and tunneled node. This course includes the AirWave management system and troubleshooting commands. The SWDI course provides the underlying material required to prepare candidates for the Aruba Certified Mobility Professional (ACMP) V8 certification exam. IntroductionMobility Master RedundancyMobility Master and MC OperationsMultizoneIntroduction to MC clustersMobilityRole DerivationRemote AccessVoice OptimizationMeshAdministrationOperationsAirGroupTunneled NodeAirWave IntroductionAirWave Network HealthAirWave Client and Device TroubleshootingAirWave VisualRF, Reports and Alerts