612 Cloud courses in Cardiff delivered Live Online

Duration 4 Days 24 CPD hours This course is intended for The workshop is designed for data scientists who currently use Python or R to work with smaller datasets on a single machine and who need to scale up their analyses and machine learning models to large datasets on distributed clusters. Data engineers and developers with some knowledge of data science and machine learning may also find this workshop useful. Overview Overview of data science and machine learning at scale Overview of the Hadoop ecosystem Working with HDFS data and Hive tables using Hue Introduction to Cloudera Data Science Workbench Overview of Apache Spark 2 Reading and writing data Inspecting data quality Cleansing and transforming data Summarizing and grouping data Combining, splitting, and reshaping data Exploring data Configuring, monitoring, and troubleshooting Spark applications Overview of machine learning in Spark MLlib Extracting, transforming, and selecting features Building and evaluating regression models Building and evaluating classification models Building and evaluating clustering models Cross-validating models and tuning hyperparameters Building machine learning pipelines Deploying machine learning models Spark, Spark SQL, and Spark MLlib PySpark and sparklyr Cloudera Data Science Workbench (CDSW) Hue This workshop covers data science and machine learning workflows at scale using Apache Spark 2 and other key components of the Hadoop ecosystem. The workshop emphasizes the use of data science and machine learning methods to address real-world business challenges. Using scenarios and datasets from a fictional technology company, students discover insights to support critical business decisions and develop data products to transform the business. The material is presented through a sequence of brief lectures, interactive demonstrations, extensive hands-on exercises, and discussions. The Apache Spark demonstrations and exercises are conducted in Python (with PySpark) and R (with sparklyr) using the Cloudera Data Science Workbench (CDSW) environment. The workshop is designed for data scientists who currently use Python or R to work with smaller datasets on a single machine and who need to scale up their analyses and machine learning models to large datasets on distributed clusters. Data engineers and developers with some knowledge of data science and machine learning may also find this workshop useful. Overview of data science and machine learning at scaleOverview of the Hadoop ecosystemWorking with HDFS data and Hive tables using HueIntroduction to Cloudera Data Science WorkbenchOverview of Apache Spark 2Reading and writing dataInspecting data qualityCleansing and transforming dataSummarizing and grouping dataCombining, splitting, and reshaping dataExploring dataConfiguring, monitoring, and troubleshooting Spark applicationsOverview of machine learning in Spark MLlibExtracting, transforming, and selecting featuresBuilding and evauating regression modelsBuilding and evaluating classification modelsBuilding and evaluating clustering modelsCross-validating models and tuning hyperparametersBuilding machine learning pipelinesDeploying machine learning models Additional course details: Nexus Humans Cloudera Data Scientist Training 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 Cloudera Data Scientist Training 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 4 Days 24 CPD hours This course is intended for This course is designed for data analysts, business intelligence specialists, developers, system architects, and database administrators. Overview Skills gained in this training include:The features that Pig, Hive, and Impala offer for data acquisition, storage, and analysisThe fundamentals of Apache Hadoop and data ETL (extract, transform, load), ingestion, and processing with HadoopHow Pig, Hive, and Impala improve productivity for typical analysis tasksJoining diverse datasets to gain valuable business insightPerforming real-time, complex queries on datasets Cloudera University?s four-day data analyst training course focusing on Apache Pig and Hive and Cloudera Impala will teach you to apply traditional data analytics and business intelligence skills to big data. Hadoop Fundamentals The Motivation for Hadoop Hadoop Overview Data Storage: HDFS Distributed Data Processing: YARN, MapReduce, and Spark Data Processing and Analysis: Pig, Hive, and Impala Data Integration: Sqoop Other Hadoop Data Tools Exercise