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Duration 1 Days 6 CPD hours This course is intended for This course is intended for: Developers responsible for developing Deep Learning applications Developers who want to understand concepts behind Deep Learning and how to implement a Deep Learning solution on AWS Overview This course is designed to teach you how to: Define machine learning (ML) and deep learning Identify the concepts in a deep learning ecosystem Use Amazon SageMaker and the MXNet programming framework for deep learning workloads Fit AWS solutions for deep learning deployments In this course, you?ll learn about AWS?s deep learning solutions, including scenarios where deep learning makes sense and how deep learning works. You?ll learn how to run deep learning models on the cloud using Amazon SageMaker and the MXNet framework. You?ll also learn to deploy your deep learning models using services like AWS Lambda while designing intelligent systems on AWS. Module 1: Machine learning overview A brief history of AI, ML, and DL The business importance of ML Common challenges in ML Different types of ML problems and tasks AI on AWS Module 2: Introduction to deep learning Introduction to DL The DL concepts A summary of how to train DL models on AWS Introduction to Amazon SageMaker Hands-on lab: Spinning up an Amazon SageMaker notebook instance and running a multi-layer perceptron neural network model Module 3: Introduction to Apache MXNet The motivation for and benefits of using MXNet and Gluon Important terms and APIs used in MXNet Convolutional neural networks (CNN) architecture Hands-on lab: Training a CNN on a CIFAR-10 dataset Module 4: ML and DL architectures on AWS AWS services for deploying DL models (AWS Lambda, AWS IoT Greengrass, Amazon ECS, AWS Elastic Beanstalk) Introduction to AWS AI services that are based on DL (Amazon Polly, Amazon Lex, Amazon Rekognition) Hands-on lab: Deploying a trained model for prediction on AWS Lambda Additional course details: Nexus Humans Deep Learning on AWS 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 Deep Learning on AWS 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 2 Days 12 CPD hours This course is intended for This course is intended for system and network administrators responsible for installation, setup, configuration, and administration of BIG-IP DNS systems. This course gives networking professionals a functional understanding of the BIG-IP DNS system as it is commonly used. The course covers configuration and ongoing management of the BIG-IP DNS system, and includes a combination of lecture, discussion, and hands-on labs. Module 1: Setting Up the BIG-IP System Introducing the BIG-IP System Initially Setting Up the BIG-IP System Archiving the BIG-IP Configuration Leveraging F5 Support Resources and Tools Provision the BIG-IP System and Confirm Network Configuration Module 2: Introducing the Domain Name System (DNS) and BIG-IP DNS Understanding the Domain Name System (DNS) Reviewing the Name Resolution Process Implementing BIG-IP DNS Using DNS Resolution Diagnostic Tools Module 3: Accelerating DNS Resolution Introducing DNS Resolution with BIG-IP DNS BIG-IP DNS Resolution Decision Flow Configuring BIG-IP DNS Listeners Resolving DNS Queries in the Labs (Lab Zone Records) Load Balancing Queries to a DNS Server Pool Accelerating DNS Resolution with DNS Cache Accelerating DNS Resolution with DNS Express Introducing Wide IPs Using Other Resolution Methods with BIG-IP DNS Integrating BIG-IP DNS into Existing DNS Environments Module 4: Implementing Intelligent DNS Resolutions Introducing Intelligent DNS Resolution Identifying Physical Network Components Identifying Logical Network Components Collecting Metrics for Intelligent Resolution Configuring Data Centers Configuring a BIG-IP DNS System as a Server Configuring a BIG-IP LTM System as a Server Establishing iQuery Communication between BIG-IP Systems Configuring a Non-F5 Server Defining Links and Routers Configuring Wide IP Pools Configuring Wide IPs Managing Object Status Using the Traffic Management Shell (TMSH) Module 5: Using LDNS Probes and Metrics Introducing LDNS Probes and Metrics Types of LDNS Probes Excluding an LDNS from Probing Configuring Probe Metrics Collection Module 6: Load Balancing Intelligent DNS Resolution Introducing Load Balancing on BIG-IP DNS Using Static Load Balancing Methods Round Robin Ratio Global Availability Static Persist Other Static Load Balancing Methods Using Dynamic Load Balancing Methods Round Trip Time Completion Rate CPU Hops Least Connections Packet Rate Kilobytes per Second Other Dynamic Load Balancing Methods Virtual Server Capacity Virtual Server Score Using Quality of Service Load Balancing Persisting DNS Query Responses Configuring GSLB Load Balancing Decision Logs Using Manual Resume Using Topology Load Balancing Module 7: Monitoring Intelligent DNS Resources Exploring Monitors Configuring Monitors Assigning Monitors to Resources Monitoring Best Practices Module 8: Advanced BIG-IP DNS Topics Implementing DNSSEC Setting Limits for Resource Availability Using iRules with Wide IPs Introducing Other Wide IP Types Implementing BIG-IP DNS Sync Groups Module 9: Final Configuration Projects Final Configuration Projects

