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Duration 3 Days 18 CPD hours Overview In this course you?ll learn how to: Containerize and deploy a new Python script Configure the deployment with ConfigMaps, Secrets and SecurityContexts Understand multi-container pod design Configure probes for pod health Update and roll back an application Implement services and NetworkPolicies Use PersistentVolumeClaims for state persistence And more In this vendor agnostic course, you will use Python to build, monitor and troubleshoot scalable applications in Kubernetes. Introduction Objectives Who You Are The Linux Foundation Linux Foundation Training Preparing Your System Course Registration Labs Kubernetes Architecture What Is Kubernetes? Components of Kubernetes Challenges The Borg Heritage Kubernetes Architecture Terminology Master Node Minion (Worker) Nodes Pods Services Controllers Single IP per Pod Networking Setup CNI Network Configuration File Pod-to-Pod Communication Cloud Native Computing Foundation Resource Recommendations Labs Build Container Options Containerizing an Application Hosting a Local Repository Creating a Deployment Running Commands in a Container Multi-Container Pod readinessProbe livenessProbe Testing Labs Design Traditional Applications: Considerations Decoupled Resources Transience Flexible Framework Managing Resource Usage Multi-Container Pods Sidecar Container Adapter Container Ambassador Points to Ponder Labs Deployment Configuration Volumes Overview Introducing Volumes Volume Spec Volume Types Shared Volume Example Persistent Volumes and Claims Persistent Volume Persistent Volume Claim Dynamic Provisioning Secrets Using Secrets via Environment Variables Mounting Secrets as Volumes Portable Data with ConfigMaps Using ConfigMaps Deployment Configuration Status Scaling and Rolling Updates Deployment Rollbacks Jobs Labs Security Security Overview Accessing the API Authentication Authorization ABAC RBAC RBAC Process Overview Admission Controller Security Contexts Pod Security Policies Network Security Policies Network Security Policy Example Default Policy Example Labs Exposing Applications Service Types Services Diagram Service Update Pattern Accessing an Application with a Service Service without a Selector ClusterIP NodePort LoadBalancer ExternalName Ingress Resource Ingress Controller Labs Troubleshooting Troubleshotting Overview Basic Troubleshooting Steps Ongoing (Constant) Change Basic Troubleshooting Flow: Pods Basic Troubleshooting Flow: Node and Security Basic Troubleshooting Flow: Agents Monitoring Logging Tools Monitoring Applications System and Agent Logs Conformance Testing More Resource Labs Additional course details: Nexus Humans Kubernetes for App Developers 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 Kubernetes for App Developers 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 class is intended for network engineers and network admins that are either using Google Cloud Platform or are planning to do so. The class is also for individuals that want to be exposed to software-defined networking solutions in the cloud. Overview Configure Google VPC networks, subnets, and routers Control administrative access to VPC objects Control network access to endpoints in VPCsInterconnect networks among GCP projects Interconnect networks among GCP VPC networks and on-premises or other-cloud networks Choose among GCP load balancer and proxy options and configure them Use Cloud CDN to reduce latency and save money Optimize network spend using Network TiersConfigure Cloud NAT or Private Google Access to provide instances without public IP addresses access to other services Deploy networks declaratively using Cloud Deployment Manager or Terraform Design networks to meet common customer requirements Configure monitoring and logging to troubleshoot networks problems Learn about the broad variety of networking options on Google Cloud. This course uses lectures, demos, and hands-on labs to help you explore and deploy Google Cloud networking technologies, including Virtual Private Cloud (VPC) networks, subnets, and firewalls; interconnection among networks; load balancing; Cloud DNS; Cloud CDN; and Cloud NAT. You'll also learn about common network design patterns and automated deployment using Cloud Deployment Manager or Terraform. Google Cloud VPC Networking Fundamentals Recall that networks belong to projects. Explain the differences among default, auto, and custom networks. Create networks and subnets. Explain how IPv4 addresses are assigned to Compute Engine instances. Publish domain names using Google Cloud DNS. Create Compute Engine instances with IP aliases. Create Compute Engine instances with multiple virtual network. Controlling Access to VPC Networks Outline how IAM policies affect VPC networks. Control access to network resources