442 Algorithm courses

Duration 5 Days 30 CPD hours This course is intended for Experienced system administrators and network administrators Overview By the end of the course, you should be able to meet the following objectives: Describe the NSX Advanced Load Balancer architecture Describe the NSX Advanced Load Balancer components and main functions Explain the NSX Advanced Load Balancer key features and benefits Deploy and configure the NSX Advanced Load Balancer infrastructure within private or public clouds using Write and No-Access Cloud Connectors Explain, deploy, and configure Service Engines Explain and configure local load balancing constructs such as virtual services, pools, health monitors, and related components Explain and configure advanced virtual services and related concepts such as Subject Name Indication, Enhanced Virtual Hosting, and authentication of virtual services Explain and modify application behavior through profiles, policies, and DataScripts Describe Central licensing management using VMware NSX Advanced Load Balancer Enterprise with Cloud services (formerly Avi Pulse) Explain how to configure Role-Based Access Control (RBAC) in NSX Advanced Load Balancer Configure advanced services such as global server load balancing Describe how to use NSX Advanced Load Balancer REST API interfaces and related automation capabilities Describe and configure NSX Advanced Load Balancer application and infrastructure monitoring Gather relevant information and perform basic troubleshooting of applications that use built-in NSX Advanced Load Balancer tooling Identify the key features of VMware NSX Network Detection and Response This five-day, fast-paced course provides comprehensive training to install, configure, and manage a VMware NSX Advanced Load Balancer (Avi Networks) solution. This course covers key NSX Advanced Load Balancer (Avi Networks) features and functionality offered in the NSX Advanced Load Balancer 21.x release. Features include the overall infrastructure, virtual services, application components, global server load balancing, various cloud connectors, application troubleshooting, and solution monitoring. Hands-on labs provide access to a software-defined data center environment to reinforce the skills and concepts presented in the course. Course Introduction Introduction and course logistics Course objectives Introduction to NSX Advanced Load Balancer Introduce NSX Advanced Load Balancer Discuss NSX Advanced Load Balancer use cases and benefits Explain NSX Advanced Load Balancer architecture and components Explain the management, control, data, and consumption planes and their respective functions Virtual Services Configuration Concepts Explain virtual service components Explain virtual service types Explain and configure basic virtual service components such as application profiles and network profiles Virtual Services Configuration Advanced Concepts Explain the virtual service advanced components such as Wildcard VIP, Server Name Identification (SNI), and Enhanced Virtual Hosting (EVH) Explain the concept of virtual service VIP Sharing Explain different authentication mechanisms used for a virtual service such as LDAP, SAML, JSON Web Token, and OAUTH Profiles and Policies Explain application profiles and types such as L4, DNS, Syslog, HTTP, and VMware Horizon VDI Explain and configure advanced application HTTP profile options Describe network profiles and types Explain and configure SSL profiles and certificates Explain and configure HTTP, network, and DNS policies Pools Configuration Concepts Explain pools configuration options Describe the available load balancing algorithms Explain multiple health monitor types Explain multiple Persistence profiles Explain and configure pool groups Modifying Application Behavior Design and apply application solutions by using application profiles Design and apply application solutions by using network, HTTP policies, and DataScripts Explain DataScript fundamentals Explain and use NSX Advanced Load Balancer analytics to understand application behavior Describe and configure client SSL certificate validation Describe and configure virtual service DDoS, Rate limiting, and Throttling capabilities Modify network profile properties such as TCP connection properties Design and apply application solutions by using Persistence profiles NSX Advanced Load Balancer Infrastructure Architecture Explain management, control, data, and consumption planes and functions Describe control plane clustering and high availability Describe controller sizing and process sharing Describe Service Engine CPU and NIC architecture Explain tenants Configure properties of Service Engine groups Explain Service Engine group high availability modes Describe