7106 Acro courses

Duration 3 Days 18 CPD hours This course is intended for The target audience for the SRE Practitioner course are professionals including: Anyone focused on large-scale service scalability and reliability Anyone interested in modern IT leadership and organizational change approaches Business Managers Business Stakeholders Change Agents Consultants DevOps Practitioners IT Directors IT Managers IT Team Leaders Product Owners Scrum Masters Software Engineers Site Reliability Engineers System Integrators Tool Providers Overview After completing this course, students will have learned: Practical view of how to successfully implement a flourishing SRE culture in your organization. The underlying principles of SRE and an understanding of what it is not in terms of anti-patterns, and how you become aware of them to avoid them. The organizational impact of introducing SRE. Acing the art of SLIs and SLOs in a distributed ecosystem and extending the usage of Error Budgets beyond the normal to innovate and avoid risks. Building security and resilience by design in a distributed, zero-trust environment. How do you implement full stack observability, distributed tracing and bring about an Observability-driven development culture? Curating data using AI to move from reactive to proactive and predictive incident management. Also, how you use DataOps to build clean data lineage. Why is Platform Engineering so important in building consistency and predictability of SRE culture? Implementing practical Chaos Engineering. Major incident response responsibilities for a SRE based on incident command framework, and examples of anatomy of unmanaged incidents. Perspective of why SRE can be considered as the purest implementation of DevOps SRE Execution model Understanding the SRE role and understanding why reliability is everyone's problem. SRE success story learnings This course introduces a range of practices for advancing service reliability engineering through a mixture of automation, organizational ways of working and business alignment. Tailored for those focused on large-scale service scalability and reliability. SRE Anti-patterns Rebranding Ops or DevOps or Dev as SRE Users notice an issue before you do Measuring until my Edge False positives are worse than no alerts Configuration management trap for snowflakes The Dogpile: Mob incident response Point fixing Production Readiness Gatekeeper Fail-Safe really? SLO is a Proxy for Customer Happiness Define SLIs that meaningfully measure the reliability of a service from a user?s perspective Defining System boundaries in a distributed ecosystem for defining correct SLIs Use error budgets to help your team have better discussions and make better data-driven decisions Overall, Reliability is only as good as the weakest link on your service graph Error thresholds when 3rd party services are used Building Secure and Reliable Systems SRE and their role in Building Secure and Reliable systems Design for Changing Architecture Fault tolerant Design Design for Security Design for Resiliency Design for Scalability Design for Performance Design for Reliability Ensuring Data Security and Privacy Full-Stack Observability Modern Apps are Complex & Unpredictable Slow is the new down Pillars of Observability Implementing Synthetic and End user monitoring Observability driven development Distributed Tracing What happens to Monitoring? Instrumenting using Libraries an Agents Platform Engineering and AIOPs Taking a Platform Centric View solves Organizational scalability challenges such as fragmentation, inconsistency and unpredictability. How do you use AIOps to improve Resiliency How can DataOps help you in the journey A simple recipe to implement AIOps Indicative measurement of AIOps SRE & Incident Response Management SRE Key Responsibilities towards incident response DevOps & SRE and ITIL OODA and SRE Incident Response Closed Loop Remediation and the Advantages Swarming ? Food for Thought AI/ML for better incident management Chaos Engineering Navigating Complexity Chaos Engineering Defined Quick Facts about Chaos Engineering Chaos Monkey Origin Story Who is adopting Chaos Engineering Myths of Chaos Chaos Engineering Experiments GameDay Exercises Security Chaos Engineering Chaos Engineering Resources SRE is the Purest form of DevOps Key Principles of SRE SREs help increase Reliability across the product spectrum Metrics for Success Selection of Target areas SRE Execution Model Culture and Behavioral Skills are key SRE Case study Post-class assignments/exercises Non-abstract Large Scale Design (after Day 1) Engineering Instrumentation- Instrumenting Gremlin (after Day 2)

Duration 2 Days 12 CPD hours This course is intended for vSphere administrators, architects, system engineers, and systems integrators who are responsible for the deployment or management of Site Recovery Manager Overview By the end of the course, you should be able to meet the following objectives: Summarize the components of Site Recovery Manager architecture Deploy and configure the Site Recovery Manager appliance Describe the principal disaster recovery topologies that are used with Site Recovery Manager Configure inventory and resource mappings Describe the storage replication options that are used with Site Recovery Manager Configure Site Recovery Manager to leverage array-based replication Describe VMware vSphere Replication™ functionality Describe the vSphere Replication architecture Deploy and configure vSphere Replication for use with Site Recovery Manager Build Site Recovery Manager protection groups based on vSphere Replication Build, edit, execute, test, and remove a recovery plan Perform a planned migration Perform reprotect and failback using Site Recovery Manager and vSphere Replication This hands-on training course gives experienced VMware vSphere© administrators the knowledge to install, configure, and manage VMware Site Recovery Manager? 