using service accounts. Control access to Compute Engine instances with tag-based firewall rules. Sharing Networks across Projects Outline the overall workflow for configuring Shared VPC. Differentiate between the IAM roles that allow network resources to be managed. Configure peering between unrelated VPC Networks. Recall when to use Shared VPC and when to use VPC Network Peering. Load Balancing Recall the various load balancing services. Configure Layer 7 HTTP(S) load balancing. Whitelist and blacklist IP traffic with Cloud Armor. Cache content with Cloud CDN. Explain Layer 4 TCP or SSL proxy load balancing. Explain regional network load balancing. Configure internal load balancing. Recall the choices for enabling IPv6 Internet connectivity for Google Cloud load balancers. Determine which Google Cloud load balancer to use when. Hybrid Connectivity Recall the Google Cloud interconnect and peering services available to connect your infrastructure to Google Cloud. Explain Dedicated Interconnect and Partner Interconnect. Describe the workflow for configuring a Dedicated Interconnect. Build a connection over a VPN with Cloud Router. Determine which Google Cloud interconnect service to use when. Explain Direct Peering and Partner Peering. Determine which Google Cloud peering service to use when. Networking Pricing and Billing Recognize how networking features are charged for. Use Network Service Tiers to optimize spend. Determine which Network Service Tier to use when. Recall that labels can be used to understand networking spend. Network Design and Deployment Explain common network design patterns. Configure Private Google Access to allow access to certain Google Cloud services from VM instances with only internal IP addresses. Configure Cloud NAT to provide your instances without public IP addresses access to the internet. Automate the deployment of networks using Deployment Manager or Terraform. Launch networking solutions using Cloud Marketplace. Network Monitoring and Troubleshooting Configure uptime checks, alerting policies and charts for your network services. Use VPC Flow Logs to log and analyze network traffic behavior.

Duration 5 Days 30 CPD hours This course is intended for This course is intended for: Network administrators Network engineers with little or no programming or Python experience Network managers Systems engineers Overview After taking this course, you should be able to: Create a Python script Describe data types commonly used in Python coding Describe Python strings and their use cases Describe Python loops, conditionals, operators, and their purposes and use cases Describe Python classes, methods, functions, namespaces, and scopes Describe the options for Python data manipulation and storage Describe Python modules and packages, their uses, and their benefits Explain how to manipulate user input in Python Describe error and exception management in Python Describe Python code debugging methods The Programming for Network Engineers (PRNE) v2.0 course is designed to equip you with fundamental skills in Python programming. Through a combination of lectures and lab experience in simulated network environments, you will learn to use Python basics to create useful and practical scripts with Netmiko to retrieve data and configure network devices. Upon completion of this course, you should have a basic understanding of Python, including the knowledge to create, apply, and troubleshoot simple network automation scripts. Course outline Introducing Programmability and Python for Network Engineers Scripting with Python Examining Python Data Types Manipulating Strings Describing Conditionals, Loops, and Operators Exploring Classes, Methods, Functions, Namespaces, and Scopes Exploring Data Storage Options Exploring Python Modules and Packages Gathering and Validating User Input Analyzing Exceptions and Error Management Examining Debugging Methods Course Summary Lab outline Execute Your First Python Program Use the Python Interactive Shell Explore Foundation Python Data Types Explore Complex Python Data Types Use Standard String Operations Use Basic Pattern Matching Reformat MAC Addresses Use the if-else Construct Use for Loops Use while Loops Create and Use Functions Create and Use Classes Use the Python main() Construct Traverse the File Structure Read Data in Comma-Separated Values (CSV) Format Read, Store, and Retrieve Data in XML Format Read, Store, and Retrieve Date in JavaScript Object Notation (JSON) Format Read, Store, and Retrieve Data in a Raw or Unstructured Format Import Modules from the Python Standard Library Import External Libraries Create a Python Module Prompt the User for Input Use Command-Line Arguments Manage Exceptions with the try-except Structure Manage Exceptions with the try-except-finally Structure Use Assertions Use Simple Debugging Methods Use the Python Debugger Code a Practical Debugging Script