and configure active-standby high availability mode Explain Service Engine placement in multiple availability zones for public clouds Describe and configure elastic HA high availability mode (Active-Active, N+M) Explain Service Engine failure detection and self-healing Describe Service Engine as a router Explain virtual service scale-out options such as Layer 2 (Native), Layer 3 (BGP), and DNS-based Describe how to upgrade NSX Advanced Load Balancer Introduction to Cloud Connector Explain cloud connectors Review cloud connector integration modes List cloud connector types Review the different Service Engine image types in different ecosystems Installing, Configuring, and Managing NSX Advanced Load Balancer in No-Orchestrator Cloud Explain No-Access cloud concepts Configure No-Access cloud integration on bare metal Explain and configure Linux Server Cloud Explain and configure VMware No Orchestrator Describe the advanced configuration options available in bare metal (Linux Server Cloud) Installing, Configuring, and Managing NSX Advanced Load Balancer in VMware Environment: Cloud Configuration Introduce VMware integration options Explain and configure VMware Write Access Cloud Connector Explain NSX Advanced Load Balancer integration options in a VMware NSX environment Explain and configure NSX Cloud Connector for Overlay and VLAN-backed segments AWS Cloud Configuration Describe NSX Advanced Load Balancer public cloud integrations Explain different AWS components Explain and demonstrate AWS public cloud integration Deploy VMware NSX Advanced Load Balancer Controller, SEs, and virtual services in AWS Cloud Review Multi-AZ Support for virtual services in AWS cloud GCP Cloud Configuration Explain different GCP components Explain and demonstrate GCP public cloud integration Deploy NSX Advanced Load Balancer Controller, SEs, and virtual services in GCP cloud Azure Cloud Configuration Describe NSX Advanced Load Balancer public cloud integrations Explain different Microsoft Azure components Explain and demonstrate Azure public cloud integration Deploy NSX Advanced Load Balancer Controller, SEs, and virtual services in Azure Cloud NSX Advanced Load Balancer Enterprise with Cloud Services (Avi Pulse) Describe NSX Advanced Load Balancer public cloud services Explain different features of NSX Advanced Load Balancer Cloud Services Register the controller with Cloud Services DNS Foundations Review, discuss, and explain DNS fundamentals Describe NSX Advanced Load Balancer DNS and IPAM providers Global Server Load Balancing (GSLB) Introduce Global Server load balancing concepts and benefits Explain and configure the NSX Advanced Load Balancer infrastructure Explain and configure the DNS Virtual Service components Explain and configure GSLB Service Engine Group Describe and configure GSLB sites Explain and configure basic GSLB services to include pools and health monitors Describe GSLB Server Load Balancing algorithms Explain and configure health monitors based on data plane and control plane Describe GSLB Health Monitor Proxy Explain GSLB Site-Cookie Persistence Explain the different GSLB replication methods Role-Based Access Control (RBAC) Introduce local authentication in NSX Advanced Load Balancer Introduce remote authentication in NSX Advanced Load Balancer Review the different types of remote authentication Explain granular RBAC using labels NSX Advanced Load Balancer: Troubleshooting Introduce infrastructure and application troubleshooting concepts Describe troubleshooting based on control plane and data plane Explain application analytics and logs Describe client logs analysis Explain headers troubleshooting and packet capture mechanism Describe how to use CLI for detailed data plane troubleshooting Explain Service Engine logs Explain health monitors troubleshooting Explain BGP session troubleshooting Describe control plane troubleshooting, clustering, and cloud connector issues Events and Alerts Describe NSX Advanced Load Balancer events Describe and configure NSX Advanced Load Balancer alerts Describe NSX Advanced Load Balancer monitoring capabilities with SNMP, Syslog, and Email Introduction to NSX Advanced Load Balancer Rest API Introduce the NSX Advanced Load Balancer REST API interface Describe REST API Object Schema Explain and interact with REST API interface with