Scenarios Explanation Introduction to Pig What Is Pig? Pig?s Features Pig Use Cases Interacting with Pig Basic Data Analysis with Pig Pig Latin Syntax Loading Data Simple Data Types Field Definitions Data Output Viewing the Schema Filtering and Sorting Data Commonly-Used Functions Processing Complex Data with Pig Storage Formats Complex/Nested Data Types Grouping Built-In Functions for Complex Data Iterating Grouped Data Multi-Dataset Operations with Pig Techniques for Combining Data Sets Joining Data Sets in Pig Set Operations Splitting Data Sets Pig Troubleshoot & Optimization Troubleshooting Pig Logging Using Hadoop?s Web UI Data Sampling and Debugging Performance Overview Understanding the Execution Plan Tips for Improving the Performance of Your Pig Jobs Introduction to Hive & Impala What Is Hive? What Is Impala? Schema and Data Storage Comparing Hive to Traditional Databases Hive Use Cases Querying with Hive & Impala Databases and Tables Basic Hive and Impala Query Language Syntax Data Types Differences Between Hive and Impala Query Syntax Using Hue to Execute Queries Using the Impala Shell Data Management Data Storage Creating Databases and Tables Loading Data Altering Databases and Tables Simplifying Queries with Views Storing Query Results Data Storage & Performance Partitioning Tables Choosing a File Format Managing Metadata Controlling Access to Data Relational Data Analysis with Hive & Impala Joining Datasets Common Built-In Functions Aggregation and Windowing Working with Impala How Impala Executes Queries Extending Impala with User-Defined Functions Improving Impala Performance Analyzing Text and Complex Data with Hive Complex Values in Hive Using Regular Expressions in Hive Sentiment Analysis and N-Grams Conclusion Hive Optimization Understanding Query Performance Controlling Job Execution Plan Bucketing Indexing Data Extending Hive SerDes Data Transformation with Custom Scripts User-Defined Functions Parameterized Queries Choosing the Best Tool for the Job Comparing MapReduce, Pig, Hive, Impala, and Relational Databases Which to Choose?

Duration 4 Days 24 CPD hours This course is intended for This course is appropriate for developers and administrators who intend to use HBase. Overview Skills learned on the course include:The use cases and usage occasions for HBase, Hadoop, and RDBMSUsing the HBase shell to directly manipulate HBase tablesDesigning optimal HBase schemas for efficient data storage and recoveryHow to connect to HBase using the Java API, configure the HBase cluster, and administer an HBase clusterBest practices for identifying and resolving performance bottlenecks Cloudera University?s four-day training course for Apache HBase enables participants to store and access massive quantities of multi-structured data and perform hundreds of thousands of operations per second. Introduction to Hadoop & HBase What Is Big Data? Introducing Hadoop Hadoop Components What Is HBase? Why Use HBase? Strengths of HBase HBase in Production Weaknesses of HBase HBase Tables HBase Concepts HBase Table Fundamentals Thinking About Table Design The HBase Shell Creating Tables with the HBase Shell Working with Tables Working with Table Data HBase Architecture Fundamentals HBase Regions HBase Cluster Architecture HBase and HDFS Data Locality HBase Schema Design General Design Considerations Application-Centric Design Designing HBase Row Keys Other HBase Table Features Basic Data Access with the HBase API Options to Access HBase Data Creating and Deleting HBase Tables Retrieving Data with Get Retrieving Data with Scan Inserting and Updating Data Deleting Data More Advanced HBase API Features Filtering Scans Best Practices HBase Coprocessors HBase on the Cluster How HBase Uses HDFS Compactions and Splits HBase Reads & Writes How HBase Writes Data How HBase Reads Data Block Caches for Reading HBase Performance Tuning Column Family Considerations Schema Design Considerations Configuring for Caching Dealing with Time Series and Sequential Data Pre-Splitting Regions HBase Administration and Cluster Management HBase Daemons ZooKeeper Considerations HBase High Availability Using the HBase Balancer Fixing Tables with hbck HBase Security HBase Replication & Backup HBase Replication HBase Backup MapReduce and HBase Clusters Using Hive & Impala with HBase Using Hive and Impala with HBase Appendix A: Accessing Data with Python and Thrift Thrift Usage Working with Tables Getting and Putting Data Scanning Data Deleting Data Counters Filters Appendix B: OpenTSDB

