1419 Courses in Cardiff delivered Live Online

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 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 3 Days 18 CPD hours This course is intended for This course benefits individuals responsible for configuring and monitoring devices running the Junos OS. Overview After successfully completing this course, you should be able to: Describe the basic design architecture of the Junos OS. Identify and provide a brief overview of Junos devices. Navigate within the Junos CLI. Perform tasks within the CLI operational and configuration modes. Restore a Junos device to its factory-default state. Perform initial configuration tasks. Configure and monitor network interfaces. Describe user configuration and authentication options. Perform secondary configuration tasks for features and services such as system logging (syslog) and tracing, Network Time Protocol (NTP), configuration archival, and SNMP. Monitor basic operation for the Junos OS and devices. Identify and use network utilities. Upgrade the Junos OS. Perform file system maintenance and password recovery on a Junos device. Navigate within the Junos J-Web interface. Explain basic routing operations and concepts. View and describe routing and forwarding tables. Configure and monitor static routing. Configure and monitor OSPF. Describe the framework for routing policy and firewall filters. Explain the evaluation of routing policy and firewall filters. Identify instances where you might use routing policy. Write and apply a routing policy. Identify instances where you might use firewall filters. Write and apply a firewall filter. Describe the operation and configuration for unicast reverse path forwarding (RPF). This three-day course provides students with the foundational knowledge required to work with the Juniper Networks Junos operating system and to configure Junos devices. The course provides a brief overview of the Junos device families and discusses the key architectural components of the software. Key topics include user interface options with a heavy focus on the command-line interface (CLI), configuration tasks typically associated with the initial setup of devices, interface configuration basics with configuration examples, secondary system configuration, and the basics of operational monitoring and maintenance of Junos devices. The course then delves into foundational routing knowledge and configuration examples including general routing concepts, routing policy, and firewall filters. Course Outline COURSE INTRODUCTION Junos Operating System Fundamentals The Junos OS Traffic Processing Overview of Junos Devices User Interface Options: The Junos CLI User Interface Options The Junos CLI: CLI Basics The Junos CLI: Operational Mode The Junos CLI: Configuration Mode User Interface Options: The J-Web Interface User Interface Options The Junos CLI: CLI Basics The Junos CLI: Operational Mode The Junos CLI: Configuration Mode Initial Configuration Factory-Default Configuration Initial Configuration Interface Configuration Secondary System Configuration User Configuration and Authentication System Logging and Tracing Network Time Protocol Archiving Configurations SNMP Operational Monitoring and Maintenance Monitoring Platform and Interface Operation Network Utilities Maintaining the Junos OS Password Recovery System Clean-Up Interface Configuration Examples Review of the Interface Configuration Hierarchy Interface Configuration Examples Using Configuration Groups Routing Fundamentals Routing Concepts: Overview of Routing Routing Concepts: The Routing Table Routing Concepts: Routing Instances Static Routing Dynamic Routing Routing Policy Routing Policy Overview Case Study: Routing Policy Firewall Filters Firewall Filters Overview Case Study: Firewall Filters Unicast Reverse-Path-Forwarding Checks Class of Service CoS Overview Traffic Classification Traffic Queueing Traffic Scheduling Case Study: CoS JTAC Procedures Opening a Support Case Customer Support Tools Transferring Files to JTAC Juniper Security Concepts Security Challenges Juniper Networks? Security Focus A IPv6 Fundamentals IPv6 Addressing Protocols and Services Configuration Additional course details: Nexus Humans Juniper - Introduction to the Junos Operating System (IJOS) 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 Juniper - Introduction to the Junos Operating System (IJOS) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 5 Days 30 CPD hours This course is intended for This course is recommended for IT Professionals and Consultants. Overview Identify risks and areas for improvement in a Citrix Virtual Apps and Desktops environment by assessing relevant information in an existing deployment. Determine core Citrix Virtual Apps and Desktops design decisions and align them to business requirements to achieve a practical solution. Design a Citrix Virtual Apps and Desktops disaster recovery plan and understand different disaster recovery considerations. This advanced 5-day training course teaches the design principles for creating a Citrix Virtual Apps and Desktops virtualization solution. In this training, you will also learn how to assess existing environments, explore different scenarios, and