8.2. This course also shows you how to write and test disaster recovery plans that use Site Recovery Manager. Course Introduction Outline the necessary information to effectively undertake this course Identify resources for additional information Overview and Architecture Discuss Site Recovery Manager architecture Examine disaster recovery options with Site Recovery Manager Describe Site Recovery Manager integration with VMware vSphere© ClientTM Discuss Site Recovery Manager features Analyze Site Recovery Manager storage policies and integration options Discuss how Site Recovery Manager supports several disaster recovery topologies identify use cases for Site Recovery Manager across various scenarios Describe how VMware Site Recovery? for VMware Cloud? on AWS integrates with Site Recovery Manager. Deploy & Configure Site Recovery Manager Identify the requirements to deploy Site Recovery Manager Discuss the benefits of the Site Recovery Manager appliance Explore vSphere deployment models Deploy the Site Recovery Manager appliance Navigate the Site Recovery Manager configuration user interface Describe the process to register Site Recovery Manager with VMware vCenter Server© Configure site pairing Identify how to perform updates to the Site Recovery Manager appliance Configuring Inventory Mappings Outline the importance of inventory mappings Examine configuration options for inventory mappings Outline the importance of placeholders Using Array-based Replication Describe array-based replication Discuss the role of the Storage Replication Adapter (SRA) Explore the relationship between devices, consistency groups and datastore groups Configure array pairs vSphere Replication Explore vSphere Replication architecture Examine vSphere Replication functionality Formulate use cases for vSphere Replication Deploy a vSphere Replication appliance Configure vSphere Replication appliance settings Configure a vSphere Replication appliance connection Deploy a vSphere Replication server Register a vSphere Replication server Replicating Virtual Machines with vSphere Replication Configure vSphere Replication for virtual machines Explain the importance of datastore mappings Describe vSphere Replication recovery point objective scheduling Describe the vSphere Replication disk transfer protocol Building Protection Groups Define protection group functionality Examine the differences between array-based protection groups, protection groups based on vSphere Replication, and storage profile protection groups Create a protection group Discuss protection group settings Remove protection from a virtual machine Create a storage profile protection group Building Recovery Plans Discuss recovery plan concepts List recovery plan steps Discuss network planning Discuss customization options in recovery planning Outline how to implement a recovery plan Investigate recovery plan options Testing and Running a Recovery Plan Discuss use cases for Site Recovery Manager Describe planned migration Identify Site Recovery Manager workflows Discuss the importance of VMware vSphere© VMFS resignaturing Examine Site Recovery Manager integration with various vSphere technologies Outline how to conduct a recovery plan test Perform recovery plan test execution Identify the effects on the storage layer during recovery steps Explain a recovery plan execution in planned migration or disaster recovery mode Understand storage layer changes for plan execution types Identify the recovery steps for each execution type Describe how to reprotect a data center Examine failback steps Monitoring and Troubleshooting Discuss Site Recovery Manager alarms Explore Site Recovery Manager history reports Configuring advanced Site Recovery Manager settings Describe how to modify logging levels Explain how to collect log bundles Identify key log locations

Duration 3 Days 18 CPD hours This course is intended for This intermediate-level hands-on course is geared for experienced Administrators, Analysts, Architects, Data Scientists, Database Administrators and Implementers Overview This course is approximately 50% hands-on, combining expert lecture, real-world demonstrations and group discussions with machine-based practical labs and exercises. Working in a hands-on learning environment led by our Oracle Certified expert facilitator, students will learn how to: Administer ODI resources and setup security with ODI Apply ODI Topology concepts for data integration Describe ODI Model concepts Describe architecture of Oracle Data Integrator Design ODI Mappings, Procedures, Packages, and Load Plans to perform ELT data transformations Explore, audit data, and enforce data quality with ODI Implement Changed Data Capture with ODI Oracle Data Integrator is a comprehensive data integration platform that covers all data integration requirements from high-volume, high-performance batch loads, to event-driven integration processes and SOA-enabled data services. Oracle Data Integrator's Extract, Load, Transform (E-LT) architecture leverages disparate RDBMS engines to process and transform the data - the approach that optimizes performance, scalability and lowers overall solution costs. Throughout this course participants will explore how to centralize data across databases, performing integration, designing ODI Mappings, and setting up ODI security. In addition, Oracle Data Integrator can interact with the various tools of the Hadoop ecosystem, allowing administrators and data scientists to farm out map-reduce operations from established relational databases to Hadoop. They can also read back into the relational world the results of complex Big Data analysis for further processing. Working in a hands-on learning environment led by our Oracle Certified expert facilitator, students will learn how to: Administer ODI resources and setup security with ODI Apply ODI Topology concepts for data integration Describe ODI Model concepts Describe architecture of Oracle Data Integrator Design ODI Mappings, Procedures, Packages, and Load Plans to perform ELT data transformations Explore, audit data, and enforce data quality with ODI Implement Changed Data Capture with ODI Introduction to Integration and Administration Oracle Data Integrator: Introduction Oracle Data Integrator Repositories Administering ODI Repositories Create and connect to the Master Repository Export and import the Master Repository Create, connect, and set a password to the Work Repository ODI Topology Concepts ODI Topology: Overview Data Servers and Physical Schemas Defining Topology Agents in Topology Planning a Topology Describing the Physical and Logical Architecture Topology Navigator Creating Physical Architecture