Duration 4 Days 24 CPD hours This course is intended for This course is intended for: Network administrators Network engineers with little or no programming or Python experience Network managers Systems engineers Overview After taking this course, you should be able to: Create a Python script Describe data types commonly used in Python coding Describe Python strings and their use cases Describe Python loops, conditionals, operators, and their purposes and use cases Describe Python classes, methods, functions, namespaces, and scopes Describe the options for Python data manipulation and storage Describe Python modules and packages, their uses, and their benefits Explain how to manipulate user input in Python Describe error and exception management in Python Describe Python code debugging methods The Programming for Network Engineers (PRNE) v2.0 course is designed to equip you with fundamental skills in Python programming. Through a combination of lectures and lab experience in simulated network environments, you will learn to use Python basics to create useful and practical scripts with Netmiko to retrieve data and configure network devices. Upon completion of this course, you should have a basic understanding of Python, including the knowledge to create, apply, and troubleshoot simple network automation scripts. Course Outline Introducing Programmability and Python for Network Engineers Scripting with Python Examining Python Data Types Manipulating Strings Describing Conditionals, Loops, and Operators Exploring Classes, Methods, Functions, Namespaces, and Scopes Exploring Data Storage Options Exploring Python Modules and Packages Gathering and Validating User Input Analyzing Exceptions and Error Management Examining Debugging Methods Course Summary

Duration 0.5 Days 3 CPD hours This course is intended for This course is primarily designed for business leaders, consultants, product and project managers, and other decision-makers who are interested in growing the business by leveraging the power of AI. Other individuals who wish to explore basic AI concepts are also candidates for this course. This course is also designed to assist students in preparing for the CertNexus AIBIZ™ (Exam AIZ-210) credential. Overview In this course, you will identify ways in which AI can bring significant value to the business. You will: Describe AI fundamentals. Identify the functions of AI in business. Implement business requirements for AI. Artificial intelligence (AI) is not just another technology or process for the business to consider?it is a truly disruptive force, one that delivers an entirely new level of results across business sectors. Even organizations that resist adopting AI will feel its impact. If the organization wants to thrive and survive in this transforming business landscape, it will need to harness the power of AI. This course is designed to help business professionals conquer and move beyond the basics of AI to apply AI concepts for the benefit of the business. It will give you the essential knowledge of AI you'll need to steer the business forward. Lesson 1: AI Fundamentals Topic A: A Brief History of AI Topic B: AI Concepts Lesson 2: Functions of AI in Business Topic A: Improve User Experiences Topic B: Segment Audiences Topic C: Secure Assets Topic D: Optimize Processes Lesson 3: Implementing Business Requirements for AI Topic A: Identify Design Requirements Topic B: Identify Data Requirements Topic C: Identify Risks in Implementing AI Topic D: Develop an AI Strategy

Duration 3 Days 18 CPD hours This course is intended for Cloud Solutions Architects, DevOps Engineers. Individuals using Google Cloud Platform to create new solutions or to integrate existing systems, application environments, and infrastructure with a focus on Google Compute Engine. Overview Configure VPC networks and virtual machines Administer Identity and Access Management for resources Implement data storage services in GCP Manage and examine billing of GCP resources Monitor resources using Stackdriver services Connect your infrastructure to GCP Configure load balancers and autoscaling for VM instances Automate the deployment of GCP infrastructure services Leverage managed services in GCP This class introduces participants to the comprehensive and flexible infrastructure and platform services provided by Google Cloud Platform, with a focus on Compute Engine. Through a combination of presentations, demos, and hands-on labs, participants explore and deploy solution elements, including infrastructure components such as networks, systems, and application services. This course also covers deploying practical solutions including securely interconnecting networks, customer-supplied encryption keys, security and access management, quotas and