Duration 4 Days 24 CPD hours This course is intended for This course is best suited to developers, engineers, and architects who want to use use Hadoop and related tools to solve real-world problems. Overview Skills learned in this course include:Creating a data set with Kite SDKDeveloping custom Flume components for data ingestionManaging a multi-stage workflow with OozieAnalyzing data with CrunchWriting user-defined functions for Hive and ImpalaWriting user-defined functions for Hive and ImpalaIndexing data with Cloudera Search Cloudera University?s four-day course for designing and building Big Data applications prepares you to analyze and solve real-world problems using Apache Hadoop and associated tools in the enterprise data hub (EDH). IntroductionApplication Architecture Scenario Explanation Understanding the Development Environment Identifying and Collecting Input Data Selecting Tools for Data Processing and Analysis Presenting Results to the Use Defining & Using Datasets Metadata Management What is Apache Avro? Avro Schemas Avro Schema Evolution Selecting a File Format Performance Considerations Using the Kite SDK Data Module What is the Kite SDK? Fundamental Data Module Concepts Creating New Data Sets Using the Kite SDK Loading, Accessing, and Deleting a Data Set Importing Relational Data with Apache Sqoop What is Apache Sqoop? Basic Imports Limiting Results Improving Sqoop?s Performance Sqoop 2 Capturing Data with Apache Flume What is Apache Flume? Basic Flume Architecture Flume Sources Flume Sinks Flume Configuration Logging Application Events to Hadoop Developing Custom Flume Components Flume Data Flow and Common Extension Points Custom Flume Sources Developing a Flume Pollable Source Developing a Flume Event-Driven Source Custom Flume Interceptors Developing a Header-Modifying Flume Interceptor Developing a Filtering Flume Interceptor Writing Avro Objects with a Custom Flume Interceptor Managing Workflows with Apache Oozie The Need for Workflow Management What is Apache Oozie? Defining an Oozie Workflow Validation, Packaging, and Deployment Running and Tracking Workflows Using the CLI Hue UI for Oozie Processing Data Pipelines with Apache Crunch What is Apache Crunch? Understanding the Crunch Pipeline Comparing Crunch to Java MapReduce Working with Crunch Projects Reading and Writing Data in Crunch Data Collection API Functions Utility Classes in the Crunch API Working with Tables in Apache Hive What is Apache Hive? Accessing Hive Basic Query Syntax Creating and Populating Hive Tables How Hive Reads Data Using the RegexSerDe in Hive Developing User-Defined Functions What are User-Defined Functions? Implementing a User-Defined Function Deploying Custom Libraries in Hive Registering a User-Defined Function in Hive Executing Interactive Queries with Impala What is Impala? Comparing Hive to Impala Running Queries in Impala Support for User-Defined Functions Data and Metadata Management Understanding Cloudera Search What is Cloudera Search? Search Architecture Supported Document Formats Indexing Data with Cloudera Search Collection and Schema Management Morphlines Indexing Data in Batch Mode Indexing Data in Near Real Time Presenting Results to Users Solr Query Syntax Building a Search UI with Hue Accessing Impala through JDBC Powering a Custom Web Application with Impala and Search

Duration 5 Days 30 CPD hours The iPhone combines technologies of smartphones and personal computing. With a multitouch screen, built-in accelerometer and virtual keyboard, the iPhone also requires the mobile application developer to adopt a vastly different software design philosophy. With over a billion mobile apps sold, iPhone Programming is a critical part of the future of mobile technology. This five day course teaches the attendee all aspects of iOS mobile app development Introduction and Setup Joining the Apple iOS Developer Program Installing Xcode and the iOS SDK A Guided Tour of Xcode An Introduction to Xcode Playgrounds Swift Programming Language Swift Data Types, Constants, and Variables Swift Operators and Expressions Swift Flow Control The Swift Switch Statement Overview of Swift Functions The Basics of Object Oriented Programming in Swift Swift Subclassing and Extensions Arrays and Dictionary Collections in Swift Understanding Error Handling in Swift Views, Layouts, and Storyboards Creating an Interactive iOS App Auto Layout in iOS Working with iOS Auto Layout Constraints in Interface Builder Implementing iOS Auto Layout Constraints in Code Implementing