5525 Courses delivered Live Online

Duration 2 Days 12 CPD hours Overview Understand why Blockchain is needed and where Explore the major components of BlockchainLearn about Hyperledger Fabric and the structure of the Hyperledger ArchitectureLean the features of the Fabric model including chaincode, SDKs, Ledger, Security and Membership ServicesPerform comprehensive labs on writing chaincodeExplore the architecture of Hyperledger FabricUnderstand and perform in depth labs on Bootstrapping the NetworkPerform comprehensive labs to integrate/develop an application with Hyperledger Fabric running a smart contractBuild applications on Hyperledger FabricCourse Outline: This training course has been created to walk you through Chaincode Development, Testing, and Deployment for a Hyperledger Fabric Network catering specifically toward Golang written Chaincode (Fabric?s original Chaincode Language). Additionally as an Application Developer you will learn how to write, and prepare Client Applications using the most mature Standard Development Kit in Hyperledger Fabric, NodeJS. Blockchain Basics (Overview)Hyperledger Fabric Development EnvironmentKnowing the Difference: ComposerChaincode Use CasesChaincode BasicsGolang Shim DevelopmentDatabases for the DeveloperChaincode Dev. Deployment and InteractionsClients & SDK Development: Fabric-NetworkClients & SDK Development: Fabric-Client InteractionsLogging and Monitoring

Duration 5 Days 30 CPD hours This course is intended for Technology ConsultantSystem AdministratorSystem ArchitectHelp Desk / COE Support Overview Explain the architecture of SAP NetWeaver AS JavaStart and stop SAP NetWeaver AS JavaCarry out basic configurations for SAP NetWeaver AS JavaClassify network security conceptsSet up SSL encryption for SAP NetWeaver AS JavaExplain the architecture of the User Management EngineConfigure the User Management EngineCarry out user and authorization maintenanceUnderstand and change the standard logon procedure of SAP NetWeaver AS JavaMaintain destinations and the JCo RFC ProviderUnderstand the architecture and the tasks of the SAP NetWeaver Development InfrastructureExplain the process flow of the development process using the SAP NetWeaver Development InfrastructureSpecify the options for monitoring SAP NetWeaver AS JavaConnect SAP NetWeaver AS Java to a central Monitoring systemDisplay Monitoring and logging data using the SAP NetWeaver AdministratorImplement corrections for SAP NetWeaver AS Java In this course, students learn how to explain the architecture of SAP NetWeaver AS Java, carry out basic configurations for SAP NetWeaver AS Java, and much more. Fundamental Concepts of Java Describing the Fundamental Concepts of Java Describing the Architecture of the SAP NetWeaver Application Server (SAP NetWeaver AS) Outlining the Java Cluster Architecture Describing the Internal Structure of SAP NetWeaver AS for Java SAP NetWeavear AS for Java Start and Stop Procedures Starting and Stopping Procedures in SAP NetWeaver AS for Java Evaluating the Tools for Starting and Stopping an SAP System Evaluating Load Balancing Options in SAP NetWeaver AS for Java Operating the Java Startup and Control Framework Analyzing the Logs of Start and Stop Processes in SAP NetWeaver AS for Java Basic Configuration of SAP NetWeaver AS for Java Identifying the Administration Tools Used in Configuration Maintaining the Basic Configuration of SAP NetWeaver AS for Java with the Config Tool Configuring SAP NetWeaver AS for Java with SAP NetWeaver Administrator Configuring the Properties of the Central Services Instance Administering the Internet Communication Manager (ICM) Process Infrastructure Security Describing Network Security Setting Up the Secure Sockets Layer (SSL) User and Authorization Administration Configuring the SAP User Management Engine (UME) Maintaining Users and Groups Managing Java Authorization Administrating Special Principles Configuring the Logon Procedure in SAP NetWeaver AS for Java Java Connectors and Destinations Creating Connections to Other Systems Creating Connections to Other Systems with J2EE Connector Architecture (JCA) Change Management and Software Logistics Structuring the Java Development Approach Describing the Components of SAP NetWeaver Development Infrastructure Developing and Releasing Java Changes with SAP NetWeaver Development Infrastructure Transporting Java Developments Monitoring Monitoring SAP NetWeaver AS for Java Connecting to a Central Monitoring System (CEN) Configuring Availability Monitoring Configuring the Log and Trace Files Monitoring a System with SAP Solution Manager Software Maintenance Preparing for Software Maintenance Describing Java Support Packages, Stacks, and Patches Deploying Corrections with Software Update Manager (SUM) in SAP NetWeaver AS for Java Deploying Java Archives with Alternative Tools Outlining the Backup Strategy in SAP NetWeaver AS for Java

Duration 1 Days 6 CPD hours This course is intended for Individuals planning to deploy applications and create application environments on Google Cloud. Developers, systems operations professionals, and solution architects getting started with Google Cloud. Executives and business decision makers evaluating the potential of Google Cloud to address their business needs. Overview Identify the purpose and value of Google Cloud products and services. Interact with Google Cloud services. Describe ways in which customers have used Google Cloud. Choose among and use application deployment environments on Google Cloud: App Engine, Google Kubernetes Engine, and Compute Engine. Choose among and use Google Cloud storage options: Cloud Storage, Cloud SQL, Cloud Bigtable, and Firestore. Make basic use of BigQuery, Google's managed data warehouse for analytics. This course uses lectures, demos, and hands-on labs to give you an overview of Google Cloud products and services so that you can learn the value of Google Cloud and how to incorporate cloud-based solutions into your business strategies. Introducing Google Cloud Platform Explain the advantages of Google Cloud Platform. Define the components of Google's network infrastructure, including: Points of presence, data centers, regions, and zones. Understand the difference between Infrastructure-as-a-Service (IaaS) and Platform-as-a-Service (PaaS). Getting Started with Google Cloud Platform Identify the purpose of projects on Google Cloud Platform. Understand the purpose of and use cases for Identity and Access Management. List the methods of interacting with Google Cloud Platform. Lab: Getting Started with Google Cloud Platform. Google Compute Engine and Networking Identify the purpose of and use cases for Google Compute Engine. Understand the basics of networking in Google Cloud Platform. Lab: Deploying Applications Using Google Compute Engine. Google Cloud Platform Storage Options Understand the purpose of and use cases for: Google Cloud Storage, Google Cloud SQL, and Google Cloud Bigtable. Learn how to choose between the various storage options on Google Cloud Platform. Lab: Integrating Applications with Google Cloud Storage. Google Container Engine Define the concept of a container and identify uses for containers. Identify the purpose of and use cases for Google Container Engine and Kubernetes. Introduction to Hybrid and Multi-Cloud computing (Anthos). Lab: Deploying Applications Using Google Container Engine. Google App Engine and Google Cloud Datastore Understand the purpose of and use cases for Google App Engine and Google Cloud Datastore. Contrast the App Engine Standard environment with the App Engine Flexible environment. Understand the purpose of and use cases for Google Cloud Endpoints. Lab: Deploying Applications Using App Engine and Cloud Datastore. Deployment and Monitoring Understand the purpose of template-based creation and management of resources. Understand the purpose of integrated monitoring, alerting, and debugging. Lab: Getting Started with Stackdriver and Deployment Manager. Big Data and Machine Learning Understand the purpose of and use cases for the products and services in the Google Cloud big data and machine learning platforms. Lab: Getting Started with BigQuery. Summary and Review Summary and Review. What's Next?.