billing, and resource monitoring. Introduction to Google Cloud Platform List the different ways of interacting with GCP Use the GCP Console and Cloud Shell Create Cloud Storage buckets Use the GCP Marketplace to deploy solutions Virtual Networks List the VPC objects in GCP Differentiate between the different types of VPC networks Implement VPC networks and firewall rules Design a maintenance server Virtual Machines Recall the CPU and memory options for virtual machines Describe the disk options for virtual machines Explain VM pricing and discounts Use Compute Engine to create and customize VM instances Cloud IAM Describe the Cloud IAM resource hierarchy Explain the different types of IAM roles Recall the different types of IAM members Implement access control for resources using Cloud IAM Storage and Database Services Differentiate between Cloud Storage, Cloud SQL, Cloud Spanner, Cloud Firestore and Cloud Bigtable Choose a data storage service based on your requirements Implement data storage services Resource Management Describe the cloud resource manager hierarchy Recognize how quotas protect GCP customers Use labels to organize resources Explain the behavior of budget alerts in GCP Examine billing data with BigQuery Resource Monitoring Describe the Stackdriver services for monitoring, logging, error reporting, tracing, and debugging Create charts, alerts, and uptime checks for resources with Stackdriver Monitoring Use Stackdriver Debugger to identify and fix errors Interconnecting Networks Recall the GCP interconnect and peering services available to connect your infrastructure to GCP Determine which GCP interconnect or peering service to use in specific circumstances Create and configure VPN gateways Recall when to use Shared VPC and when to use VPC Network Peering Load Balancing and Autoscaling Recall the various load balancing services Determine which GCP load balancer to use in specific circumstances Describe autoscaling behavior Configure load balancers and autoscaling Infrastructure Automation Automate the deployment of GCP services using Deployment Manager or Terraform Outline the GCP Marketplace Managed Services Describe the managed services for data processing in GCP Additional course details: Nexus Humans Architecting with Google Compute Engine 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 Architecting with Google Compute Engine 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 solid Python skills who wish to learn and use basic machine learning algorithms and concepts 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. Topics Covered: This is a high-level list of topics covered in this course. Please see the detailed Agenda below Getting Started & Optional Python Quick Refresher Statistics and Probability Refresher and Python Practice Probability Density Function; Probability Mass Function; Naive Bayes Predictive Models Machine Learning with Python Recommender Systems KNN and PCA Reinforcement Learning Dealing with Real-World Data Experimental Design / ML in the Real World Time Permitting: Deep Learning and Neural Networks Machine Learning Essentials with Python is a foundation-level, three-day hands-on course that teaches students core skills and concepts in modern machine learning practices. This course is geared for attendees experienced with Python, but new to machine learning, who need introductory level coverage of these topics, rather than a deep dive of the math and statistics behind Machine Learning. Students will learn basic algorithms from scratch. For each machine learning concept, students will first learn about and discuss the foundations, its applicability and limitations, and then explore the implementation and use, reviewing and working with specific use casesWorking in a hands-on learning environment, led by our Machine Learning expert instructor, students will learn about and explore:Popular machine learning algorithms, their applicability and limitationsPractical application of these methods in a machine learning environmentPractical use cases and limitations of algorithms Getting Started Installation: Getting Started and Overview LINUX jump start: Installing and Using Anaconda & Course Materials (or reference the default container) Python Refresher Introducing the Pandas, NumPy and Scikit-Learn Library Statistics and Probability Refresher and Python Practice Types of Data Mean, Median, Mode Using mean, median, and mode in Python Variation and Standard Deviation Probability Density Function; Probability Mass Function; Naive Bayes Common Data Distributions Percentiles and Moments A Crash Course in matplotlib Advanced Visualization with Seaborn Covariance and Correlation Conditional Probability Naive Bayes: Concepts Bayes? Theorem Naive Bayes Spam Classifier with Naive Bayes Predictive Models Linear Regression Polynomial