make design decisions based on business requirements. This course covers the Citrix Consulting approach to design and covers the key design decisions through lectures, lab exercises, and interactive discussions. You will also learn about additional considerations and advanced configurations for multi-location solutions and disaster recovery planning. This training will help you prepare for the Citrix Certified Expert in Virtualization (CCE-V) exam. Module 1: Methodology & Assessment The Citrix Consulting Methodology Citrix Consulting Methodology Use Business Drivers Prioritize Business Drivers User Segmentation User Segmentation Process App Assessment Introduction App Assessment Analysis Why Perform a Capabilities Assessment? Common Capabilities Assessment Risks Module 2: User Layer Endpoint Considerations Peripherals Considerations Citrix Workspace App Version Considerations Citrix Workspace App Multiple Version Considerations Network Connectivity and the User Experience Bandwidth and Latency Considerations Graphics Mode Design Considerations HDX Transport Protocols Considerations Media Content Redirection Considerations Session Interruption Management Session Reliability Feature Considerations Session Interruption Management Auto-Client Reconnect Feature Considerations Session Interruption Management ICA Keep-Alive Feature Considerations Module 3: Access Layer Access Matrix Access Layer Access Layer Communications Double-Hop Access Layer Considerations Citrix Cloud Access Layer Considerations Use Cases for Multiple Stores Define Access Paths per User Group Define Number of URLs Configuration and Prerequisites for Access Paths Citrix Gateway Scalability Citrix Gateway High Availability StoreFront Server Scalability StoreFront Server High Availability Module 4: Resource Layer - Images Flexcast Models VDA Machine Scalability VDA Machine Sizing with NUMA VDA Machine Sizing VDA Machine Scalability Cloud Considerations Scalability Testing and Monitoring Secure VDA Machines Network Traffic Secure VDA Machines Prevent Breakouts Secure VDA Machines Implement Hardening Secure VDA Machines Anti-Virus Review of Image Methods Citrix Provisioning Overall Benefits and Considerations Citrix Provisioning Target Device Boot Methods Citrix Provisioning Read Cache and Sizing Citrix Provisioning Write Cache Type Citrix Provisioning vDisk Store Location Citrix Provisioning Network Design Citrix Provisioning Scalability Considerations Citrix Machine Creation Services Overall Benefits and Considerations Citrix Machine Creation Services Cloning Types Citrix Machine Creation Services Storage Locations & Sizing Citrix Machine Services Read and Write Cache App Layering Considerations Image Management Methods Module 5: Resource Layer - Applications and Personalization Application Delivery Option Determine the Optimal Deployment Method for an App General Application Concerns Profile Strategy Profile Types Review Citrix Profile Management Design Considerations Citrix Profile Management Scaling Citrix Profile Management Permissions Policies Review Optimize Logon Performance with Policies Printing Considerations Module 6: Control Layer Pod Architecture Introduction Pod Architecture Considerations Citrix Virtual Apps and Desktops Service Design Considerations Implement User Acceptance Testing Load Balancing the Machine Running the VDA Citrix Director Design Considerations Management Console Considerations Change Control Delivery Controller Scalability and High Availability Control Layer Security Configuration Logging Considerations Session Recording Module 7: Hardware/Compute Layer Hypervisor Host Hardware Considerations Separating Workloads Considerations Workload Considerations VMs Per Host and Hosts Per Pool Citrix Hypervisor Scalability VM Considerations in Azure and Amazon Web Services Storage Tier Considerations Storage I/O Considerations Storage Architecture Storage RAID & Disk Type Storage Sizing LUNs Storage Bandwidth Storage in Public Cloud Datacenter Networking Considerations Securing Hypervisor Administrative Access Secure the Physical Datacenter Secure the Virtual Datacenter Module 8: Module 8: High Availability and Multiple Location Environments Redundancy vs. Fault Tolerance vs. High Availability Multi-Location Architecture Considerations Multi-Site Architecture Considerations Global Server Load Balancing Optimal Gateway Routing Zone Preference and Failover StoreFront Resource Aggregation StoreFront Subscription Sync Hybrid Environment Options Citrix Provisioning Across Site Site Database Scalability and High Availability Citrix Provisioning Across Sites Considerations Citrix Machine Creation Across Sites App Layering Across Sites Managing Roaming Profiles and Citrix Workspace App Configurations Across Devices Profile Management Multi-Site Replication Considerations Folder Redirections and Other User Data in a Multi-Location Environment Application Data Considerations Cloud-Based Storage Replication Options Multi-Location Printing Considerations Zone Considerations Active Directory Considerations Module 9: Disaster Recovery Tiers of Disaster Recovery Disaster Recovery Considerations Business Continuity Planning and Testing Citrix Standard of Business Continuity