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Duration 5 Days 30 CPD hours This course is intended for The Microsoft Technology Associate (MTA) is Microsoft?s newest suite of technology certification exams that validate fundamental knowledge needed to begin building a career using Microsoft technologies. This program provides an appropriate entry point to a future career in technology and assumes some hands-on experience or training but does not assume on-the-job experience. Overview This five-day Training 2-Pack helps you prepare for Microsoft Technology Associate Exams 98-366 and 98-367, and build an understanding of these topics: Network Infrastructures, Network Hardware, Protocols and Services, Security Layers, Operating System Security, Network Security, Security Software. These courses leverage the same content as found in the Microsoft Official Academic Courses (MOAC) for these exams. Understand Network InfrastructuresUnderstand Network HardwareUnderstand Protocols and ServicesUnderstand Security LayersUnderstand Operating System SecurityUnderstand Network SecurityUnderstand Security Software UNDERSTANDING LOCAL AREA NETWORKINGDEFINING NETWORKS WITH THE OSI MODELUNDERSTANDING WIRED AND WIRELESS NETWORKSUNDERSTANDING INTERNET PROTOCOLIMPLEMENTING TCP/IP IN THE COMMAND LINEWORKING WITH NETWORKING SERVICESUNDERSTANDING WIDE AREA NETWORKSDEFINING NETWORK INFRASTRUCTURES AND NETWORK SECURITYUNDERSTANDING SECURITY LAYERSAUTHENTICATION, AUTHORIZATION, AND ACCOUNTINGUNDERSTANDING SECURITY POLICYUNDERSTANDING NETWORK SECURITYPROTECTING THE SERVER AND CLIENT

Duration 5 Days 30 CPD hours This course is intended for Security Professionals working with Kubernetes Clusters Container Orchestration Engineers DevOps Professionals Overview In this course, students will learn and practice essential Kubernetes concepts and tasks in the following sections: Cloud Security Fundamentals Cluster Hardening System Hardening Minimize Microservice Vulnerabilities Supply Chain Security Disaster Recovery Secure Back-up and Restore This class prepares students for the Certified Kubernetes Security Specialist (CKS) exam. Kubernetes is a Cloud Orchestration Platform providing reliability, replication, and stabilitywhile maximizing resource utilization for applications and services. By the conclusion of this hands-on, vendor agnostic training you will be equipped with a thorough understanding ofcloud security fundamentals, along with the knowledge, skills and abilities to secure a Kubernetes cluster, detect threats, and properly resolve a security catastrophe. This courseincludes hands-on instruction which develops skills and knowledge for securing container-based applications and Kubernetes platforms, during build, deployment, and runtime. We prioritizecovering all objectives and concepts necessary for passing the Certified Kubernetes Security Specialist (CKS) exam. You will be provided the components necessary to assemble your ownhigh availability Kubernetes environment and harden it for your security needs. Learning Your Environment Underlying Infrastructure Using Vim Tmux Cloud Security Primer Basic Principles Threat Analysis Approach CIS Benchmarks Securing your Kubernetes Cluster Kubernetes Architecture Pods and the Control Plane Kubernetes Security Concepts Install Kubernetes using kubeadm Configure Network Plugin Requirements Kubeadm Basic Cluster Installing Kubeadm Join Node to Cluster Kubeadm Token Manage Kubeadm Tokens Kubeadm Cluster Upgrade Securing the kube-apiserver Configuring the kube-apiserver Enable Audit Logging Falco Deploy Falco to Monitor System Calls Enable Pod Security Policies Encrypt Data