Regression Multiple Regression, and Predicting Car Prices Logistic Regression Logistic Regression Machine Learning with Python Supervised vs. Unsupervised Learning, and Train/Test Using Train/Test to Prevent Overfitting Understanding a Confusion Matrix Measuring Classifiers (Precision, Recall, F1, AUC, ROC) K-Means Clustering K-Means: Clustering People Based on Age and Income Measuring Entropy LINUX: Installing GraphViz Decision Trees: Concepts Decision Trees: Predicting Hiring Decisions Ensemble Learning Support Vector Machines (SVM) Overview Using SVM to Cluster People using scikit-learn Recommender Systems User-Based Collaborative Filtering Item-Based Collaborative Filtering Finding Similar Movie Better Accuracy for Similar Movies Recommending movies to People Improving your recommendations KNN and PCA K-Nearest-Neighbors: Concepts Using KNN to Predict a Rating for a Movie Dimensionality Reduction; Principal Component Analysis (PCA) PCA with the Iris Data Set Reinforcement Learning Reinforcement Learning with Q-Learning and Gym Dealing with Real-World Data Bias / Variance Tradeoff K-Fold Cross-Validation Data Cleaning and Normalization Cleaning Web Log Data Normalizing Numerical Data Detecting Outliers Feature Engineering and the Curse of Dimensionality Imputation Techniques for Missing Data Handling Unbalanced Data: Oversampling, Undersampling, and SMOTE Binning, Transforming, Encoding, Scaling, and Shuffling Experimental Design / ML in the Real World Deploying Models to Real-Time Systems A/B Testing Concepts T-Tests and P-Values Hands-on With T-Tests Determining How Long to Run an Experiment A/B Test Gotchas Capstone Project Group Project & Presentation or Review Deep Learning and Neural Networks Deep Learning Prerequisites The History of Artificial Neural Networks Deep Learning in the TensorFlow Playground Deep Learning Details Introducing TensorFlow Using TensorFlow Introducing Keras Using Keras to Predict Political Affiliations Convolutional Neural Networks (CNN?s) Using CNN?s for Handwriting Recognition Recurrent Neural Networks (RNN?s) Using an RNN for Sentiment Analysis Transfer Learning Tuning Neural Networks: Learning Rate and Batch Size Hyperparameters Deep Learning Regularization with Dropout and Early Stopping The Ethics of Deep Learning Learning More about Deep Learning Additional course details: Nexus Humans Machine Learning Essentials with Python (TTML5506-P) 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 Machine Learning Essentials with Python (TTML5506-P) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 5 Days 30 CPD hours This course is intended for System administrators and system integrators responsible for designing, implementing, and managing VMware Aria Automation Overview By the end of the course, you should be able to meet the following objectives: Describe the VMware Aria Automation architecture and use cases in cloud environments Describe the key services of VMware Cloud Automation Services™ Manage VMware Aria Automation entities on VMware and third-party virtual and cloud infrastructures Install VMware Aria Automation with VMware Aria Suite Lifecycle Configure and manage cloud accounts, projects, flavor mappings, image mappings, network profiles, storage profiles, volumes, tags, and services Create, modify, manage, and deploy VMware Aria Automation Templates Customize services and virtual machines with cloudConfig and cloudbase-init Configure and manage VMware Aria Automation Consumption Configure and manage ABX actions, custom properties, event broker subscriptions, and VMware Aria Automation Orchestrator workflows Connect to a Kubernetes cluster and manage namespaces Use VMware Aria Automation Config to configure and deploy systems Use logs and CLI commands to monitor and troubleshoot VMware Aria Automation During this five-day course, you focus on installing, configuring, and managing VMware Aria Automation 8.10? on-premises systems. You learn how it can be used to automate the delivery of virtual machines, applications, and personalized IT services across different data centers and hybrid cloud environments. The course covers how VMware Aria Automation Consumption? can aggregate content in native formats from multiple clouds and platforms into a common catalog.This course also covers interfacing VMware Aria Automation with other systems using VMware Aria Orchestrator and how to use VMware Aria Automation to manage Kubernetes systems and leverage other systems. In this course, you will use VMware Aria Automation Config? as a configuration management tool. Course Introduction Introductions and course logistics Course objectives VMware Aria Automation Overview and Architecture Describe the purpose and functionality of VMware Aria Automation Identify the key services offered by VMware Aria Automation Describe the VMware Aria Automation