Duration 4 Days 24 CPD hours This course is intended for Project administrators and ETL developers responsible for data extraction and transformation using DataStage. Overview Describe the uses of DataStage and the DataStage workflowDescribe the Information Server architecture and how DataStage fits within itDescribe the Information Server and DataStage deployment optionsUse the Information Server Web Console and the DataStage Administrator client to create DataStage users and to configure the DataStage environmentImport and export DataStage objects to a fileImport table definitions for sequential files and relational tablesDesign, compile, run, and monitor DataStage parallel jobsDesign jobs that read and write to sequential filesDescribe the DataStage parallel processing architectureDesign jobs that combine data using joins and lookupsDesign jobs that sort and aggregate dataImplement complex business logic using the DataStage Transformer stageDebug DataStage jobs using the DataStage PX Debugger This course enables the project administrators & developers to acquire the skills necessary to develop parallel jobs in DataStage. Students will learn to create parallel jobs that access sequential & relational data, and combine and transform the data. Course Outline Introduction to DataStage Deployment DataStage Administration Work with Metadata Create Parallel Jobs Access Sequential Data Partitioning and Collecting Algorithms Combine Data Group Processing Stages Transformer Stage Repository Functions Work with Relational Data Control Jobs

Duration 1 Days 6 CPD hours This course is intended for Experienced system administrators or network administrators Overview By the end of the course, you should be able to meet the following objectives: Describe NSX Advanced Load Balancer architecture Describe the NSX Advanced Load Balancer components and main functions Explain the NSX Advanced Load Balancer key features and benefits Explain and configure Local Load Balancing constructors such as Virtual Services, Pools, Health Monitors and related components During this one-day course, you gain an understanding of the architecture and features of VMware NSX Advanced Load Balancer (Avi Networks) solution. This course provides hands-on labs to provide a solid foundation to load balancing fundamentals and work with most common load balancing functionality offered by VMware NSX Advanced Load Balancer (Avi Networks) solution. Course Introduction Introductions and course logistics Course objectives Introduction to NSX Advanced Load Balancer Introduce NSX Advanced Load Balancer Discuss NSX Advanced Load Balancer use cases and benefits Explain NSX Advanced Load Balancer architecture and components Explain the management, control, data, and consumption planes and their respective functions Virtual Services Configuration Concepts Explain Virtual Service components Explain Virtual Service types Explain and configure basic virtual services components such as Application Profiles, Network Profiles, Pools and Health Monitors Profiles and Policies Explain and deep dive on Advanced Virtual Service creation Explain and deep dive on Application Profiles and Types such as L4, DNS, Syslog and HTTP Explain and configure advanced application HTTP Profile options Deep dive on Network Profiles and Types Explain and configure SSL Profiles and Certificates Explain and Configure HTTP and DNS policies Pools Configuration Concepts Explain and deep dive on Pools configuration options Describe available Load Balancing algorithms Explain multiple Health Monitor types Explain multiple Persistence Profiles Explain and configure Pool Groups

Duration 3 Days 18 CPD hours This course is intended for Business application consultant Data Consultant / Manager Database Administrator Application developer BI specialist Overview This course will prepare you to: Understand and put into practice the main advanced modeling capabilities of SAP HANA 2.0 SPS04 in the areas of text search and analysis, graph modeling, spatial analysis and predictive modeling. Promote these advanced modeling capabilities to extend the core SAP HANA Modeling features. Broaden your experience with the modern SAP HANA tooling in XS Advanced (SAP Web IDE for SAP HANA) This course provides advanced knowledge and practical experience on several topics that are included in, or connected to, the scope of the modeler role. Its purpose is to take a step further, beyond the core modeling knowledge from HA300, and to demonstrate how applications powered by SAP HANA can benefit from innovations such as Spatial Data Storage and Processing, Text Search and Analysis, Predictive Analysis and Graph Modeling.The course is supported by many demos and exercise, which demonstrate the advanced modeling capabilities in several scenarios. For example, working with classical schemas or HDI containers in XS Advanced, using the SQL console, developing graphical models. Some of the proposed case studies blend together several modeling capabilities, such as text with spatial, or text with graph.An introduction to SAP HANA Series Data is also provided. Introduction to Advanced ModelingSAP HANA Predictive Analysis Library (PAL) Describing SAP HANA PAL Using PAL in Flowgraphs Calling PAL Functions in Calculation Views Calling PAL Procedures in SQL Scripts Exploring the PAL Library SAP HANA Spatial Introducing SAP HANA Spatial Working with Spatial Data Types Importing and Exporting Spatial Data Accessing and Manipulating Spatial Data Using Spatial Clustering SAP HANA Graph Defining SAP HANA Graph Workspace Describing the Different Graph Algorithms Using the Graph Node in Calculation Views Using GraphScript Procedures SAP HANA Text Understanding Full Text Search Understanding Text Analysis Understanding Text Mining SAP HANA Series Data Getting Started with SAP HANA Series Data