Duration 2 Days 12 CPD hours This course is intended for This course is for IT network or security professionals who have practical experience with the ProxySG in the field and wish to master the advanced network security of the ProxySG. Overview Solve common authentication and SSL issuesUnderstand the underlying architecture of SGOSMonitor and analyze ProxySG performanceUse policy tracing as a troubleshooting tool The ProxySG 6.6 Advanced Administration course is intended for IT professionals who wish to learn to master the advanced features of the ProxySG. Using Authentication Realms Describe the benefits of enabling authentication on the ProxySG Describe, at a high level, the ProxySG authentication architecture Understand the use of IWA realms, with both IWA Direct and IWA BCAAA connection methods Understanding Authentication Credentials Describe how NTLM and Kerberos authentication work in both IWA direct and IWA BCAAA deployments Configure the ProxySG to use Kerberos authentication Understanding Authentication Modes Describe authentication surrogates and authentication modes Describe ProxySG authentication in both explicit and transparent deployment mode Understanding HTTPS Describe key components of SSL encryption Describe how the SSL handshake works Describe some of the legal and security considerations related to use of the SSL proxy Managing SSL Traffic on the ProxySG Describe how the SSL proxy service handles SSL traffic Describe the standard keyrings that are installed by default on the ProxySG Identify the types of security certificates that the ProxySG uses Optimizing SSL Interception Performance Configure the ProxySG to process SSL traffic according to best practices for performance SGOS Architecture Identify key components of SGOS Explain the interaction among client workers and software workers in processing client requests Explain the significance of policy checkpoints Describe key characteristics of the SGOS storage subsystem Explain the caching behavior of the ProxySG Caching Architecture Describe the benefits of object caching on the ProxySG Explain the caching-related steps in a ProxySG transaction Identify and describe the HTTP request and response headers related to caching Describe, in general terms, how the ProxySG validates cached objects to ensure freshness Explain how the ProxySG uses cost-based deletion, popularity contests, and pipelining to improve object caching System Diagnostics Describe the use of the health monitor and health checks Explain the use of the event and access logs Describe the information available in advanced URLs and sysinfo files Describe the function of policy tracing and packet captures Introduction to Content Policy Language (CPL) Describe the fundamental concepts and purposes of ProxySG policy transactions Understand the relationship of layers, rules, conditions, properties, and triggers Describe the two types of actions in CPL Describe how to write, edit, and upload CPL code Using Policy Tracing for Troubleshooting Identify the two main types of ProxySG policy traces Describe the various sections of a policy trace result Configure a global and policy-driven trace Access and interpret policy trace results ProxySG Integration Identify other Symantec products that can be used as part of a complete security solution

Duration 3 Days 18 CPD hours This course is intended for This course is designed for technical professionals who will deploy or have deployed the Ultra M virtual packet core solution in their network, including: Systems engineers Technical support personnel Channel partners and resellers Overview After taking this course, you should be able to: Describe the Ultra M hardware and software Describe the features covered in the OpenStack component overview and deployment architecture Describe the Ultra M deployment architecture and operation Describe the Virtualized Packet Core-Distributed Instance (VPC-DI) architecture and packet flow Deploy and operate Ultra M This course teaches you about the hardware components of the Cisco© Ultra M virtual packet core solution, including Cisco Nexus© spine and leaf switches and Cisco Unified Computing System. The course also covers the operation and administration of the Red Hat Enterprise Linux operating system in relation to the Ultra M Undercloud and Overcloud deployments. Cisco Ultra M Hardware and Topology Overview Cisco Ultra M Hardware Components Cisco Ultra M UCS Components Cisco Ultra M UCS Interfaces Cisco Ultra M Networking Components Cisco Ultra M Physical Network