Duration 3 Days 18 CPD hours This course is intended for This course is intended for both novice and experienced project managers, managers, schedulers, and other project stake holders who need to incorporate the discipline of project management with Microsoft Project 2019. Overview Understand the discipline of project management as it applies to using Microsoft Project 2019. Create a Work Breakdown Structure. Identify Task Types & Relationships. Define Resources within Project. Make Work Package Estimates. Create an Initial Schedule. Create a Resource Leveled Schedule. Create Projects from templates, Excel files. Create Global templates. Create formulas and graphical indicators. The steps to record a macro. Format Output and Print Reports. Integrate Multiple Projects. Set up a Project with a Calendar, Start date, and scheduling method. Understand Manually Schedule vs. Auto Schedule. Manage multiple projects. Be able to create a master project list with shared resources. This three-day instructor-led course is intended for individuals who are interested in expanding their knowledge base and technical skills about Microsoft Project. The course begins with the basic concepts and leads students through all the functions they?ll need to plan and manage a small to medium-size project, including how to level resources and capture both cost and schedule progress. 1 - Introduction to Microsoft Project Describe how Project relates to the discipline of Project management. Learn what the new features are in Project 2019. Navigate to the primary views available using the Ribbon. Choose Views that display task, resource, or assignment information. Select table within views to change the information that is available to see and edit. Relate the features of Project to the 5 steps for building a plan in Project. Learn new accessibility features in Project 2 - A Quick and Easy Overview of Managing with Project Create a new project and prepare it for data entry. Enter project tasks. Sequence the tasks. Define resources. Estimate Task duration and assign resources. Baseline the project. Track project progress. 3 - Setting Up a Project Use multiple methods to create a new project from an Excel file and a SharePoint Tasks list. Establish one or more calendars to constrain resource availability. Configure Project to calculate the schedule from the Start Date forward, or from the Finish Date backward. 4 - Manually Schedule vs. Auto Schedule Students practice switching tasks between Manually Schedule and Auto Schedule modes. By switching modes, students learn the impact made on the project schedule and the individual tasks. 5 - Creating a Work Breakdown Structure Build and use summary and subordinate tasks. Understand and use milestones. Develop WBS Outlines. Assign completion criteria. Evaluate the WBS. Understand and use WBS templates. 6 - Identifying Task Relationships Understand the different types of task relationships. Understand and use various methods to create relationships. Determine and display task sequence. Understand and use lag, lead, and delay. Understand the new feature of Task Paths. 7 - Defining Resources within Project Define resource types. Define individual resources that will be used on the project. Record the cost (s) of using each type of resource. Record the limit of availability for each type of resource by establishing a resource calendar and defining the maximum units of that resource. 8 - Making Work Package Estimates Enter estimates for duration and costs for each task. Distinguish between task types and describe when each is appropriate. Describe the relationship between work, units, and duration. Describe the way Effort Driven scheduling is affected by work, units, and duration. Assign tasks to resources using the Team Planner view. 9 - Creating an Initial Schedule Calculate float and identify a project?s critical path. Understand and identify task constraints. Create milestones. Use the Task Inspector to troubleshoot the initial schedule. 10 - Create a Resource Leveled Schedule Adjust a project schedule to account for limited people and other resources. View the overall cost and schedule of a project. Identify resources that have been overallocated for a project schedule. Use multiple ways to adjust tasks and assignments to remove over allocation for any resource. 11 - Managing the Project Learn how to set a baseline. Lean how to enter and track project performance data. Learn how to apply different tracking methods. Learn how to perform a variance analysis on a project. Learn how to Reschedule Work Learn how to inactivate tasks Learn how to synch projects to SharePoint 12 - Formatting Output and Printing Reports Print Views Formats Sorting Filtering Grouping Custom Fields Reporting Other File Formats 13 - Managing Multiple Projects Learn how to use common resources among multiple projects. Learn how to link tasks between multiple projects. Learn how to create a consolidated view of multiple projects. 14 - Advanced Topics Learn how to customize the Ribbon and the Quick Access Toolbar. Learn how to customize WBS numbering. Learn the concepts of Formulas and Graphical indicators. Learn the purpose of the Global template and Organizer. Learn how to record a Macro.