Creating Logical Architecture Setting Up a New ODI Project ODI Projects Using Folders Understanding Knowledge Modules Exporting and Importing Objects Using Markers Oracle Data Integrator Model Concepts Understanding the Relational Model Understanding Reverse-Engineering Creating Models Organizing ODI Models and Creating ODI Datastores Organizing Models Creating Datastores Constraints in ODI Creating Keys and References Creating Conditions Exploring Your Data Constructing Business Rules ODI Mapping Concepts ODI Mappings Expressions, Join, Filter, Lookup, Sets, and Others Behind the Rules Staging Area and Execution Location Understanding Knowledge Modules Mappings: Overview Designing Mappings Multiple Sources and Joins Filtering Data Overview of the Flow in ODI Mapping Selecting a Staging Area Configuring Expressions Execution Location Selecting a Knowledge Module Mappings: Monitoring and Troubleshooting Monitoring Mappings Working with Errors Designing Mappings: Advanced Topics 1 Working with Business Rules Using Variables Datasets and Sets Using Sequences Designing Mappings: Advanced Topics 2 Partitioning Configuring Reusable Mappings Using User Functions Substitution Methods Modifying Knowledge Modules Using ODI Procedures Procedures: Overview Creating a Blank Procedure Adding Commands Adding Options Running a Procedure Using ODI Packages Packages: Overview Executing a Package Review of Package Steps Model, Submodel, and Datastore Steps Variable Steps Controlling the Execution Path Step-by-Step Debugger Starting a Debug Session New Functions Menu Bar Icons Managing ODI Scenarios Scenarios Managing Scenarios Preparing for Deployment Using Load Plans What are load plans? Load plan editor Load plan step sequence Defining restart behavior Enforcing Data Quality with ODI Data Quality Business Rules for Data Quality Enforcing Data Quality with ODI Working with Changed Data Capture CDC with ODI CDC implementations with ODI CDC implementation techniques Journalizing Results of CDC Advanced ODI Administration Setting Up ODI Security Managing ODI Reports ODI Integration with Java

Duration 4 Days 24 CPD hours This course is intended for This course is geared for experienced skilled Java developers, software developers, data scientists, machine learning experts or others who wish to transtion their coding skills to Scala, learning how to code in Scala and apply it in a practical way. This is not a basic class. Overview Working in a hands-on learning environment led by our expert instructor you'll: Get comfortable with Scala's core principles and unique features, helping you navigate the language confidently and boosting your programming skills. Discover the power of functional programming and learn techniques that will make your code more efficient,maintainable, and enjoyable to write. Become proficient in creating dynamic web applications using the Play Framework, and easily connect to databases with the user-friendly Slick library. Master concurrency programming with Akka, empowering you to build scalable and fault-tolerant applications that excel in performance. Enhance your testing skills using ScalaTest and ScalaCheck, ensuring the reliability and quality of your Scala applications, while having fun in the process. Explore the fascinating world of generative AI and GPT technologies, and learn how to integrate them into your projects,adding a touch of innovation and intelligence to your Scala solutions. If your team requires different topics, additional skills or a custom approach, our team will collaborate with you to adjust the course to focus on your specific learning objectives and goals. Discover the power of Scala programming in our comprehensive, hands-on technical training course designed specifically for experienced object-oriented (OO) developers. Scala is a versatile programming language that combines the best of both OO and functional programming paradigms, making it ideal for a wide range of projects, from web applications to big data processing and machine learning. By mastering Scala, you'll be able to develop more efficient, scalable, and maintainable applications. Fast Track to Scala Programming for OO / Java Developers is a four day hands-on course covers the core principles of Scala, functional programming, web application development, database connectivity, concurrency programming, testing, and interoperability between Scala and Java. Additionally, you'll explore cutting-edge generative AI and GPT technologies, learning how to integrate them into your Scala applications for intelligent suggestions or automation. Throughout the course you?ll explore the latest tools and best practices in the Scala ecosystem, gaining valuable knowledge and experience that can be directly applied to your day-to-day work. With 50% of the course content dedicated to hands-on labs, you'll gain practical experience applying the concepts you've learned across various projects, such as building functional web applications, connecting to databases, designing modular components, and implementing concurrency. Upon completing the course, you'll have a solid understanding of the language and its features, empowering you to confidently apply your new skills in data science and machine learning projects. You'll exit well-prepared to create efficient, scalable, and maintainable Scala applications, regardless of the complexity of your projects. Introduction to Scala Scala features and benefits Comparing Scala with Java and other OO languages Installing Scala and setting up the development environment Object-Oriented Programming in Scala Classes and objects Traits, mixins, and inheritance Companion objects and factories Encapsulation and polymorphism Functional Programming Basics Pure functions and referential transparency Higher-order functions and currying Immutability and persistent data structures Pattern matching and recursion Having Fun with Functional Data Structures Lists, sets, and maps in Scala Folding and reducing operations Stream processing and lazy evaluation For-comprehensions Building Web Applications in Functional Style Introduction to Play Framework Functional web routing and request handling JSON handling with Play-JSON Middleware and functional composition Connecting to a Database Introduction to Slick library Database