Topology OpenStack Deployment Architecture and Components OpenStack Overview Nova ? OpenStack Compute Service Glance ? OpenStack Image Service Neutron ? OpenStack Network Service Keystone ? OpenStack Identity Service Cinder ? OpenStack Block Storage Service OpenStack Horizon Dashboard Ultra M Services Platform Ultra Services Platform Architecture Ultra M VNF Architecture Ultra Automation Services (UAS) Elastic Services Controller OpenStack and Ultra Automation Services VPC-DI Overview and Operation Virtual Packet Core Evolution Ultra M Layer 3 Network Topology VPC-DI Network Topology VPC-DI Packet Flows Ultra M Installation and Deployment Reviewing the Ultra M System Components Planning the Network for Installation and Deployment Deploying Hyperconverged Ultra M Models Using UAS Deploying VNFs Using AutoVNF Ultra Automation Services Additional course details: Nexus Humans Cisco Ultra M Deployment and Operations v1.0 (SPMBL301) 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 Ultra M Deployment and Operations v1.0 (SPMBL301) 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 for information technology professionals, security professionals, network, system managers and administrators tasked with installing, configuring and maintaining Symantec Data Center Security: Server Advanced. Overview At the completion of the course, you will be able to: Describe the major components of Symantec Data Center Security: Server Advanced and how they communicate. Install the management server, console and agent. Define, manage and create assets, policies, events and configurations. Understand policy creation and editing in depth. course is an introduction to implementing and managing a Symantec Data Center Security: Server Advanced 6.0 deployment. Introduction Course Overview The Classroom Lab Environment Introduction to Security Risks and Risk Security Risks Security Risk Management Managing and Protecting Systems Corporate Security Policies and Security Assessments Host-Based Computer Security Issues SDCS:Server Advanced Overview SDCS: Server Advanced Component Overview Policy Types and Platforms Management Console Overview Agent User Interface Overview DEMO of Management Console Installation and Deployment Planning the Installation Deploying SDCS:SA for High Availability Scalability Installing the Management Server Installing the Management Console Installing a Windows Agent Installing a UNIX Agent LAB: Install Manager and Agents Configuring Assets Asset and Agent Overview Viewing Agents and Assets Managing Agents Managing Agents on Assets LAB: Create Asset Groups LAB: Examine Agent Interface Policy Overview Policies Defined Prevention Policy Overview Process Sets Resource Access Policy Options Detection Policy Overview IDS Capabilities Rules Collectors Policy Management Workspace User Interface on Agent Example Use Cases LAB: Paper Based Scenarios LAB: What type of security strategy should be used? Detailed Prevention Policies Policy Editor Policy Structure Global Policy Options Service Options Program Options Policy Processing Order Network Rules File Rules Registry Rules Process Sets Predefined Policies LAB: Deploy Strict policy LAB: Examine Functionality Advanced Prevention Profiling Applications Customizing Predefined Policies LAB: Modify Policy Previously Deployed LAB: Re-examine Functionality LAB: Preparing for Policy deployment LAB: Best Practice - Covering Basics LAB: Further Enhance Strict Policy LAB: Create Custom Process Set LAB :Secure an FTP Server LAB: Troubleshoot Policy/pset Assignment Using CLI Detection Policies Detection Policies Structure Collectors Rules Predefined Detection Policies Creating a Detection Policy Using the Template Policy LAB: Deploy Baseline Policy LAB: Create Custom Policy Event Management Events Defined Viewing Events Reports and Queries Overview Creating Queries and Reports Creating Alerts LAB: View Monitor Types and Search Events LAB: Create Real Time Monitor Agent Management and Troubleshooting Configurations Defined Creating and Editing Configurations Common Parameters Prevention Settings Detection Settings Analyzing Agent Log Files Diagnostic Policies Local Agent Tool ? sisipsconfig LAB: Create Custom Configurations LAB: Implement Bulk Logging LAB: Disable Prevention on Agent Using CLI LAB: Use Diagnostic Policy to Gather Logs LAB: Troubleshoot a Policy System Management Managing Users and Roles Server Security Viewing and Managing Server Settings Viewing and Managing Database Settings Viewing and Managing Tomcat Settings LAB: Create a New User LAB: View System Settings