Duration 3 Days 18 CPD hours This course is intended for Experienced system administrators or network administrators, software and DevOps engineers Overview By the end of the course, you should be able to meet the following objectives: Describe VMware NSX Advanced Load Balancer architecture Describe VMware NSX Advanced Load Balancer components and main functions Explain VMware NSX Advanced Load Balancer key features and benefits Describe and leverage VMware NSX Advanced Load Balancer REST API Describe and leverage VMware NSX Advanced Load Balancer SDKs with extended focus on Python SDK Leverage REST API and SDK features and functions to provision application delivery components Describe and leverage VMware NSX Advanced Load Balancer Ansible and Terraform integrations Describe and leverage VMware NSX Advanced Load Balancer Github, Docker (avinetworks/avitools), Ansible Galaxy and other open source resources to accelerate the automation planning and implementation Leverage VMware NSX Advanced Load Balancer Ansible and Terraform integrations to provision infrastructure components Leverage VMware NSX Advanced Load Balancer Ansible and Terraform integrations to automate and streamline application delivery services provisioning This three-day, fast-paced course provides comprehensive training on how to automate infrastructure and application components of VMware NSX Advanced Load Balancer (Avi Networks) solution. This course covers key application delivery features of NSX Advanced Load Balancer (Avi Networks) features and functionality offered in VMware NSX Advanced Load Balancer 18.2 release and focuses on how to plan and implement automation of infrastructure and application components leveraging REST API, SDK or automation solutions such as Ansible, Terraform or similar. 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 Pools Configuration Concepts Explain and deep dive on Pool configuration options Describe multiple load balancing algorithms Explain multiple Health Monitor types Explain multiple Persistent profiles Explain and configure Pool Groups Leveraging NSX Advanced Load Balancer REST API Explain NSX Advanced Load Balancer automation vision Explain and introduce NSX Advanced Load Balancer REST API Describe NSX Advanced Load Balancer REST API methods and capabilities Describe NSX Advanced Load Balancer REST API session handling properties such authentication, API versioning and tenancy model Deep dive on NSX Advanced Load Balancer REST API Object Model Explain and investigate NSX Advanced Load Balancer REST API leveraging browser and command line utilities Explain and interact with NSX Advanced Load Balancer REST API leveraging browser, Postman and Curl Explain Swagger-based API Documentation Explain and leverage NSX Advanced Load Balancer Inventory API Explain and leverage NSX Advanced Load Balancer methods such as GET, PUT, POST and PATCH and associated queries, filters and parameters Deep dive on NSX Advanced Load Balancer PATCH method Explain and leverage NSX Advanced Load Balancer Analytics API Explain and leverage NSX Advanced Load Balancer MACRO API NSX Advanced Load Balancer Software-Defined Kits (SDKs) and ControlScripts Introduce NSX Advanced Load Balancer SDKs Describe, install and leverage NSX Advanced Load Balancer Python SDK Deep dive on NSX Advanced Load Balancer Python SDK Describe and leverage Golang SDK Leverage NSX Advanced Load Balancer open source resources such as Github, etc to accelerate SDKs adoption Describe NSX Advanced Load Balancer Events and Alerts framework Introduce ControlScripts foundations Leverage ControlScripts to automate configuration changes and alerts remediation Automating NSX Advanced Load Balancer Application Delivery Services with Ansible and Terraform Introduce NSX Advanced Load Balancer Configuration Orchestration and Management vision Introduce and explain Ansible foundations Describe Ansible and NSX Advanced Load Balancer Ansible capabilities Deep dive and implement NSX Advanced Load Balancer Ansible Core configuration modules (avinetworks/avisdk) Deep dive and implement Ansible NSX Advanced Load Balancer Declarative configuration role (avinetworks/aviconfig) Leverage Swagger NSX Advanced Load Balancer REST API models to develop and implement Ansible playbooks Explain application delivery configuration automation approach and models Apply configuration automation models with Ansible Introduce and explain Terraform foundations Describe Terraform and NSX Advanced Load Balancer Terraform capabilities Deep dive and implement NSX Advanced Load Balancer Terraform Provider Leverage Swagger NSX Advanced Load Balancer REST API models to develop and implement Terraform plans Apply