at Rest Encryption Configuration Benchmark Cluster with Kube-Bench Kube-Bench Securing ETCD ETCD Isolation ETCD Disaster Recovery ETCD Snapshot and Restore Purge Kubernetes Purge Kubeadm 3Purge Kubeadm Image Scanning Container Essentials Secure Containers Creating a Docker Image Scanning with Trivy Trivy Snyk Security Manually Installing Kubernetes Kubernetes the Alta3 Way Deploy Kubernetes the Alta3 Way Validate your Kubernetes Installation Sonobuoy K8s Validation Test Kubectl (Optional) Kubectl get and sorting kubectl get kubectl describe Labels (Optional) Labels Labels and Selectors Annotations Insert an Annotation Securing your Application Scan a Running Container Tracee Security Contexts for Pods Understanding Security Contexts AppArmor Profiles AppArmor Isolate Container Kernels gVisor Pod Security Pod Security Policies Deploy a PSP Pod Security Standards Enable PSS Open Policy Agent (OPA) Admission Controller Create a LimitRange Open Policy Agent Policy as Code Deploy Gatekeeper User Administration Contexts Contexts Authentication and Authorization Role Based Access Control Role Based Access Control RBAC Distributing Access Service Accounts Limit Pod Service Accounts Securing Secrets Secrets Create and Consume Secrets Hashicorp Vault Deploy Vault Securing the Network Networking Plugins NetworkPolicy Deploy a NetworkPolicy mTLS Linkerd mTLS with istio istio Threat Detection Active Threat Analysis Host Intrusion Detection Deploy OSSEC Network Intrusion Detection Deploy Suricata Physical Intrusion Detection Disaster Recovery Harsh Reality of Security Deploy a Response Plan Kasten K10 Backups Deploy K10

Duration 4 Days 24 CPD hours This course is intended for This class is intended for experienced developers who are responsible for managing big data transformations including: Extracting, loading, transforming, cleaning, and validating data. Designing pipelines and architectures for data processing. Creating and maintaining machine learning and statistical models. Querying datasets, visualizing query results and creating reports Overview Design and build data processing systems on Google Cloud Platform. Leverage unstructured data using Spark and ML APIs on Cloud Dataproc. Process batch and streaming data by implementing autoscaling data pipelines on Cloud Dataflow. Derive business insights from extremely large datasets using Google BigQuery. Train, evaluate and predict using machine learning models using TensorFlow and Cloud ML. Enable instant insights from streaming data Get hands-on experience with designing and building data processing systems on Google Cloud. This course uses lectures, demos, and hand-on labs to show you how to design data processing systems, build end-to-end data pipelines, analyze data, and implement machine learning. This course covers structured, unstructured, and streaming data. Introduction to Data Engineering Explore the role of a data engineer. Analyze data engineering challenges. Intro to BigQuery. Data Lakes and Data Warehouses. Demo: Federated Queries with BigQuery. Transactional Databases vs Data Warehouses. Website Demo: Finding PII in your dataset with DLP API. Partner effectively with other data teams. Manage data access and governance. Build production-ready pipelines. Review GCP customer case study. Lab: Analyzing Data with BigQuery. Building a Data Lake Introduction to Data Lakes. Data Storage and ETL options on GCP. Building a Data Lake using Cloud Storage. Optional Demo: Optimizing cost with Google Cloud Storage classes and Cloud Functions. Securing Cloud Storage. Storing All Sorts of Data Types. Video Demo: Running federated queries on Parquet and ORC