Cross-Hierarchy Auto Layout Constraints in iOS Understanding the iOS Auto Layout Visual Format Language Using Size Classes to Design Adaptable Universal iOS User Interfaces Using Storyboards in Xcode Organizing Scenes over Multiple Xcode Storyboard Files Using Xcode Storyboards to Create an iOS Tab Bar Application Working with the iOS Stack View Class iOS Stack View Tutorial iOS Split View Master-Detail Example Multitasking in iOS Implementing a Page based iOS Application using UIPageViewController iOS UIPageViewController Application Data Storage with Files, iCloud, and Databases Working with Directories in Swift on iOS Working with Files in Swift on iOS iOS Directory Handling and File I/O in Swift Preparing an iOS App to use iCloud Storage Managing Files using the iOS UIDocument Class Using iCloud Storage in an iOS Application Synchronizing iOS Key-Value Data using iCloud iOS Database Implementation using SQLite SQLite based iOS Application using Swift and FMDB Working with iOS Databases using Core Data iOS Core Data Introduction to CloudKit Data Storage on iOS iOS CloudKit Example iOS CloudKit Subscription Example Touch, Taps, and Gestures An Overview of iOS Multitouch, Taps and Gestures iOS Touch, Multitouch and Tap Application Detecting iOS Touch Screen Gesture Motions Identifying Gestures using iOS Gesture Recognizers iOS Gesture Recognition iOS 3D Touch Force Handling iOS 3D Touch Quick Actions iOS 3D Touch Peek and Pop Advanced View Options Basic iOS Animation using Core Animation iOS UIKit Dynamics ? An Overview Introduction to iOS Sprite Kit Programming iOS Sprite Kit Level Editor Game iOS Sprite Kit Collision Handling Extensions Introduction to Extensions in iOS iOS Today Extension Widget Creating an iOS Photo Editing Extension Creating an iOS Action Extension Receiving Data from an iOS Action Extension Multimedia, Facebook, and Twitter Accessing the iOS Camera and Photo Library iOS Camera Application iOS Video Playback using AVPlayer and AVPlayerViewController iOS Multitasking Picture in Picture Tutorial Playing Audio on iOS using AVAudioPlayer Recording Audio on iOS with AVAudioRecorder The App Store Preparing and Submitting an iOS Application to the App Store Additional course details: Nexus Humans iPhone Mobile App Development 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 iPhone Mobile App Development 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 4 Days 24 CPD hours Overview By the end of the course, you should be able to meet the following objectives: Describe how Tanzu Kubernetes Grid fits in the VMware Tanzu portfolio Describe the Tanzu Kubernetes Grid architecture Deploy and manage Tanzu Kubernetes Grid management and supervisor clusters Deploy and manage Tanzu Kubernetes Grid workload clusters Deploy, configure, and manage Tanzu Kubernetes Grid packages Perform basic troubleshooting During this four-day course, you focus on installing VMware Tanzu© Kubernetes Grid? in a VMware vSphere© environment and provisioning and managing Tanzu Kubernetes Grid clusters. The course covers how to install Tanzu Kubernetes Grid packages for image registry, authentication, logging, ingress, multipod network interfaces, service discovery, and monitoring. The concepts learned in this course are transferable for users who must install Tanzu Kubernetes Grid on other supported clouds. Course Introduction Introductions and course logistics Course objectives Introducing VMware Tanzu Kubernetes Grid Identify the VMware Tanzu products responsible for Kubernetes life cycle management and describe the main differences between them Explain the core concepts of Tanzu Kubernetes Grid, including bootstrap, Tanzu Kubernetes Grid management, supervisor, and workload clusters List the components of a Tanzu Kubernetes Grid instance VMware Tanzu Kubernetes Grid CLI and API Illustrate how to use the Tanzu CLI Define the Carvel Tool set Define Cluster API Identify the infrastructure providers List the Cluster API controllers Identify the Cluster API custom resource definitions Authentication Explain how Kubernetes manages authentication with Management clusters Explain how Kubernetes manages authentication with supervisor clusters Define Pinniped Define Dex Describe the Pinniped authentication workflow Load Balancers Illustrate how load balancing works for the Kubernetes control plane Illustrate how load balancing works for application workload Explain how Tanzu Kubernetes Grid integrates with VMware NSX Advanced Load Balancer List load balancing