configuration automation models with Terraform Automating NSX Advanced Load Balancer Infrastructure with Ansible and Terraform Introduce NSX Advanced Load Balancer infrastructure Automation vision Describe infrastructure deployment approach and capabilities Describe Ansible and NSX Advanced Load Balancer Ansible Infrastructure deployment approach and capabilities Describe Terraform and NSX Advanced Load Balancer Terraform deployment approach and capabilities Leverage Terraform to deploy Controllers and perform system configuration, including control plane cluster setup Leverage Terraform to provision Cloud, Service Engine Groups and Service Engine components Describe and leverage Ansible roles to deploy Controllers and perform initial system configuration, including control plane cluster setup Leverage Ansible declarative and core roles to provision Cloud, Service Engine Groups and Service Engine components Describe and implement combined Terraform + Ansible model to streamline NSX Advanced Load Balancer solution deployment

Duration 4 Days 24 CPD hours This course is intended for Students in this course are interested in implementing DevOps processes or in passing the Microsoft Azure DevOps Solutions certification exam. Overview After completing this course, students will be able to: Plan for the transformation with shared goals and timelines Select a project and identify project metrics and Key Performance Indicators (KPI's) Create a team and agile organizational structure Design a tool integration strategy Design a license management strategy (e.g., Azure DevOps and GitHub users) Design a strategy for end-to-end traceability from work items to working software Design an authentication and access strategy Design a strategy for integrating on-premises and cloud resources Describe the benefits of using Source Control Describe Azure Repos and GitHub Migrate from TFVC to Git Manage code quality including technical debt SonarCloud, and other tooling solutions Build organizational knowledge on code quality Explain how to structure Git repos Describe Git branching workflows Leverage pull requests for collaboration and code reviews Leverage Git hooks for automation Use Git to foster inner source across the organization Explain the role of Azure Pipelines and its components Configure Agents for use in Azure Pipelines Explain why continuous integration matters Implement continuous integration using Azure Pipelines Define Site Reliability Engineering Design processes to measure end-user satisfaction and analyze user feedback Design processes to automate application analytics Manage alerts and reduce meaningless and non-actionable alerts Carry out blameless retrospectives and create a just culture Define an infrastructure and configuration strategy and appropriate toolset for a release pipeline and application infrastructure Implement compliance and security in your application infrastructure Describe the potential challenges with integrating open-source software Inspect open-source software packages for security and license compliance Manage organizational security and compliance policies Integrate license and vulnerability scans into build and deployment pipelines Configure build pipelines to access package security and license ratings This course provides the knowledge and skills to design and implement DevOps processes and practices. Students will learn how to plan for DevOps, use source control, scale Git for an enterprise, consolidate artifacts, design a dependency management strategy, manage secrets, implement continuous integration, implement a container build strategy, design a release strategy, set up a release management workflow, implement a deployment pattern, and optimize feedback mechanisms. Module 1: Get started on a DevOps transformation journey Introduction to DevOps Choose the right project Describe team structures Choose the DevOps tools Plan Agile with GitHub Projects and Azure Boards Introduction to source control Describe types of source control systems Work with Azure Repos and GitHub Module 2: Development for enterprise DevOps Structure your Git Repo Manage Git branches and workflows Collaborate with pull requests in Azure Repos Explore Git hooks Plan foster inner source Manage Git repositories Identify technical debt Module 3: Implement CI with Azure Pipelines and GitHub Actions Explore Azure Pipelines Manage Azure Pipeline agents and pools Describe pipelines and concurrency Explore Continuous integration Implement a pipeline strategy Integrate with Azure Pipelines Introduction to GitHub Actions Learn continuous integration with GitHub Actions Design a container build strategy Module 4: Design and implement a release strategy