files in BigQuery. Cloud SQL as a relational Data Lake. Lab: Loading Taxi Data into Cloud SQL. Building a Data Warehouse The modern data warehouse. Intro to BigQuery. Demo: Query TB+ of data in seconds. Getting Started. Loading Data. Video Demo: Querying Cloud SQL from BigQuery. Lab: Loading Data into BigQuery. Exploring Schemas. Demo: Exploring BigQuery Public Datasets with SQL using INFORMATION_SCHEMA. Schema Design. Nested and Repeated Fields. Demo: Nested and repeated fields in BigQuery. Lab: Working with JSON and Array data in BigQuery. Optimizing with Partitioning and Clustering. Demo: Partitioned and Clustered Tables in BigQuery. Preview: Transforming Batch and Streaming Data. Introduction to Building Batch Data Pipelines EL, ELT, ETL. Quality considerations. How to carry out operations in BigQuery. Demo: ELT to improve data quality in BigQuery. Shortcomings. ETL to solve data quality issues. Executing Spark on Cloud Dataproc The Hadoop ecosystem. Running Hadoop on Cloud Dataproc. GCS instead of HDFS. Optimizing Dataproc. Lab: Running Apache Spark jobs on Cloud Dataproc. Serverless Data Processing with Cloud Dataflow Cloud Dataflow. Why customers value Dataflow. Dataflow Pipelines. Lab: A Simple Dataflow Pipeline (Python/Java). Lab: MapReduce in Dataflow (Python/Java). Lab: Side Inputs (Python/Java). Dataflow Templates. Dataflow SQL. Manage Data Pipelines with Cloud Data Fusion and Cloud Composer Building Batch Data Pipelines visually with Cloud Data Fusion. Components. UI Overview. Building a Pipeline. Exploring Data using Wrangler. Lab: Building and executing a pipeline graph in Cloud Data Fusion. Orchestrating work between GCP services with Cloud Composer. Apache Airflow Environment. DAGs and Operators. Workflow Scheduling. Optional Long Demo: Event-triggered Loading of data with Cloud Composer, Cloud Functions, Cloud Storage, and BigQuery. Monitoring and Logging. Lab: An Introduction to Cloud Composer. Introduction to Processing Streaming Data Processing Streaming Data. Serverless Messaging with Cloud Pub/Sub Cloud Pub/Sub. Lab: Publish Streaming Data into Pub/Sub. Cloud Dataflow Streaming Features Cloud Dataflow Streaming Features. Lab: Streaming Data Pipelines. High-Throughput BigQuery and Bigtable Streaming Features BigQuery Streaming Features. Lab: Streaming Analytics and Dashboards. Cloud Bigtable. Lab: Streaming Data Pipelines into Bigtable. Advanced BigQuery Functionality and Performance Analytic Window Functions. Using With Clauses. GIS Functions. Demo: Mapping Fastest Growing Zip Codes with BigQuery GeoViz. Performance Considerations. Lab: Optimizing your BigQuery Queries for Performance. Optional Lab: Creating Date-Partitioned Tables in BigQuery. Introduction to Analytics and AI What is AI?. From Ad-hoc Data Analysis to Data Driven Decisions. Options for ML models on GCP. Prebuilt ML model APIs for Unstructured Data Unstructured Data is Hard. ML APIs for Enriching Data. Lab: Using the Natural Language API to Classify Unstructured Text. Big Data Analytics with Cloud AI Platform Notebooks What's a Notebook. BigQuery Magic and Ties to Pandas. Lab: BigQuery in Jupyter Labs on AI Platform. Production ML Pipelines with Kubeflow Ways to do ML on GCP. Kubeflow. AI Hub. Lab: Running AI models on Kubeflow. Custom Model building with SQL in BigQuery ML BigQuery ML for Quick Model Building. Demo: Train a model with BigQuery ML to predict NYC taxi fares. Supported Models. Lab Option 1: Predict Bike Trip Duration with a Regression Model in BQML. Lab Option 2: Movie Recommendations in BigQuery ML. Custom Model building with Cloud AutoML Why Auto ML? Auto ML Vision. Auto ML NLP. Auto ML Tables.