options available on public clouds VMware Tanzu Kubernetes Grid on vSphere List the requirements for deploying a supervisor cluster List the steps to install a Tanzu Kubernetes Grid supervisor cluster Summarize the events of a supervisor cluster creation List the requirements for deploying a management cluster List the steps to install a Tanzu Kubernetes Grid management cluster Summarize the events of a management cluster creation Demonstrate how to use commands when working with management clusters VMware Tanzu Kubernetes Grid on Public Clouds List the requirements for deploying a management cluster on AWS and Microsoft Azure List the configuration options to install a Tanzu Kubernetes Grid a management cluster on AWS and Azure Tanzu Kubernetes Workload Clusters List the steps to build a custom image Describe the available customizations Identify the options for deploying Tanzu Kubernetes Grid clusters Explain the difference between the v1alpha3 and v1beta1 APIs Explain how Tanzu Kubernetes Grid clusters are created Discuss which VMs compose a Tanzu Kubernetes Grid cluster List the pods that run on a Tanzu Kubernetes Grid cluster Describe the Tanzu Kubernetes Grid core add-ons that are installed on a cluster Tanzu Kubernetes Grid Packages Define the Tanzu Kubernetes Grid packages Explain the difference between Auto-Managed and CLI-Managed packages Define packages repositories Configuring and Managing Tanzu Kubernetes Grid Operation and Analytics Packages Describe Cert-Manager Describe the Harbor Image Registry Describe Fluent Bit Identify the logs that Fluent Bit collects Explain basic Fluent Bit configuration Describe Prometheus and Grafana Configuring and Managing Tanzu Kubernetes Grid Networking Packages Describe the Contour ingress controller Demonstrate how to install Contour on a Tanzu Kubernetes Grid cluster Describe ExternalDNS Demonstrate how to install Service Discovery with ExternalDNS Describe Multus CNI Tanzu Kubernetes Grid Day 2 Operations List the load balancer configuration options in vSphere to load balance applications Demonstrate how to configure Ingress with the NodePortLocal Mode Explain how to install VMware Tanzu Application Platform Describe life cycle management in Tanzu Kubernetes Grid Explain how backup and restore are implemented in Tanzu Kubernetes Grid Describe Velero and Restic List the steps to back up a Workload cluster using Velero and Restic Troubleshooting Tanzu Kubernetes Grid Discuss the various Tanzu Kubernetes Grid logs Identify the location of Tanzu Kubernetes Grid logs Explain the purpose of crash diagnostics Demonstrate how to check the health of a Tanzu Kubernetes Grid cluster Explain packages cleanup procedures Explain management recovery procedures Additional course details:Notes Delivery by TDSynex, Exit Certified and New Horizons an VMware Authorised Training Centre (VATC) Nexus Humans VMware Tanzu Kubernetes Grid: Install, Configure, Manage [V2.0] training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the VMware Tanzu Kubernetes Grid: Install, Configure, Manage [V2.0] course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 2 Days 12 CPD hours This course is intended for Application consultants, Business Analysts, Executives, Technology Consultants, Users Overview By the end of this course, students will be able to:Explain SAP LumiraCreate documents and acquire dataPrepare datasetsVisualize dataShare stories In this course, students will learn how to create stunning and interactive visualizations by choosing a rich library of visualization types, ranging from scatter plots, heat and geo maps to tag clouds, box plots and network charts. Course Outline Positioning and Overview of SAP Lumira Discovery Navigating the BI Launchpad Acquiring Data Enrich the Dataset Create Visualizations Create a Story Sharing Options Using the Lumira Discovery Formula Editor Additional Data Sources Data Mashups