Duration 3.5 Days 21 CPD hours This course is intended for This course is for AWS Cloud Architects with expertise in designing and implementing solutions running on AWS who now want to design for Microsoft Azure. Overview After completing this course, students will be able to: Secure identities with Azure Active Directory and users and groups. Implement identity solutions spanning on-premises and cloud-based capabilities Apply monitoring solutions for collecting, combining, and analyzing data from different sources. Manage subscriptions, accounts, Azure policies, and Role-Based Access Control. Administer Azure using the Resource Manager, Azure portal, Cloud Shell, and CLI. Configure intersite connectivity solutions like VNet Peering, and virtual network gateways. Administer Azure App Service, Azure Container Instances, and Kubernetes. This course teaches Solutions Architects who have previously designed for Amazon Web Services how to translate business requirements into secure, scalable, and reliable solutions for Azure. Introduction to Azure Subscriptions and accounts Resource groups and templates in Azure Resource Manager Azure global infrastructure Azure regions Azure Availability Zones Comparison with AWS Implement Azure Active Directory Introduction to Azure Active Directory Domains and custom domains Safety features Guest users in Azure Active Directory Manage multiple directories Comparison with AWS Implement and manage hybrid identities Introduction to Azure AD Connect Comparison with AWS Implement virtual networking Azure Virtual Network and VNet peering VPN and ExpressRoute connections Comparison with AWS Implement VMs for Windows and Linux Configure high availability Comparison with AWS Implement load balancing and network security Implement Azure Load Balancer Implement an Azure Application Gateway Implement Azure Firewall Implement network security groups and application security groups Comparison with AWS Implement container-based applications Configure Azure Kubernetes Service Publish a solution on an Azure Container Instance Comparison with AWS Implement an application infrastructure Create an App Service plan Create and configure Azure App Service Configure networking for an App Service Introduction to Logic Apps and Azure Functions Comparison with AWS Implement storage accounts Azure Storage core concepts Managing the Azure Blob storage lifecycle Working with Azure Blob storage Comparison with AWS Implement NoSQL databases Introduction to Azure Cosmos DB Consistency Select appropriate CosmosDB APIs Set up replicas in CosmosDB Comparison with AWS DynamoDB Implement Azure SQL databases Configure Azure SQL database settings Implement Azure SQL Database managed instances Configure high availability for an Azure SQL database Comparison with AWS Implement cloud infrastructure monitoring Monitor security Monitor cost Configure a Log Analytics workspace Comparison with AWS Implement and manage Azure governance solutions Assign RBAC roles Configure management access to Azure Implement and configure an Azure Policy Comparison with AWS Manage security for applications Implement Azure Key Vault Implement and configure Azure AD Managed Identities Register and manage applications in Azure AD Comparison with AWS Migration, backup, and disaster recovery management Migrate workloads Implement Azure Backup for VMs Implement disaster recovery Comparison with AWS

Duration 1 Days 6 CPD hours This course is intended for This class is intended for the following: Data analysts, Data scientists, Business analysts getting started with Google Cloud Platform. Individuals responsible for designing pipelines and architectures for data processing, creating and maintaining machine learning and statistical models, querying datasets, visualizing query results and creating reports. Executives and IT decision makers evaluating Google Cloud Platform for use by data scientists. Overview This course teaches students the following skills:Identify the purpose and value of the key Big Data and Machine Learning products in the Google Cloud Platform.Use Cloud SQL and Cloud Dataproc to migrate existing MySQL and Hadoop/Pig/Spark/Hive workloads to Google Cloud Platform.Employ BigQuery and Cloud Datalab to carry out interactive data analysis.Train and use a neural network using TensorFlow.Employ ML APIs.Choose between different data processing products on the Google Cloud Platform. This course introduces participants to the Big Data and Machine Learning capabilities of Google Cloud Platform (GCP). It provides a quick overview of the Google Cloud Platform and a deeper dive of the data processing capabilities. Introducing Google Cloud Platform Google Platform Fundamentals Overview. Google Cloud Platform Big Data Products. Compute and Storage Fundamentals CPUs on demand (Compute Engine). A global filesystem (Cloud Storage). CloudShell. Lab: Set up a Ingest-Transform-Publish data processing pipeline. Data Analytics on the Cloud Stepping-stones to the cloud. Cloud SQL: your SQL database on the cloud. Lab: Importing data into CloudSQL and running queries. Spark on Dataproc. Lab: Machine Learning Recommendations with Spark on Dataproc. Scaling Data Analysis Fast random