architecture Describe the use of VMware Workspace ONE Access? Describe the relationship between Kubernetes clusters, container, and VMware Aria Automation services Installing VMware Aria Automation List the different VMware Aria Automation deployment types Describe the purpose of Easy Installer Describe the VMware Aria Automation installation process Authentication and Authorization Identify the steps to integrating Workspace ONE© Access with Active Directory Describe the features of Workspace ONE Access Describe the user roles available in VMware Aria Automation Identify the key tasks performed by each user role Define custom roles Configure branding and multitenancy Basic Initial Configuration Create a basic configuration with a cloud account, cloud zone, project, flavor mapping, and image mapping VMware Aria Automation Templates Configure and deploy a basic VMware Aria Automation template Create a VMware Aria Automation template that can run on any cloud Use cloudConfig and cloudbase-init to run commands, create users, and install software Use YAML for inputs, variables, and conditional deployments Tags Configure tags Describe functions of tags Manage tags Storage Configuration Configure storage profiles Use tags and storage profiles Integrating NSX With VMware Aria Automation List the capabilities and use cases of VMware NSX© Describe the NSX architecture and components Integrate NSX with VMware Aria Automation List the supported network profiles in VMware Aria Automation Use the NSX components to design a multitier application with VMware Aria Automation Templates Identify the network and security options available in design canvas Create and manage on-demand networks and security groups Configure NSX Day 2 actions Integrating with Public Clouds Configure and use VMware Cloud Foundation? accounts Integrate VMware Cloud Director? account Configure and use an AWS cloud account Configure and use an Azure cloud account Configure and use a Google Cloud Platform cloud account Integrate VMware Cloud on AWS cloud account Using VMware Aria Automation Consumption Release a VMware Aria Automation template Define content source and content sharing Define VMware Aria Automation policy enforcement Use custom forms for catalog items VMware Aria Automation Extensibility Describe VMware Aria Automation extensibility Use event topics Create a subscription Call a VMware Aria Automation Orchestrator workflow Create ABX actions Using Kubernetes Clusters Introduction to Kubernetes Connect to an existing Kubernetes Cluster Create a VMware Aria Automation template with Kubernetes components Using VMware Aria Automation Config for Configuration Management Describe VMware Aria Automation Config Use VMware Aria Automation Config for software deployment Use VMware Aria Automation Config for configuration management Use VMware Aria Automation Config with event-driven orchestration VMware Aria Automation Troubleshooting and Integration Demonstrate how to monitor deployment history Demonstrate basic troubleshooting Execute CLI commands Explain how to collect logs Describe integration with VMware Aria Operations for Logs Describe integration with VMware Aria Operations

Duration 3 Days 18 CPD hours This course is intended for Experienced system administrators and network administrators Customers, cloud architects, systems engineers, data center administrators Network administrators with experience in managed services or managing a Telco Cloud environment Overview By the end of the course, you should be able to meet the following objectives: Deploy VMware Telco Cloud Service Assurance Manage VMware Telco Cloud Service Assurance to satisfy Telco cloud provider needs Discuss configurable options for VMware Telco Cloud Service Assurance Identify and configure different data sources which are used with VMware Telco Cloud Service Assurance Configure different collectors in VMware Telco Cloud Service Assurance Identify the Root Cause Analysis options with VMware Telco Cloud Service Assurance Discuss data collection in VMware Telco Cloud Service Assurance Explain root cause analysis in VMware Telco Cloud Service Assurance Navigate through the logs for troubleshooting This three-day, hands-on training course provides the knowledge, skills, and tools to achieve competency in installing, configuring, and managing the VMware Telco Cloud Service Assurance environment. In this course, you are introduced to the installation methods of VMware Telco Cloud Service Assurance? across various supported platforms and troubleshooting tools that help you install, manage, and troubleshoot your VMware Telco Cloud Service Assurance environment. In addition, you are presented with various types of configuration options, which you will identify, analyze, and navigate through as you explore the UI and configurable options of