Introduction to continuous delivery Explore release strategy recommendations Build a high-quality release pipeline Introduction to deployment patterns Implement blue-green deployment and feature toggles Implement canary releases and dark launching Implement A/B testing and progressive exposure deployment Module 5: Implement a secure continuous deployment using Azure Pipelines Create a release pipeline Provision and test environments Manage and modularize tasks and templates Automate inspection of health Manage application configuration data Integrate with identity management systems Implement application configuration Module 6: Manage infrastructure as code using Azure and DSC Explore infrastructure as code and configuration management Create Azure resources using Azure Resource Manager templates Create Azure resources by using Azure CLI Explore Azure Automation with DevOps Implement Desired State Configuration (DSC) Implement Bicep Module 7: Implement security and validate code bases for compliance Introduction to Secure DevOps Implement open-source software Software Composition Analysis Static analyzers OWASP and Dynamic Analyzers Security Monitoring and Governance Module 8: Design and implement a dependency management strategy Explore package dependencies Understand package management Migrate, consolidate, and secure artifacts Implement a versioning strategy Introduction to GitHub Packages Module 9: Implement continuous feedback Implement tools to track usage and flow Develop monitor and status dashboards Share knowledge within teams Design processes to automate application analytics Manage alerts, Blameless retrospectives and a just culture Additional course details: Nexus Humans AZ-400 Designing and Implementing Microsoft DevOps Solutions 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 AZ-400 Designing and Implementing Microsoft DevOps Solutions 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 Cloud Solutions Architects, Site Reliability Engineers, Systems Operations professionals, DevOps Engineers, IT managers. Individuals using Google Cloud Platform to create new solutions or to integrate existing systems, application environments, and infrastructure with the Google Cloud Platform. Overview Apply a tool set of questions, techniques and design considerations Define application requirements and express them objectively as KPIs, SLO's and SLI's Decompose application requirements to find the right microservice boundaries Leverage Google Cloud developer tools to set up modern, automated deployment pipelines Choose the appropriate Google Cloud Storage services based on application requirements Architect cloud and hybrid networks Implement reliable, scalable, resilient applications balancing key performance metrics with cost Choose the right Google Cloud deployment services for your applications Secure cloud applications, data and infrastructure Monitor service level objectives and costs using Stackdriver tools This course features a combination of lectures, design activities, and hands-on labs to show you how to use proven design patterns on Google Cloud to build highly reliable and efficient solutions and operate deployments that are highly available and cost-effective. This course was created for those who have already completed the Architecting with Google Compute Engine or Architecting with Google Kubernetes Engine course. Defining the Service Describe users in terms of roles and personas. Write qualitative requirements with user stories. Write quantitative requirements using key performance indicators (KPIs). Evaluate KPIs using SLOs and SLIs. Determine the quality of application requirements using SMART criteria. Microservice Design and Architecture Decompose monolithic applications into microservices. Recognize appropriate microservice boundaries. Architect stateful and stateless services to optimize scalability and reliability. Implement services using 12-factor best practices. Build loosely coupled services by implementing a well-designed REST architecture. Design consistent, standard RESTful service APIs. DevOps Automation Automate service deployment using CI/CD pipelines. Leverage Cloud Source Repositories for source and version control. Automate builds with Cloud Build and build triggers. Manage container images with Google Container Registry. Create infrastructure with code using Deployment Manager and Terraform. Choosing Storage Solutions Choose the appropriate Google Cloud data storage service based on use case, durability, availability, scalability and cost. Store binary data with Cloud Storage. Store relational data using Cloud SQL and Spanner. Store NoSQL data using Firestore and Cloud Bigtable. Cache