Duration 2 Days 12 CPD hours This course is intended for Application developers who want to increase their understanding of Spring and Spring Boot and a focus on fundamentals. Overview By the end of the course, you should be able to meet the following objectives: Describe the benefits provided by Spring Boot Initialize a project using Spring Boot Starters Leverage Spring Boot's auto configuration features Create simplified backing-store solutions using Spring Data JPA Build a simple MVC application using Spring Boot, embedded Web Server and fat JARs or classic WARs Build a RESTful Web application Use Spring Security to secure Web and REST endpoints Enable and extend metrics and monitoring capabilities using Spring Boot actuator Leverage advance configuration capabilities Utilize Spring Boot enhancements to testing This course offers experience with Spring Boot and its major features, including auto-configuration, Actuator, Spring Boot testing framework and more. On completion, participants will have a foundation for creating enterprise and cloudready applications. Please note that this course is a subset of the material in our 4-day Spring: Core Training course - there is no need to take both courses. This course is recommended if you have a good working knowledge of Spring Basics (see Prerequisites) but are new to Spring Boot. Introduction to Spring Essentials Why Spring Configuration using Spring Bean creation Data Management Spring Boot Introduction Introduction to Spring Boot Features Value Proposition of Spring Boot Creating a simple Boot application using Spring Initializer website Spring Boot Dependencies, Auto-configuration, and Runtime Dependency management using Spring Boot starters How auto-configuration works Configuration properties Overriding auto-configuration Using CommandLineRunner JPA with Spring and Spring Data Quick introduction to ORM with JPA Benefits of using Spring with JPA JPA configuration in Spring Configuring Spring JPA using Spring Boot Spring Data JPA dynamic repositories Spring MVC Architecture and Overview Introduction to Spring MVC and request processing Controller method signatures Using @Controller, @RestController and @GetMapping annotations Configuring Spring MVC with Spring Boot Spring Boot packaging options, JAR or WAR Rest with Spring MVC An introduction to the REST architectural style Controlling HTTP response codes with @ResponseStatus Implementing REST with Spring MVC, @RequestMapping, @RequestBody and @ResponseBody Spring MVC?s HttpMessageConverters and automatic content negotiation Spring Security What problems does Spring Security solve? Configuring authentication Implementing authorization by intercepting URLs Authorization at the Java method level Understanding the Spring Security filter chain Spring security testing Actuators, Metrics and Health Indicators Exposing Spring Boot Actuator endpoints Custom Metrics Health Indicators Creating custom Health Indicators External monitoring systems Spring Boot Testing Enhancements Spring Boot testing overview Integration testing using @SpringBootTest Web slice testing with MockMvc framework Slices to test different layers of the application

Duration 1 Days 6 CPD hours This course is intended for This course is intended for: Developers System Administrators Solutions Architects Overview This course is designed to teach you how to: Design a microservices-based architecture that uses containers Use Amazon ECS to run and scale a microservices-based application Integrate Amazon ECS with other AWS services Running Container-Enabled Microservices on AWS is designed to teach you how to manage and scale container-enabled applications by using Amazon Elastic Container Service (ECS). This course highlights the challenges of running containerized applications at scale and provides guidance on creating and using Amazon ECS to develop and deploy containerized microservices-based applications. In the hands-on lab exercises you will use Amazon ECS to handle long-running services, build and deploy container images, link services together, and scale capacity to meet demand. You will also learn how to run container workers for asynchronous application processes. Module 1a: Overview of Microservices on AWS Welcome to Simple Mustache Service! The monolith What are microservices? How to implement a microservices infrastructure The six principles of microservices Module 1b: Containers and Docker Introduction to containers Comparing virtual machines with containers Docker Running containers Storing container images Hands-on lab: Building and running your first container Module 2: Continuous delivery for container-based microservices Compare and contrast different software development cycles Use AWS CodePipeline to code, build, and deploy a microservice Use AWS CodeCommit as a source control service Use Jenkins to perform a Docker build Use Postman to run and test microservices Use AWS CloudFormation to provision and deploy microservices Hands-on lab: Using the Amazon ECS Service Scheduler Module 3: High availability and scaling with Amazon Elastic Container Service High availability Cluster