Duration 3 Days 18 CPD hours This course is intended for Java Fundamentals is designed for tech enthusiasts who are familiar with some programming languages and want a quick introduction to the most important principles of Java. Overview After completing this course, you will be able to: Create and run Java programs Use data types, data structures, and control flow in your code Implement best practices while creating objects Work with constructors and inheritance Understand advanced data structures to organize and store data Employ generics for stronger check-types during compilation Learn to handle exceptions in your code Since its inception, Java has stormed the programming world. Its features and functionalities provide developers with the tools needed to write robust cross-platform applications. Java Fundamentals introduces you to these tools and functionalities that will enable you to create Java programs. The course begins with an introduction to the language, its philosophy, and evolution over time, until the latest release. You'll learn how the javac/java tools work and what Java packages are - the way a Java program is usually organized. Once you are comfortable with this, you'll be introduced to advanced concepts of the language, such as control flow keywords. You'll explore object-oriented programming and the part it plays in making Java what it is. In the concluding lessons, you'll be familiarized with classes, typecasting, and interfaces, and understand the use of data structures, arrays, strings, handling exceptions, and creating generics. Introduction to Java The Java Ecosystem Our First Java Application Packages Variables, Data Types, and Operators Variables and Data Types Integral Data Types Type casting Control Flow Conditional Statements Looping Constructs Object-Oriented Programming Object-Oriented Principles Classes and Objects Constructors The this Keyword Inheritance Overloading Constructor Overloading Polymorphism and Overriding Annotations References OOP in Depth Interfaces Typecasting The Object Class Autoboxing and Unboxing Abstract Classes and Methods Data Structures, Arrays, and Strings Data Structures and Algorithms Strings The Java Collections Framework and Generics Reading Data from Files The Java Collections Framework Generics Collection Advanced Data Structures in Java Implementing a Custom Linked List Implementing Binary Search Tree Enumerations Set and Uniqueness in Set Exception Handling Motivation behind Exceptions Exception Sources Exception Mechanics Best Practices

Duration 3 Days 18 CPD hours This course is intended for This class is designed for experienced Salesforce Administrators with little or no Flow experience who need to streamline business processes with no-code automated solutions. This class is not recommended for developers. However, if you are a developer interested in learning Flow, we highly recommend Declarative Development for Platform App Builders in Lightning Experience (DEX403). Overview When you complete this course, you will be able to: Create automated no-code solutions with Salesforce Flow. Analyze use cases and effectively translate requirements into design plans that detail accurate Flow building processes. Understand and leverage various Flow types, elements, and resources. Build Screen Flows and manage screen layouts and field visibility. Implement Flows on Home and Record pages. Automate business processes by creating Record-Triggered Flows (based on record create, update, or delete) to perform specific actions. Identify best practices for creating and managing Flows. Streamline business processes and automate manual tasks across your organization by building no-code automation solutions with Flow Builder. In this 3-day class designed for administrators, our experts will introduce you to Screen and Record-Trigger Flows, in addition to various Flow elements and resources. Learn how to effectively create and manage Flows that champion automation best practices, solve for user requirements, and empower you to get more out of Salesforce. Foundations of Flow Create Variables