configuration and setup Querying and updating with Slick Transactions and error handling Building Scalable and Extensible Components Modular architecture and design patterns Dependency injection with MacWire Type classes and type-level programming Implicit parameters and conversions Concurrency Programming & Akka Introduction to Akka framework and Actor model Actor systems and message passing Futures and Promises Supervision and fault tolerance Building Confidence with Testing Introduction to ScalaTest and ScalaCheck Unit testing and property-based testing Test-driven development in Scala Mocking and integration testing Interoperability between Scala and Java Calling Java code from Scala Using Java libraries in Scala projects Converting Java collections to Scala collections Writing Scala code that can be called from Java Using Generative AI and GPT Technologies in Scala Programming Overview of GPT and generative AI Integrating GPT with Scala applications Use cases and practical examples

Duration 4 Days 24 CPD hours This course is intended for This course assumes the student has successfully taken and passed the NCSF Foundation 2.0 course based on the NIST Cybersecurity Framework version 1.1, release April 2018. Following the course introduction, the course provides an introduction to the intersection between digital transformation and cybersecurity, which is followed by an overview of the threat landscape. Following an approach to the implementation of cybersecurity controls, the course delves into an organizational approach to cybersecurity that starts governance, management, and a supportive culture,Finally, the course provides additional guidance for the cybersecurity practitioner to determine the current state, the desired state, and a plan to close the gap - and to do this over and over again to inculcate it into organizational DNA. Overview This course looks at the impact of digital transformation on cybersecurity risks, an understanding of the threat landscape, and an approach to the application of cybersecurity controls. It provides guidance for students on the best approach to design and build a comprehensive cybersecurity program. Executives are keenly aware of the risks but have limited knowledge on the best way to mitigate these risks. This course also enables our executives to answer the critical question - Are we secure? The class includes lectures, informative supplemental reference materials, quizzes, exercises, and formal examination. The exercises are a critical aspect of the course; do not skip them. Outcomes and benefits from this class is a practical approach that students can use to build and maintain comprehensive cybersecurity and cyber-risk management programs. This course is targeted at IT and Cybersecurity professionals looking to become certified on how to operationalize the NIST Cybersecurity Framework (NCSP) across an enterprise and its supply chain. Digital Transformation Explores what the Practitioner needs to know about the relationship between digital transformation and cybersecurity Explain how to determine the impact of cybersecurity on DX. Explain the relationships between culture and digital transformation from the perspective of a practitioner. Explain the delivery of value to stakeholders in a DX & cybersecurity environment. Illustrate the interdependent relationship between cybersecurity and DX. Threat Landscape The Practitioner needs to understand what threat actors do and their capabilities. Compare the evolving attack type impact to the threat environment. Apply knowledge about the threat landscape to maintain a readiness to respond. Develop a risk profile based on business impact analysis Establish the relationship between awareness and training in the continual improvement of cybersecurity posture. Develop and treat training & awareness as a critical aspect of deterrence Use knowledge about the threat landscape as a predicate to the adoption and adaptation of your cybersecurity posture. The Controls This chapter provides a sample set of controls based on an informative reference. Understand the purpose goals & objectives for each control. Characterize & explain the informative reference controls Discover how to apply the controls in an organizational context. Adopt & Adapt Adopt is a decision about governance; adapt is the set of management decisions that result from the decision to adopt. Distinguish Adopt, Adapt, Management & Governance. Develop an approach to adoption & adaptation. Distinguish & demonstrate the impact of organizational culture on developing cybersecurity as a capability. Develop an assessment approach to define current state. Adaptive Way of Working Threat actors are agile and highly adaptive. The cybersecurity Practitioner must develop the same capabilities Break down what constitutes an adaptive approach. Characterize & apply the need for crossfunctional teams. Recognize and prioritize the first steps (get started). Demonstrate & establish cybersecurity phases. Break down the impact of the flows. Rapid Adoption & Rapid Adaptation FastTrack FastTrack? is an approach to allow organizations to learn to adapt to an evolving threat landscape rapidly. Approach: Establish what it takes to adopt CS. Determine how that impacts management adaptation of CS. Determine how that impacts the capability to assess. CS Capability: Determine the gap between existing & needed capabilities. Establish what must be developed. Develop appropriate risk management profile. Discover how cybersecurity impacts people, practice & technology impacts organization. Differentiate CIS Implementation groups. Determine appropriate implementation group & approach. Develop appropriate phase approaches. CIIS Practice Cybersecurity is an ongoing game of cat and mouse. Organizations must learn how to inculcate cybersecurity improvement into their DNA. Break down & develop mechanisms for ongoing cybersecurity improvement that includes developing a learning organization. Illustrate an improvement plan based on the NIST 7-Step Approach. Illustrate an improvement plan based on the Improvement GPS Demonstrate understanding of Cybersecurity Maturity Model Certification Break down the balancing loop & how it fits into the escalation archetype Use the Fast Track? (improvement & implementation) cycles.