management and scheduling Monitoring Scaling a cluster Scaling services Hands-on lab: Continuous delivery pipelines for container-based microservices Module 4: Security for container-based microservices Implement security Apply best practices Automate security Evaluate compliance requirements Embed security into the CI/CD Hands-on lab: Extending Amazon ECS with Service Discovery and Config Management Additional course details: Nexus Humans Running Container Enabled Microservices 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 Running Container Enabled Microservices 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 3 Days 18 CPD hours This course is intended for Platform operators who are responsible for deploying and managing Tanzu Kubernetes clusters Overview By the end of the course, you should be able to meet the following objectives: Describe how Tanzu Kubernetes Grid fits in the VMware TanzuTM portfolio Describe the Tanzu Kubernetes Grid architecture Deploy and manage Tanzu Kubernetes Grid management clusters Deploy and manage Tanzu Kubernetes Grid workload clusters Deploy, configure, and manage Tanzu Kubernetes Grid packages Perform basic troubleshooting During this three-day course, you focus on installing VMware Tanzu© Kubernetes Grid? on a VMware vSphere© environment and then provisioning and managing Tanzu Kubernetes Grid clusters. The course covers how to install Tanzu Kubernetes Grid packages for image registry, authentication, logging, ingress, multi-pod network interfaces, service discovery, and monitoring. The concepts learned in this course are transferable for users who must install Tanzu Kubernetes Grid on other supported clouds. Course Introduction Introductions and course logistics Course objectives Introducing VMware Tanzu Kubernetes Grid Identify the VMware Tanzu products responsible for Kubernetes life cycle management and describe the main differences between them Explain the core concepts of Tanzu Kubernetes Grid, including bootstrap, Tanzu Kubernetes Grid management and workload clusters, and the role of Cluster API List the components of a Tanzu Kubernetes Grid instance Illustrate how to use the Tanzu CLI Identify the requirements for a bootstrap machine Define the Carvel Tool set Define Cluster API Identify the infrastructure providers List the Cluster API controllers Identify the Cluster API Custom Resource Definitions Management Clusters List the requirements for deploying a management cluster Differentiate between deploying on vSphere 6.7 Update 3 and vSphere 7 Describe the components of NSX Advanced Load Balancer Explain how Tanzu Kubernetes Grid integrates with NSX Advanced Load Balancer Explain how Kubernetes manages authentication Define Pinniped Define Dex Describe the Pinniped authentication workflow List the steps to install a Tanzu Kubernetes Grid management cluster Summarize the events of a management cluster creation Demonstrate how to use commands when working with management clusters Tanzu Kubernetes Clusters List the steps to build a custom image Describe the available customizations Identify the options for deploying Tanzu Kubernetes Grid clusters Explain how Tanzu Kubernetes Grid clusters are created Discuss which VMs make up a Tanzu Kubernetes Grid cluster List the pods that run on a Tanzu Kubernetes cluster Describe the Tanzu Kubernetes Grid core add-ons that are installed on a cluster Configuring and Managing Tanzu Kubernetes Grid Instances Define the Tanzu Kubernetes Grid packages Describe the Harbor Image Registry Define Fluent Bit Identify the logs that Fluent Bit collects Explain basic Fluent Bit configuration Describe the Contour ingress controller Demonstrate how to install Contour on a Tanzu Kubernetes Grid cluster Demonstrate how to install Service Discovery with ExternalDNS. Define Multus CNI Define Prometheus Define Grafana Troubleshooting Discuss the various Tanzu Kubernetes Grid logs Identify the location of Tanzu Kubernetes Grid logs Explain the purpose of crash diagnostics Demonstrate how to use SSH to connect to a Tanzu Kubernetes Grid VM Describe the steps for troubleshooting a failed cluster deployment Additional course details:Notes Delivery by TDSynex, Exit Certified and New Horizons an VMware Authorised Training Centre (VATC) Nexus Humans VMware Tanzu Kubernetes Grid: Install, Configure, Manage [V1.5] 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 VMware Tanzu Kubernetes Grid: Install, Configure, Manage [V1.5] 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.