Understand Algorithms Explore Control Structures Examine Flow Best Practices Screen Flows Use Elements and Resources Control Field Visibility Manage Data and Navigation Surface a Flow Complete the Flow Record-Triggered Flows Define Flow Triggers Use Flow Triggers to Replace Formula Fields Share Records with Flow Additional course details: Nexus Humans Salesforce Automate No-Code Solutions Using Flow (ADX301) 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 Salesforce Automate No-Code Solutions Using Flow (ADX301) 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 software testers, architects, engineers, or other related roles, who wish to apply AI to software testing practices within their enterprise. While there are no specific pre-requisites for this course, it would be helpful is the attendee has familiarity with basic scripting (Python preferred) and be comfortable with working from the command line (for courses that add the optional hands-on labs). Attendees without basic scripting skills can follow along with the hands-on labs or demos. Overview This course introduces AI and related technologies from a practical applied software testing perspective. Through engaging lecture and demonstrations presented by our expert facilitator, students will explore: Exploring AI Introduction to Machine Learning Introduction to Deep Learning Introduction to Data Science Artificial Intelligence (AI) in Software Testing Implementing AI in Test Automation Innovative AI Test Automation Tools for the Future Implementing AI in Software Testing / AI in Test Automation is an introductory-level course for attendees new to AI, Machine Learning or Deep Learning who wish to automate software testing tasks leveraging AI. The course explores the essentials of AI, ML and DL and how the integrate into IT business operations and initiatives. Then the course moves to specifics about the skills, techniques and tools used to apply AI to common software testing requirements. Exploring AI AI-Initiatives The Priority: Excellence AI- Intelligence Types The Machine Learning Types The Quality Learning Initiative The Inception in Academics AI - Importance & Applications The Re-visit Learning Re-visited via AI Teaching in the world of AI Exploring AI for Self-Development AI In Academics Beyond Academics Introduction to Machine Learning What is Machine Learning? Why Machine Learning? Examples - Algorithms behind Machine Learning Introduction to Deep Learning What is Deep Learning? Why Deep Learning? Example - Deep Learning Vs Machine Learning Introduction to Data Science What is Data Science? Why Data Science? Examples - Use Cases of Data Science Artificial Intelligence (AI) in Software Testing What is AI in Software Testing? The Role of AI Testing Why do we Need AI in Software Testing? Pros and Cons of AI in Software Testing Applications of AI in Software Testing Is it time for Testers or QA Teams to worry about AI? Automated Testing with Artificial Intelligence Implementing AI in Test Automation Training the AI Bots Challenges with AI-powered Applications Examples - Real World use cases using Artificial Intelligence Demo - Facial Emotion Detection Using Artificial Intelligence Demo - Text Analysis API Using Artificial Intelligence Demo - EYE SPY Mobile App Using Artificial Intelligence Innovative AI Test Automation Tools for the Future Tools used for Implementing AI in Automation Testing What is NEXT? AI Test Automation Demo using Testim

Duration 3 Days 18 CPD hours This course is intended for Experienced DataStage developers seeking training in more advanced DataStage job techniques and who seek an understanding of the parallel framework architecture. In this course, students will develop a deeper understanding of the DataStage architecture, including a deeper understanding of the DataStage development and runtime environments. Introduction to the Parallel Framework Architecture Describe the parallel processing architecture Describe pipeline and partition parallelism Describe the role of the configuration file Design a job that creates robust test data Compiling & Executing Jobs Describe the main parts of the configuration file Describe the compile process and the OSH that the compilation process generates Describe the role and the main parts of the Score Describe the job execution process Partitioning & Collecting Data Understand how partitioning works in the Framework Viewing partitioners in the Score Selecting partitioning algorithms Generate sequences of numbers (surrogate keys) in a partitioned, parallel environment Sorting Data Sort data in the parallel framework Find inserted sorts in the Score Reduce the number of inserted sorts Optimize Fork-Join jobs Use Sort stages to determine the last row in a group Describe