Duration 3 Days 18 CPD hours This course is intended for Data Analysts, Business Analysts, Business Intelligence professionals Cloud Data Engineers who will be partnering with Data Analysts to build scalable data solutions on Google Cloud Platform Overview This course teaches students the following skills: Derive insights from data using the analysis and visualization tools on Google Cloud Platform Interactively query datasets using Google BigQuery Load, clean, and transform data at scale Visualize data using Google Data Studio and other third-party platforms Distinguish between exploratory and explanatory analytics and when to use each approach Explore new datasets and uncover hidden insights quickly and effectively Optimizing data models and queries for price and performance Want to know how to query and process petabytes of data in seconds? Curious about data analysis that scales automatically as your data grows? Welcome to the Data Insights course! This four-course accelerated online specialization teaches course participants how to derive insights through data analysis and visualization using the Google Cloud Platform. The courses feature interactive scenarios and hands-on labs where participants explore, mine, load, visualize, and extract insights from diverse Google BigQuery datasets. The courses also cover data loading, querying, schema modeling, optimizing performance, query pricing, and data visualization. This specialization is intended for the following participants: Data Analysts, Business Analysts, Business Intelligence professionals Cloud Data Engineers who will be partnering with Data Analysts to build scalable data solutions on Google Cloud Platform To get the most out of this specialization, we recommend participants have some proficiency with ANSI SQL. Introduction to Data on the Google Cloud Platform Highlight Analytics Challenges Faced by Data Analysts Compare Big Data On-Premises vs on the Cloud Learn from Real-World Use Cases of Companies Transformed through Analytics on the Cloud Navigate Google Cloud Platform Project Basics Lab: Getting started with Google Cloud Platform Big Data Tools Overview Walkthrough Data Analyst Tasks, Challenges, and Introduce Google Cloud Platform Data Tools Demo: Analyze 10 Billion Records with Google BigQuery Explore 9 Fundamental Google BigQuery Features Compare GCP Tools for Analysts, Data Scientists, and Data Engineers Lab: Exploring Datasets with Google BigQuery Exploring your Data with SQL Compare Common Data Exploration Techniques Learn How to Code High Quality Standard SQL Explore Google BigQuery Public Datasets Visualization Preview: Google Data Studio Lab: Troubleshoot Common SQL Errors Google BigQuery Pricing Walkthrough of a BigQuery Job Calculate BigQuery Pricing: Storage, Querying, and Streaming Costs Optimize Queries for Cost Lab: Calculate Google BigQuery Pricing Cleaning and Transforming your Data Examine the 5 Principles of Dataset Integrity Characterize Dataset Shape and Skew Clean and Transform Data using SQL Clean and Transform Data using a new UI: Introducing Cloud Dataprep Lab: Explore and Shape Data with Cloud Dataprep Storing and Exporting Data Compare Permanent vs Temporary Tables Save and Export Query Results Performance Preview: Query Cache Lab: Creating new Permanent Tables Ingesting New Datasets into Google BigQuery Query from External Data Sources Avoid Data Ingesting Pitfalls Ingest New Data into Permanent Tables Discuss Streaming Inserts Lab: Ingesting and Querying New Datasets Data Visualization Overview of Data Visualization Principles Exploratory vs Explanatory Analysis Approaches Demo: Google Data Studio UI Connect Google Data Studio to Google BigQuery Lab: Exploring a Dataset in Google Data Studio Joining and Merging Datasets Merge Historical Data Tables with UNION Introduce Table Wildcards for Easy Merges Review Data Schemas: Linking Data Across Multiple Tables Walkthrough JOIN Examples and Pitfalls Lab: Join and Union Data from Multiple Tables Advanced Functions and Clauses Review SQL Case Statements Introduce Analytical Window Functions Safeguard Data with One-Way Field Encryption Discuss Effective Sub-query and CTE design Compare SQL and Javascript UDFs Lab: Deriving Insights with Advanced SQL Functions Schema Design and Nested Data Structures Compare Google BigQuery vs Traditional RDBMS Data Architecture Normalization vs Denormalization: Performance Tradeoffs Schema Review: The Good, The Bad, and The Ugly Arrays and Nested Data in Google BigQuery Lab: Querying Nested and Repeated Data More Visualization with Google Data Studio Create Case Statements and Calculated Fields Avoid Performance Pitfalls with Cache considerations Share Dashboards and Discuss Data Access considerations Optimizing for Performance Avoid Google BigQuery Performance Pitfalls Prevent Hotspots in your Data Diagnose Performance Issues with the Query Explanation map Lab: Optimizing and Troubleshooting Query Performance Advanced Insights Introducing Cloud Datalab Cloud Datalab Notebooks and Cells Benefits of Cloud Datalab Data Access Compare IAM and BigQuery Dataset Roles Avoid Access Pitfalls Review Members, Roles, Organizations, Account Administration, and Service Accounts