Virtual course for parents of adult children at risk/pre manifest. We are pleased to invite you to our virtual course for parents of adult children at risk/pre manifest. This is an opportunity to improve your knowledge of the issues surrounding your adult child at risk, share your experiences and gain ideas of support available for yourself and your adult child. This is a 5 week course running from Thursday 22 February 2024 10am -11.30am until Thursday 21 March, with the final session being an extended session narrative therapy session facilitated by Riverbank Psychology. There will be the opportunity to join a follow up support group. Week 1 – Thursday 22 February 2024 10am Welcome and overview of support available from the Huntington Disease Association. Speaker: James O’Connor – Team Leader HDYES – Huntington’s Disease Association Week 2 – Thursday 29 February 2024 10am Genetics: How to access testing, the process and family planning options Speaker: Chris Platt – SHDA – Huntington’s Disease Association Week 3 – Thursday 7 March 2024 10am Research update and what next Speaker: Nataile Saad - Research Sister - Welcome Trust Southampton University Hospital Week 4 – Thursday 14 March 2024 10am Finances planning ahead Speaker: Lisa Pearson - Financial Advisor - Asset management Week 5 – Thursday 21 March 2024 9.30 -12.30pm (note longer session)* Narrative Therapy: Coping with Feelings, supporting a loved one and self-care. Mariangels Ferrer – Clinical Psychologist – Riverbank Psychology * We will invite previous course participants to this part of the course but can only accommodate a maximum of 12/14 people on the day. The focus of Narrative Therapy in this group is to participate in a creative activity that explores identity through values, beliefs, and support systems, enabling us to make connections to our external lives which will be sustainable in our everyday lives. Mariangels Ferrer Duch is a Clinical Psychologist trained in Narrative Therapy who will be facilitating a three-hour Narrative Therapy session. The focus of the session will be upon the many small things that are important to us in life which can often be overlooked in times of stress. We hope the conversation will help to mutually inspire us all! We take your privacy seriously and promise to never sell your data. You can find out more about your rights, how we use your personal information and how we keep your details safe and secure by reading our privacy policy here. For more information email info@hda.org.uk or call 0151 331 5444.

Keeping Yourself in Mind: An ACT-informed programme for people supporting a family member with JHD We are pleased to invite you to our virtual course for parents and family carers of people living with Juvenile Huntington’s disease. The course will be run by Sarah Gunn, a clinical psychologist and researcher at the University of Leicester, and will be based on the principles of Acceptance and Commitment Therapy. Acceptance and Commitment Therapy is a therapeutic approach which focuses on learning to manage difficult thoughts and feelings, and to live a life which feels valuable and meaningful despite the struggles we encounter. This is an opportunity to explore the difficulties that can be associated with caring for a person with JHD (for you and within the family), to identify the values that matter most to you, and for you to think about how to move towards a more rich and valued life than you may have now. This is an eight-week course running from Wednesday 7 February to Wednesday 27 March 2024. The sessions will be on a Wednesday afternoon 1-2.30pm. Here is a very brief session outline: Week 1: Introductions: To ACT, to the programme, and to each other Week 2: Impacts of Juvenile Huntington’s on the “carer”* and wider family Week 3: Psychological wellbeing when supporting a person with Juvenile Huntington’s Week 4: Coping and adjustment: Living with, not battling against Week 5: What matters to you: Finding your values Week 6: Moving forward: Taking steps to align with your values Week 7: Living a valued life alongside Huntington’s: Plans and coping strategies Week 8: Reflection and ending: What’s next? *Note: Some people don’t like this term, so here we’re using it in quote marks. During the course, we will discuss which term would be preferred by the people attending. For more information on what information we collect and how we use it when booking onto one of our events, please see our privacy policy on our website.