the product. Course Introduction Introduction and course logistics Course objectives Introduction to VMware Telco Cloud Service Assurance Describe the features of VMware Telco Cloud Service Assurance List the capabilities of VMware Telco Cloud Service Assurance Discuss the use cases of VMware Telco Cloud Service Assurance Describe the role played by VMware Telco Cloud Service Assurance components in delivering service assurance Deploying VMware Telco Cloud Service Assurance Explain different deployment options of VMware Telco Cloud Service Assurance Identify different deployment methods of VMware Telco Cloud Service Assurance Discuss different phases in deploying VMware Telco Cloud Service Assurance Identify different footprints available for HA based and non-HA based installation of VMware Telco Cloud Service Assurance Describe the SMARTs components of VMware Telco Cloud Service Assurance Deploy VMware Telco Cloud Service Assurance User Access Control Describe the features Role-based Access Control (RBAC) Outline the role of Keycloak in implementing RBAC in VMware Telco Cloud Service Assurance Configure user federation in Keycloak Use the VMware Telco Cloud Service Assurance UI to manage RBAC Create policies in VMware Telco Cloud Service Assurance that align with job roles Services and User Interface Configurations Describe the architecture of logical switching Describe the core services on a TCSA cluster Discuss the Global Manager or Service Assurance Manager (SAM), IP Domain Manager, Server Manager (ESM) Discuss VMware Telco Cloud Service Assurance UI Overview Explain Working with Notifications Elaborate Configuring Summary's Describe Accessing Notification Details Explain Viewing and configuring Topologies List Customizing Topologies Describe Topology Explorer Explain Collecting Troubleshooting Information Discuss Custom models Describe how compute resources are provided to VMware Telco Cloud Service Assurance Describe how storage is provided to VMware Telco Cloud Service Assurance Configure and manage VMware Telco Cloud Service Assurance Discuss configurable options for VMware Telco Cloud Service Assurance Day 1 and Day 2 Operations Review the architecture of logical routing and NSX Edge nodes Identify different data sources to be used with VMware Telco Cloud Service Assurance Configure different collectors with VMware Telco Cloud Service Assurance Describe Alarms and Thresholds Demonstrate how to configure alarms with VMware Telco Cloud Service Assurance Explain how to setup thresholds and timelines in VMware Telco Cloud Service Assurance Define Catalog management and sharing catalogs inside and between organizations. Identify the steps to import or upload data into catalogs. Explain the purpose of catalogs and How to Create a catalog organization. Describe the Purpose and Usage of Open Virtualization Format (OVA) and Custom vApp or VM Properties. Discuss vApp Templates Logs and Troubleshooting Review the architecture of the Distributed Firewall Discuss VMware Telco Cloud Service Assurance installations logs List Smarts installation logs Explain backup and restore options of VMware Telco Cloud Service Assurance Identify the approach for troubleshooting containerized services Discuss monitoring services

Duration 5 Days 30 CPD hours This course is intended for This course is designed for professionals in job roles such as: Communication engineers Project managers Network engineers Software engineers System architects The Developing Applications for Cisco Webex and Webex Devices (DEVWBX) v1.1 course prepares you to use the programmability features of Webex©, Cisco© enterprise solution for video conferencing, online meetings, online training, webinars, web conferencing, cloud calling, and collaboration. Through a combination of lessons and hands-on labs, you will learn about Webex Application Programming Interface (API) Foundation, meetings, devices, teams, messaging, embedding Cisco Webex, administration, and compliance. You will learn how to leverage Webex APIs to extend the functionalities of teams, meetings, and devices, and explore how these APIs can help automate, administer, and enforce compliance. This course prepares you for the 300-920 Developing Applications for Cisco Webex and Webex Devices (DEVWBX) exam. Introducing Webex APIs Foundations Webex as an Extensible Platform Building Cisco Webex Teams Applications Introduction to Webex Messaging Developing with Webex Meetings XML API Describe the Capabilities of Cisco Webex Meetings APIs Automating and Extending Cisco Collaboration Devices with xAPI Overview, Capabilities and Transport Methods for Cisco Endpoint Device Programmability Embedding Cisco Webex Benefits of Embedding Cisco Webex into Other Applications Managing Administration and Compliance with Cisco Webex APIs Administer a Cisco Webex Organization