Duration 5 Days 30 CPD hours This course is intended for Experienced system administrators and system integrators responsible for designing and implementing vRealize Automation Overview By the end of the course, you should be able to meet the following objectives: Describe the vRealize Automation architecture and use cases in cloud environments Manage vRealize Automation entities on VMware and third-party virtual and cloud infrastructures Configure and manage Cloud Accounts, Projects, Flavor Mappings, Image Mappings, Network Profiles, Storage Profiles, Volumes, Tags, and Services Create, modify, manage, and deploy Cloud Templates Connect to a Kubernetes Cluster and manage namespaces Customize services and virtual machines with cloudConfig Configure and manage the Service Broker Configure and manage ABX actions, custom properties, event broker subscriptions, and vRealize Orchestrator workflows Integrate with vRealize Orchestrator Install vRealize Automation with Lifecycle Configuration Manager Describe Cloud Automation Services (Cloud Assembly and Code Stream). Integrate Cloud Assembly with Terraform and SaltStack Use logs and CLI commands to monitor and troubleshoot vRealize Automation During this five-day course, you focus on installing, configuring, and managing VMware vRealize© Automation?. You learn about how vRealize Automation 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 to manage both on-premise systems and cloud services. The course covers how vRealize Automation Service Broker can aggregate content in native formats from multiple clouds and platforms into a common catalog. This course also covers interfacing vRealize Automation with other systems using VMware vRealize© Orchestrator? and how to use vRealize Automation to manage Kubernetes systems and leverage other systems. The course also covers integrating with Terraform and using SaltStack as a configuration management tool. Course Introduction Introductions and course logistics Course objectives vRealize Automation Overview and Architecture Describe the purpose and functionality of vRealize Automation Describe the vRealize Automation architecture Describe the use of VMware Workspace ONE© AccessTM Describe the relationship between Kubernetes clusters, containers, and vRealize Automation services Describe CLI commands for vRealize Automation 8 cluster management Describe Cloud Assembly Describe Service Broker Describe Code Stream Installing vRealize Automation List the different vRealize Automation deployment types Describe the purpose of vRealize easy installer Describe the vRealize Automation installation process Authentication and Authorization Identity the steps involved in integrating Workspace One with Active Directory Describe features of Workspace One Describe the user roles available in vRealize Automation Identify the key tasks performed by each user role Define custom roles Configure branding and multitenancy Basic Initial Configuration Quickly create a basic configuration with a cloud account, cloud zone, project, flavor mapping, and image mapping. VMware Cloud Templates Configure and deploy a basic cloud template Create cloud templates that can run on any cloud Use cloudConfig to run commands, install software, and create users Use YAML for inputs, variables, and conditional deployments Tags and Storage Configuration Configure tags Describe different types of tags Manage tags Configure storage profiles Use tags and storage profiles Integrating NSX-T Data Center List the capabilities and use cases of NSX-T Data Center Describe the NSX-T Data Center architecture and components Integrate NSX-T Data Center with vRealize Automation List the supported network profiles in vRealize Automation Use NSX-T Data Center components to design a multitier application Cloud Template Identify the network and security options available in design canvas Create and manage on-demand networks and security groups Configure NSX-T day 2 actions Integrating with Public Clouds Configure and use VMware Cloud Foundation accounts Configure and use an AWS cloud account Configure and use an Azure cloud account Configure and use a Google Cloud Platform cloud account Using Service Broker for Catalog Management Release a VMware Cloud Template? Define content source and content sharing Define Service Broker policy enforcement Use custom forms for catalog items vRealize Automation Extensibility Describe Extensibility Use event topics Create a subscription Call a vRealize Orchestrator workflow Create ABX actions Using Code Stream Introduction to Code Stream The CI/CD process Integrate GitLab with Code Stream and Cloud Assembly Use Code Stream to install software Using Terraform Integrate Cloud Assembly with Terraform Use Terraform with a VMware Cloud Template Use Terraform with Code Stream Using Kubernetes Clusters Introduction to Kubernetes Connect to an existing Kubernetes Cluster Integrate VMware Tanzu? Grid Integrated Edition Create a Supervisor Namespace as a catalog item Using SaltStack for Configuration Management Introduction SaltStack with vRealize Automation Use SaltStack for software deployment Use SaltStack for configuration management Use SaltStack with event-driven orchestration vRealize Automation Troubleshooting and Integration Location of logs Using Activity Monitoring deployment history Basic troubleshooting CLI commands Collecting logs (VAMI console) Integration with VMware vRealize© Log Insight? Integration with vRealize Operations Migrating vRealize Automation 7.x to 8