sort key and partitioner key logic in the parallel framework Buffering in Parallel Jobs Describe how buffering works in parallel jobs Tune buffers in parallel jobs Avoid buffer contentions Parallel Framework Data Types Describe virtual data sets Describe schemas Describe data type mappings and conversions Describe how external data is processed Handle nulls Work with complex data Reusable Components Create a schema file Read a sequential file using a schema Describe Runtime Column Propagation (RCP) Enable and disable RCP Create and use shared containers Balanced Optimization Enable Balanced Optimization functionality in Designer Describe the Balanced Optimization workflow List the different Balanced Optimization options. Push stage processing to a data source Push stage processing to a data target Optimize a job accessing Hadoop HDFS file system Understand the limitations of Balanced Optimizations Additional course details: Nexus Humans KM404 IBM InfoSphere Advanced DataStage - Parallel Framework (v11.5) 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 KM404 IBM InfoSphere Advanced DataStage - Parallel Framework (v11.5) 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 Python-experienced attendees who wish to be equipped with the skills you need to use pandas to ensure the veracity of your data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. Overview Working in a hands-on learning environment, guided by our expert team, attendees will learn to: Understand how data analysts and scientists gather and analyze data Perform data analysis and data wrangling using Python Combine, group, and aggregate data from multiple sources Create data visualizations with pandas, matplotlib, and seaborn Apply machine learning (ML) algorithms to identify patterns and make predictions Use Python data science libraries to analyze real-world datasets Use pandas to solve common data representation and analysis problems Build Python scripts, modules, and packages for reusable analysis code Perform efficient data analysis and manipulation tasks using pandas Apply pandas to different real-world domains with the help of step-by-step demonstrations Get accustomed to using pandas as an effective data exploration tool. Data analysis has become a necessary skill in a variety of domains where knowing how to work with data and extract insights can generate significant value. Geared for data team members with incoming Python scripting experience, Hands-On Data Analysis with Pandas will show you how to analyze your data, get started with machine learning, and work effectively with Python libraries often used for data science, such as pandas, NumPy, matplotlib, seaborn, and scikit-learn. Using real-world datasets, you will learn how to use the powerful pandas library to perform data wrangling to reshape, clean, and aggregate your data. Then, you will be able to conduct exploratory data analysis by calculating summary statistics and visualizing the data to find patterns. In the concluding lessons, you will explore some applications of anomaly detection, regression, clustering, and classification using scikit-learn to make predictions based on past data. Students will leave the course armed with the skills required to use pandas to ensure the veracity of their data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. Introduction to Data Analysis Fundamentals of data analysis Statistical foundations Setting up a virtual environment Working with Pandas DataFrames Pandas data structures Bringing data into a pandas DataFrame Inspecting a DataFrame object Grabbing subsets of the data Adding and removing data Data Wrangling with Pandas What is data wrangling? Collecting temperature data Cleaning up the data Restructuring the data Handling duplicate, missing, or invalid data Aggregating Pandas DataFrames Database-style operations on DataFrames DataFrame operations Aggregations with pandas and numpy Time series Visualizing Data with Pandas and Matplotlib An introduction to matplotlib Plotting with pandas The pandas.plotting subpackage Plotting with Seaborn and Customization Techniques Utilizing seaborn for advanced plotting Formatting Customizing visualizations Financial Analysis - Bitcoin and the Stock Market Building a Python package Data extraction with pandas Exploratory data analysis Technical analysis of financial instruments Modeling performance Rule-Based Anomaly Detection Simulating login attempts Exploratory data analysis Rule-based anomaly detection Getting Started with Machine Learning in Python Learning the lingo Exploratory data analysis Preprocessing data Clustering Regression Classification Making Better Predictions - Optimizing Models Hyperparameter tuning with grid search Feature engineering Ensemble methods Inspecting classification prediction confidence Addressing class imbalance Regularization Machine Learning Anomaly Detection Exploring the data Unsupervised methods Supervised methods Online learning The Road Ahead Data resources Practicing working with data Python practice