data for fast access using Memorystore. Build a data warehouse using BigQuery. Google Cloud and Hybrid Network Architecture Design VPC networks to optimize for cost, security, and performance. Configure global and regional load balancers to provide access to services. Leverage Cloud CDN to provide lower latency and decrease network egress. Evaluate network architecture using the Cloud Network Intelligence Center. Connect networks using peering and VPNs. Create hybrid networks between Google Cloud and on-premises data centers using Cloud Interconnect. Deploying Applications to Google Cloud Choose the appropriate Google Cloud deployment service for your applications. Configure scalable, resilient infrastructure using Instance Templates and Groups. Orchestrate microservice deployments using Kubernetes and GKE. Leverage App Engine for a completely automated platform as a service (PaaS). Create serverless applications using Cloud Functions. Designing Reliable Systems Design services to meet requirements for availability, durability, and scalability. Implement fault-tolerant systems by avoiding single points of failure, correlated failures, and cascading failures. Avoid overload failures with the circuit breaker and truncated exponential backoff design patterns. Design resilient data storage with lazy deletion. Analyze disaster scenarios and plan for disaster recovery using cost/risk analysis. Security Design secure systems using best practices like separation of concerns, principle of least privilege, and regular audits. Leverage Cloud Security Command Center to help identify vulnerabilities. Simplify cloud governance using organizational policies and folders. Secure people using IAM roles, Identity-Aware Proxy, and Identity Platform. Manage the access and authorization of resources by machines and processes using service accounts. Secure networks with private IPs, firewalls, and Private Google Access. Mitigate DDoS attacks by leveraging Cloud DNS and Cloud Armor. Maintenance and Monitoring Manage new service versions using rolling updates, blue/green deployments, and canary releases. Forecast, monitor, and optimize service cost using the Google Cloud pricing calculator and billing reports and by analyzing billing data. Observe whether your services are meeting their SLOs using Cloud Monitoring and Dashboards. Use Uptime Checks to determine service availability. Respond to service outages using Cloud Monitoring Alerts. Additional course details: Nexus Humans Architecting with Google Cloud: Design and Process training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Architecting with Google Cloud: Design and Process 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 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 Additional course details: Nexus Humans Fast Track to Scala Programming Essentials for OO / Java Developers (TTSCL2104) 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 Fast Track to Scala Programming Essentials for OO / Java Developers (TTSCL2104) 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 in an intermediate and beyond-level course is geared for experienced Python developers looking to delve into the exciting field of Natural Language Processing. It is ideally suited for roles such as data analysts, data scientists, machine learning engineers, or anyone working with text data and seeking to extract valuable insights from it. If you're in a role where you're tasked with analyzing customer sentiment, building chatbots, or dealing with large volumes of text data, this course will provide you with practical, hands on skills that you can apply right away. Overview This course combines engaging instructor-led presentations and useful demonstrations with valuable hands-on labs and engaging group activities. Throughout the course you'll: Master the fundamentals of Natural Language Processing (NLP) and understand how it can help in making sense of text data for valuable insights. Develop the ability to transform raw text into a structured format that machines can understand and analyze. Discover how to collect data from the web and navigate through semi-structured data, opening up a wealth of data sources for your projects. Learn how to implement sentiment analysis and topic modeling to extract meaning from text data and identify trends. Gain proficiency in applying machine learning and deep learning techniques to text data for tasks such as classification and prediction. Learn to analyze text sentiment, train emotion detectors, and interpret the results, providing a way to gauge public opinion or understand customer feedback. The Hands-on Natural Language Processing (NLP) Boot Camp is an immersive, three-day