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 1 Days 6 CPD hours This course is intended for To gain the most from attending this course you should possess the following incoming skills: Basic knowledge of programming concepts and syntax in Python. Familiarity with common data formats such as CSV, JSON, and XML. Experience using command-line interfaces and basic text editing tools. Understanding of basic machine learning concepts and algorithms. Overview Working in an interactive learning environment, led by our engaging expert, you will: Gain a solid understanding of prompt engineering concepts and their applications in software development and AI-driven solutions. Master the techniques for preprocessing and cleaning text data to ensure high-quality inputs for AI models like GPT-4. Develop expertise in GPT-4 tokenization, input formatting, and controlling model behavior for various tasks and requirements. Acquire the ability to design, optimize, and test prompts effectively, catering to diverse business applications and use cases. Learn advanced prompt engineering techniques, such as conditional text generation and multi-turn conversations, to create more sophisticated AI solutions. Practice creating prompts to generate, run, and test code in a chosen programming language using GPT-4 and OpenAI Codex. Understand the ethical implications and best practices in responsible AI deployment, ensuring fair and unbiased AI applications in software development. Prompt Engineering offers coders and software developers a competitive edge by empowering them to develop more effective and efficient AI-driven solutions in their projects. By harnessing the capabilities of cutting-edge AI models like GPT-4, coders can automate repetitive tasks, enhance natural language understanding, and even generate code suggestions, boosting productivity and creativity. In addition, mastering prompt engineering can contribute to improved job security, as professionals with these in-demand skills are highly sought after in the rapidly evolving tech landscape. Quick Start to Prompt Engineering for Coders and Software Developers is a one day course designed to get you quickly up and running with the prompting skills required to out AI to work for you in your development efforts. Guided by our AI expert, you?ll explore key topics such as text preprocessing, data cleansing, GPT-4 tokenization, input formatting, prompt design, and optimization, as well as ethical considerations in prompt engineering. In the hands-on labs you?ll explore tasks such as formatting inputs for GPT-4, designing and optimizing prompts for business applications, and implementing multi-turn conversations with AI. You?ll work with innovative tools like the OpenAI API, OpenAI Codex, and OpenAI Playground, enhancing your learning experience while preparing you for integrating prompt engineering into your professional toolkit. By the end of this immersive course, you?ll have the skills necessary to effectively use prompt engineering in your software development projects. You'll be able to design, optimize, and test prompts for various business tasks, integrate GPT-4 with other software platforms, and address ethical concerns in AI deployment. Introduction to Prompt Engineering Overview of prompt engineering and its importance in AI applications Major applications of prompt engineering in business Common challenges faced in prompt engineering Overview of GPT-4 and its role in prompt engineering Key terminology and concepts in prompt engineering Getting Things Ready: Text Preprocessing and Data Cleansing Importance of data preprocessing in prompt engineering Techniques for text cleaning and normalization Tokenization and n-grams Stop word removal and stemming Regular expressions and pattern matching GPT-4 Tokenization and Input Formatting GPT-4 tokenization and its role in prompt engineering Understanding and formatting GPT-4 inputs Context windows and token limits Controlling response length and quality Techniques for handling out-of-vocabulary tokens Prompt Design and Optimization Master the skills to design, optimize, and test prompts for various business tasks. Designing effective prompts for different tasks Techniques for prompt optimization GPT-4 system and user parameters for controlling behavior Importance of prompt testing and iteration Best practices for prompt engineering in business applications Advanced Techniques and Tools in Prompt Engineering Learn advanced techniques and tools for prompt engineering and their integration in business applications. Conditional text generation with GPT-4 Techniques for handling multi-turn conversations Overview of tools for prompt engineering: OpenAI API, OpenAI Codex, and OpenAI Playground Integration of GPT-4 with other software platforms and tools Monitoring and maintaining prompt performance Code Generation and Testing with Prompt Engineering Develop the skills to generate, integrate, and test AI-generated code effectively, enhancing productivity and creativity in software development projects. Introduction to code generation with AI models like GPT-4 Designing prompts for code generation across programming languages Techniques for specifying requirements and constraints in prompts Generating and interpreting code snippets using AI-driven solutions Integrating generated code into existing projects and codebases Best practices for testing and validating AI-generated code Ethics and Responsible AI Understand the ethical implications of prompt engineering and the importance of responsible AI deployment in business. Ethical considerations in prompt engineering Bias in AI systems and its impact on prompt engineering Techniques to minimize bias and ensure fairness Best practices for responsible AI deployment in business applications Monitoring and addressing ethical concerns in prompt engineering