Duration 5 Days 30 CPD hours This course is intended for This course is suitable for anyone responsible for configuring, managing or supporting a Veeam Availability Suite v11 environment. This includes Senior Engineers and Architects responsible for creating architectures for Veeam environments. Overview After completing this course, attendees should be able to: Describe Veeam Availability Suite components usage scenarios and relevance to your environment. Effectively manage data availability in on-site, off-site, cloud and hybrid environments. Ensure both Recovery Time Objectives (RTOs) and Recovery Point Objectives (RPOs) are met. Configure Veeam Availability Suite to ensure data is protected effectively. Adapt with an organization's evolving technical and business data protection needs. Ensure recovery is possible, effective, efficient, secure and compliant with business requirements. Provide visibility of the business data assets, reports and dashboards to monitor performance and risks. Design and architect a Veeam solution in a real-world environment Describe best practices, review an existing infrastructure and assess business/project requirements Identify relevant infrastructure metrics and perform component (storage, CPU, memory) quantity sizing Provide implementation and testing guidelines in line with designs Innovatively address design challenges and pain points, matching appropriate Veeam Backup & Replication features with requirements Veeam Certified Architect is the highest level of Veeam technical certifications. Engineers who complete both Veeam Availability Suite v11: Configuration and Management and Veeam Backup & Replication V11: Architecture and Design programs (courses + exams) will be granted with the 'Veeam Certified Architect' (VMCA) title by Veeam. Introduction Veeam Availability Suite v11: Configuration and Management Describe RTOs and RPOs, what they mean for your business, how to manage and monitor performance against them The 3-2-1 Rule and its importance in formulating a successful backup strategy Identify key Veeam Availability Suite components and describe their usage scenarios and deployment types Building backup capabilities Backup methods, the appropriate use cases and impact on underlying file systems Create, modify, optimize and delete backup jobs, including Agents and NAS Backup jobs. Explore different tools and methods to maximize environment performance Ensure efficiency by being able to select appropriate transport modes while being aware of the impact of various backup functions on the infrastructure Building replication capabilities Identify and describe the options available for replication and impacts of using them Create and modify replication jobs, outline considerations to ensure success Introduce the new Continuous Data Protection (CDP) policy Secondary backups Simple vs. advanced backup copy jobs, how to create and modify them using best practices to ensure efficient recovery Discuss using tapes for backups Advanced repository capabilities Ensure repository scalability using a capability such as SOBR on-premises and off-site including integration with cloud storage Ensure compatibility with existing deduplication appliances Introduce the new hardened repository Protecting data in the cloud Review how Veeam can protect the data of a cloud native application Review how Veeam Cloud Connect enables you to take advantage of cloud services built on Veeam Review how Veeam can be used to protect your Office 365 data Restoring from backup Ensure you have the confidence to use the correct restore tool at the right time for restoring VMs, bare metal and individual content such as files and folders Utilize Secure Restore to prevent the restoration of malware Describe how to use Staged Restore to comply with things like General Data Protection Regulation (GDPR) before releasing restores to production Identify, describe and utilize the different explores and instant recovery tools and features Recovery from replica Identify and describe in detail, failover features and the appropriate usage Develop, prepare and test failover plans to ensure recovery Disaster recovery from replica to meet a variety of real-world recovery needs Testing backup and replication Testing backups and replicas to ensure you can recover, what you need, when you need to Configure and setup virtual sandbox environments based on backup, replicas and storage snapshots Veeam Backup Enterprise Manager and Veeam ONE Introduce the concept of monitoring your virtual, physical and cloud environments with Veeam Backup Enterprise Manager and Veeam ONE? Configuration backup Locate, migrate or restore backup configuration Introduction Veeam Backup & Replication v11: Architecture and Design Review the architecture principles Explore what a successful architecture looks like Review Veeam?s architecture methodology Discovery Analyze the existing environment Uncover relevant infrastructure metrics Uncover assumptions and risks Identify complexity in the environment Conceptual design Review scenario and data from discovery phase Identify logical groups of objects that will share resources based on requirements Create a set of detailed tables of business and technical requirements, constraints, assumptions and risks Review infrastructure data with each product component in mind Create high level design and data flow Logical design Match critical components and features of VBR with requirements Create logical groupings Determine location of components and relationship to logical grouping Aggregate totals of component resources needed per logical grouping Calculate component (storage, CPU, memory) quantity sizing Physical/tangible design Convert the logical design into a physical design Physical hardware sizing Create a list of physical Veeam backup components Implementation and Governance Review physical design and implantation plan Review Veeam deployment hardening Describe the architect?s obligations to the implementation team Provide guidance on implementation specifics that relate to the design Validation and Iteration Provide framework for how to test the design Further develop the design according to a modification scenario