Duration 3 Days 18 CPD hours This course is intended for Experienced system administrators or network administrators, Network professionals who have experience working with VMware NSX Advanced Load Balancer and are responsible for designing or deploying Application Delivery Controllers solutions Overview By the end of the course, you should be able to meet the following objectives: Describe the NSX Advanced Load Balancer components and main functions Describe NSX Advanced Load Balancer Global Server Load Balancing architecture Explain NSX Advanced Load Balancer key features and benefits Understand and apply a Global Server Load Balancing design framework Deploy and configure NSX Advanced Load Balancer Global Server Load Balancing infrastructure Explain and Configure Global Server Load Balancing Application components such as Global Server Load Balancing Service, Global Server Load Balancing Pools and Health Monitors with related components Gather relevant information and perform basic troubleshooting of Global Server Load Balancing applications leveraging built-in NSX Advanced Load Balancer tooling Describe and Configure NSX Advanced Load Balancer application and infrastructure monitoring This 3-day course prepares you to lead VMware NSX Advanced Load Balancer (Avi Networks) Global Server Load Balancing design and deployment projects by providing an understanding of general design processes, frameworks and configurations. You look at the design and deployment considerations for Global Server Load Balancing as part of an overall software-defined data center design. This course covers key NSX Advanced Load Balancer (Avi Networks) Global Server Load Balancing features and functionalities offered in the NSX Advanced Load Balancer 18.2 release. Access to a software-defined data center environment is provided through hands-on labs to reinforce the skills and concepts presented in the course. Course Introduction Introductions and course logistics Course objectives Introduction to NSX Advanced Load Balancer Introduce NSX Advanced Load Balancer Discuss NSX Advanced Load Balancer use cases and benefits Explain NSX Advanced Load Balancer architecture and components Explain the management, control, data, and consumption planes and functions Virtual Services Configuration Concepts Explain Virtual Service components Explain Virtual Service types Explain and configure basic virtual services components such as Application Profiles, Network Profiles, Pools and Health Monitors DNS Foundations Review, discuss and explain DNS fundamentals Describe NSX Advanced Load Balancer DNS and IPAM providers Global Server Load Balancing Introduce Global Server Load Balancing concepts and benefits Explain and configure NSX Advanced Load Balancer infrastructure Explain and configure DNS Virtual Service components Explain and configure GSLB Service Engine Group Describe and configure GSLB Sites Explain and configure basic GSLB Services, to include pools and health monitors Describe GSLB Service Load Balancing algorithms Explain and configure Data and Control Plane-based Health Monitors Describe GSLB Health Monitor Proxy Global Server Load Balancing Advanced Topics Explain and configure advanced GSLB service properties such as different type of pool members, Host Header and TLS SNI extensions handling within GSLB Health Monitors Describe EDNS Client Subnet Describe Geo-aware Global Server Load Balancing Design and configure Geo-aware Global Server Load Balancing Describe and leverage DNS Policies to customize client experience Explain and configure Topology-aware Global Server Load Balancing Explain and configure GSLB 3rd party sites Describe GSLB Health Monitor sharding Describe GSLB Service Engine sizing implications Troubleshooting NSX Advanced Load Balancer GSLB Solution Introduce Infrastructure and Application troubleshooting Concepts Describe Control Plane and Data Plane-based troubleshooting Describe GSLB Infrastructure troubleshooting Describe GSLB Services troubleshooting Explain Health Monitors troubleshooting Describe Geo-aware and Topology-based GSLB Services troubleshooting Explain Application Analytics and Logs Describe Client Logs analysis Leverage CLI for advanced data plane troubleshooting Monitoring NSX Advanced Load Balancer Solution Describe NSX Advanced Load Balancer Events Describe and configure NSX Advanced Load Balancer Alerts Describe NSX Advanced Load Balancer monitoring capabilities leveraging SNMP, Syslog and Email