Duration 5 Days 30 CPD hours This course is intended for Data Warehouse Administrator Database Administrators Support Engineer Technical Administrator Technical Consultant Overview Use Oracle Flashback Technologies to recover from human error Use Recovery Manager (RMAN) to create backups and perform recovery operations Use the Data Recovery Advisor to diagnose and repair failures Plan effective backup and recovery procedures Describe the Oracle Database architecture components related to backup and recovery operations Perform an encrypted database backup and restore Perform tablespace point-in-time recovery Configure the database for recoverability Describe Cloud Tooling for Backup and Recovery Describe Oracle Database backup methods and recovery operations that can be used to resolve database failure In this Oracle Database 12c R2: Backup and Recovery Workshop, students learn how to perform backup and recovery based on the related Oracle Database architecture components. Various backup, failure, restore, and recovery scenarios are provided so that students learn to evaluate their own recovery requirements and develop an appropriate strategy for backup and recovery procedures. This course includes an interactive workshop, with scenarios that provide participants with opportunities to diagnose and recover from several failure situations. Introduction Curriculum Context Assess your recovery requirements Categories of failures Oracle backup and recovery solutions Oracle Maximum Availability Architecture Oracle Secure Backup Benefits of using Oracle Data Guard Basic Workshop Architecture Getting Started Core Concepts of the Oracle Database, critical for Backup and Recovery Oracle DBA Tools for Backup and Recovery Connecting to Oracle Recovery Manager (RMAN) Configuring for Recoverablility RMAN commands Configuring and managing persistent settings Using the Fast Recovery Area (FRA) Control File Redo Log File Archiving Logs Using the RMAN Recovery Catalog Creating and Configuring the Recovery Catalog Managing Target Database Records in the Recovery Catalog Using RMAN Stored Scripts Maintaining and Protecting the Recovery Catalog Virtual Private Catalogs Backup Strategies and Terminology Backup Solutions Overview and Terminology Balancing Backup and Restore Requirements Backing Up Read-Only Tablespaces Data Warehouse Backup and Recovery: Best Practices Additional Backup Terminology Performing Backups RMAN Backup Types Incrementally Updated Backups Fast Incremental Backup Block Change Tracking Oracle-Suggested Backup Reporting on Backups Managing Backups Improving Your Backups Compressing Backups Using a Media Manager Backup and Restore for Very Large Files Creating RMAN Multi-section Backups, Proxy Copies, Duplexed Backup Sets and Backups of Backup Sets Creating and Managing Archival Backups Backing Up Recovery Files Backing Up the Control File to a Trace File Cataloging Additional Backup Files Using RMAN-Encrypted Backups Creating RMAN-Encrypted Backups Using Transparent-Mode Encryption Using Password-Mode Encryption Using Dual-Mode Encryption Diagnosing Failures Reducing Problem Diagnosis Time Automatic Diagnostic Repository Data Recovery Advisor Handling Block Corruption Restore and Recovery Concepts Restoring and Recovering Instance Failure and Instance/Crash Recovery Media Failure Complete Recovery (Overview) Point-in-Time Recovery (Overview) Recovery with the RESETLOGS Option Performing Recovery, Part I RMAN Recovery in NOARCHIVELOG Mode Performing Complete Recovery (of critical and noncritical data files) Restoring ASM Disk Groups Recovery with Image Files Performing Point-in-Time (PITR) or Incomplete Recovery Performing Recovery, Part II Recovery of Server Parameter File, Control File (One and All) Redo Log File Loss and Recovery Password Authentication File Re-creation Index, Read-Only Tablespace, and Temp file Recovery Restoring the Database to a New Host Disaster Recovery Restoring RMAN Encrypted Backups RMAN and Oracle Secure Backup Oracle Secure Backup Overview and Interface Options RMAN and OSB: Overview and Basic Process Flow Starting with Oracle Secure Backup Configuring Oracle Secure Backup for RMAN RMAN Backup and Restore Operations Oracle Secure Backup Jobs Displaying OSB log files and transcripts for RMAN activities Using Flashback Technologies Flashback Technology: Overview and Setup Using Flashback Technology to Query Data Flashback Table Flashback Transaction (Query and Back out) Flashback Drop and the Recycle Bin Flashback Data Archive Using Flashback Database Flashback Database Architecture Configuring Flashback Database Performing Flashback Database Best Practices for Flashback Database Transporting Data Transporting Data Across Platforms Transporting Data with Backup Sets Database Transport: Using Data Files Performing Point-in-Time Recovery When to use TSPITR TSPITR Architecture Performing RMAN TS Point-in-time Recovery Recovering Tables from Backups Duplicating a Database Using a Duplicate Database Duplicating Database with 'push' and 'pull' techniques Choosing Database Duplication Techniques Creating a Backup-up Based Duplicate Database Understanding the RMAN Duplication Operation RMAN Troubleshooting and Tuning Interpreting RMAN Message Output Tuning Principles Diagnosing Performance Bottlenecks RMAN Multiplexing Restore and Recovery Performance Best Practices Cloud Tooling for Backup and Recovery Backup Destinations Customize Backup Configuration On-Demand Backup and Recovery Oracle Backup Cloud Service Installing the Backup Module Backup and Recovery Workshop Workshop Structure and Approach Business Requirements for Database Availability and Procedures Diagnosing the Failures