access. Datalab. BigQuery. Lab: Build machine learning dataset. Machine Learning Machine Learning with TensorFlow. Lab: Carry out ML with TensorFlow Pre-built models for common needs. Lab: Employ ML APIs. Data Processing Architectures Message-oriented architectures with Pub/Sub. Creating pipelines with Dataflow. Reference architecture for real-time and batch data processing. Summary Why GCP? Where to go from here Additional Resources Additional course details: Nexus Humans Google Cloud Platform Big Data and Machine Learning Fundamentals 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 Google Cloud Platform Big Data and Machine Learning Fundamentals 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 Individuals involved in IT development, IT operations or IT service management; Those whose role is touched by DevOps and continuous delivery, such as the following IT roles: DevOps engineers, Product owners Integration specialists, Operations managers, Incident & change managers, System administrators, Network administrators, Business managers, Automation architects, Enterprise architects, Testers Overview Know the emergence of DevOps Know the core concepts and principles of DevOps Know what DevOps means for you as professional and for your organization Know the essence of a DevOps culture Understand the key elements of a DevOps culture Know the important aspects when creating a DevOps culture Know the Operational models of DevOps Understand the need for autonomous teams Understand the impact of DevOps on Architecture with respect to deployment Understand governance within DevOps teams Understand Agile, Scrum and Kanban and how these practices relate to one another Understand how ITSM processes relate to practices in a DevOps culture Understand how lean is used to optimise processes Know how to provide a Value Stream Map for a given process Understand the way to harvest new and innovative ideas Know the impact of automation on Software Delivery processes Understand the benefits and core principles of Continuous Delivery Describe the key cloud principles for DevOps organisations Know the relevance of monitoring and logging DevOps This course is designed to provide the core education necessary to build your DevOps vocabulary and to understand its principles and practices. With the help of key DevOps concepts and terminology, real-life case studies, examples and interactive group discussions and extensive exercises in each module you will acquire a fundamental understanding of DevOps. Introduction Let?s Get to Know Each Other Overview Course Objectives Mapping of the Competence Model with the Course Modules Course Agenda Type of Activities Exam Course Book Technical Glossary Group Activity Module Summary DevOps Introduction Module Objectives Module Topics Emergence of DevOps Core Concepts of DevOps DevOps Agile Skills Association (DASA) Module Summary Module End Questions Culture Module Objectives Module Topics Essence of a DevOps Culture Key Elements of DevOps Implementation of a DevOps Culture Module Summary Module End Questions Organization Module Objectives Module Topics Organizational Model Autonomous Teams Architecting for DevOps Governance Module Summary Module End Questions Processes Module Objectives Module Topics Process Basics DevOps in Relation to ITSM Agile and Scrum 12 Principles of the Agile Manifesto Optimizing Processes Using Lean Business Value Optimization and Business Analysis Using Story Mapping Module Summary Module End Questions Automation Module Objectives 6A Automation Concepts Automation for Delivery of Software Continuous Delivery Core Concepts Continuous Delivery Automation Concepts Continuous Delivery Automation Focus Topics 6B Data Center Automation Emergence of Cloud Technology and Principles Cloud Services Concepts in a DevOps Organization Automated Provisioning Concepts Platform Product Characteristics and Application Maturity Module Summary Module End Questions Measure and Improvement Module Objectives Module Topics Importance of Measurement Choosing the Right Metrics Monitoring and Logging Module Summary Module End Questions

Duration 4.5 Days 27 CPD hours This course is intended for This course is intended for individuals who have basic knowledge on cloud computing; on-premise system administrators; IT specialists, interested in AWS and Cloud Technologies. Overview Upon successful completion of this course, students will know how to design and deploy scalable, highly accessible and fault-tolerant systems in AWS. In this course, students will learn the main 'Managed Service' offered by AWS; How to design and deploy scalable, highly accessible and fault-tolerant systems in AWS; How to choose the most appropriate AWS service. Introduction Course overview Exam Blue Print Public clouds & cloud economics AWS Overview & Whitepapers Setting up AWS Account Identity and Access Management (IAM) Local users, groups & roles SAML providers Policies Cross Account Access Best practices & Examples Lab Exam highlights Sample questions Simple Storage Service (S3) & Glacier Buckets Objects Lifecycle Configurations and permissions Custom bucket policies Best Practices & Examples Lab Exam highlights Sample questions Virtual Private Cloud (VPC) VPC Internet gateway vs NAT Gateway Elastic IPs Subnets & Routing tables Security Groups & Network Access Lists VPC Peering & Endpoints Managed VPN Connections Best Practices & Examples Lab Exam highlights Sample questions Elastic Compute Cloud (EC2) Instances Amazon Machine Images(AMIs) Elastic Block Store (EBS) Network & Security Load Balancers (ELB) Auto Scaling Groups (ASG) Instance Management Best Practices & Examples Lab Exam highlights Sample questions Route 53 Hosted Zones Health checks Traffic flow Best Practices & Examples Lab Exam highlights Sample questions Relational Database Service (RDS) Engine types Performance & Resilience Subnet groups Best Practices & Examples Lab Exam highlights Sample questions CloudWatch Dashboard and Metrics CloudWatch logs CloudWatch rules Best Practices & Examples Lab Exam highlights Sample questions Other AWS Services Simple Overview CloudFront DynamoDB Elasticache Redshift SQS SWF SNS Elastic Transcoder API Gateway Kenesis CloudFormation Exam highlights Sample questions Multiple AWS Services exercise Lab 1 - Architecting multi-tier environment Lab 2 - Configure backup and monitoring Practice Exam Additional course details: Nexus Humans AWS Certified Solutions Architect - Associate 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 AWS Certified Solutions Architect - Associate 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 designed for IBM Integration Bus administrators and developers who administer IBM Integration Bus. Overview After completing this course, you should be able to:Install and configure an IBM Integration Bus instanceEstablish, maintain, and manage an integration nodeAdminister IBM Integration Bus components and message flow applications by using the IBM Integration web user interface and command interfaceConfigure connectivity to IBM MQ to enable IBM Integration Bus to get messages from, or put messages to, queues on a local or remote queue managerImplement IBM Integration Bus administration and message flow securityUse problem determination aids to diagnose and solve development and runtime errorsUse the IBM Integration web user interface to generate and display message flow statisticsUse IBM MQ or MQTT to publish and subscribe to IBM Integration Bus topicsImplement an IBM Integration Bus global cache to store, reuse, and share data between integration nodesUse workload management policies to adjust the processing speed of messages and control the actions that are taken on unresponsive flows and threadsUse the IBM Integration web user interface and a database to record events and replay messagesEnable an integration node to connect to a database with ODBC and JDBCConfigure a Java Message Services (JMS) provider for use with the JMS nodesConfigure IBM Integration Bus for the secure file transfer protocol (SFTP)Find and install IBM Integration Bus SupportPac components In this course, students learn how to administer IBM Integration Bus on distributed operating systems, such as Windows and AIX, by using the IBM Integration Bus administrative interfaces. Course Outline Course introduction IBM Integration Bus overview Product installation, configuration, and security planning Exercise: Integration node setup and customization Connecting to IBM MQ Exercise: Connecting to IBM MQ Administration in the IBM Integration Toolkit Exercise: Using the IBM Integration Toolkit Administration basics Exercise: Administering the IBM Integration Bus runtime components Implementing IBM Integration Bus administration security Exercise: Using file-based security to control administration access Exercise: Using queue-based security to control administration access Implementing IBM Integration Bus message flow security Administering web services and web service security Exercise: Implementing web services and web services security Diagnosing problems Exercise: Using problem diagnosis tools Exercise: Identifying runtime problems Monitoring the integration node and message flow performance Publish/subscribe implementation overview Exercise: Viewing runtime statistics Configuring IBM Integration Bus for high availability Exercise: Administering workload management policies Monitoring, recording, and replaying message flow events Exercise: Recording and replaying message flow data Extending IBM Integration Bus Course summary Additional course details: Nexus Humans WM646 IBM Integration Bus V10 System Administration 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 WM646 IBM Integration Bus V10 System Administration 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.