course that serves as your guide to building machines that can read and interpret human language. NLP is a unique interdisciplinary field, blending computational linguistics with artificial intelligence to help machines understand, interpret, and generate human language. In an increasingly data-driven world, NLP skills provide a competitive edge, enabling the development of sophisticated projects such as voice assistants, text analyzers, chatbots, and so much more. Our comprehensive curriculum covers a broad spectrum of NLP topics. Beginning with an introduction to NLP and feature extraction, the course moves to the hands-on development of text classifiers, exploration of web scraping and APIs, before delving into topic modeling, vector representations, text manipulation, and sentiment analysis. Half of your time is dedicated to hands-on labs, where you'll experience the practical application of your knowledge, from creating pipelines and text classifiers to web scraping and analyzing sentiment. These labs serve as a microcosm of real-world scenarios, equipping you with the skills to efficiently process and analyze text data. Time permitting, you?ll also explore modern tools like Python libraries, the OpenAI GPT-3 API, and TensorFlow, using them in a series of engaging exercises. By the end of the course, you'll have a well-rounded understanding of NLP, and will leave equipped with the practical skills and insights that you can immediately put to use, helping your organization gain valuable insights from text data, streamline business processes, and improve user interactions with automated text-based systems. You?ll be able to process and analyze text data effectively, implement advanced text representations, apply machine learning algorithms for text data, and build simple chatbots. Launch into the Universe of Natural Language Processing The journey begins: Unravel the layers of NLP Navigating through the history of NLP Merging paths: Text Analytics and NLP Decoding language: Word Sense Disambiguation and Sentence Boundary Detection First steps towards an NLP Project Unleashing the Power of Feature Extraction Dive into the vast ocean of Data Types Purification process: Cleaning Text Data Excavating knowledge: Extracting features from Texts Drawing connections: Finding Text Similarity through Feature Extraction Engineer Your Text Classifier The new era of Machine Learning and Supervised Learning Architecting a Text Classifier Constructing efficient workflows: Building Pipelines for NLP Projects Ensuring continuity: Saving and Loading Models Master the Art of Web Scraping and API Usage Stepping into the digital world: Introduction to Web Scraping and APIs The great heist: Collecting Data by Scraping Web Pages Navigating through the maze of Semi-Structured Data Unearth Hidden Themes with Topic Modeling Embark on the path of Topic Discovery Decoding algorithms: Understanding Topic-Modeling Algorithms Dialing the right numbers: Key Input Parameters for LSA Topic Modeling Tackling complexity with Hierarchical Dirichlet Process (HDP) Delving Deep into Vector Representations The Geometry of Language: Introduction to Vectors in NLP Text Manipulation: Generation and Summarization Playing the creator: Generating Text with Markov Chains Distilling knowledge: Understanding Text Summarization and Key Input Parameters for TextRank Peering into the future: Recent Developments in Text Generation and Summarization Solving real-world problems: Addressing Challenges in Extractive Summarization Riding the Wave of Sentiment Analysis Unveiling emotions: Introduction to Sentiment Analysis Tools Demystifying the Textblob library Preparing the canvas: Understanding Data for Sentiment Analysis Training your own emotion detectors: Building Sentiment Models Optional: Capstone Project Apply the skills learned throughout the course. Define the problem and gather the data. Conduct exploratory data analysis for text data. Carry out preprocessing and feature extraction. Select and train a model. ? Evaluate the model and interpret the results. Bonus Chapter: Generative AI and NLP Introduction to Generative AI and its role in NLP. Overview of Generative Pretrained Transformer (GPT) models. Using GPT models for text generation and completion. Applying GPT models for improving autocomplete features. Use cases of GPT in question answering systems and chatbots. Bonus Chapter: Advanced Applications of NLP with GPT Fine-tuning GPT models for specific NLP tasks. Using GPT for sentiment analysis and text classification. Role of GPT in Named Entity Recognition (NER). Application of GPT in developing advanced chatbots. Ethics and limitations of GPT and generative AI technologies.