328 Computing & Software Development Tools courses in Borehamwood delivered Live Online

Duration 3 Days 18 CPD hours This course is intended for This course is intended for: System administrators and operators who are operating in the AWS Cloud Informational technology workers who want to increase the system operations knowledge. Overview In this course, you will learn to: Recognize the AWS services that support the different phases of Operational Excellence, a WellArchitected Framework pillar. Manage access to AWS resources using AWS Accounts and Organizations and AWS Identity and Access Management (IAM). Maintain an inventory of in-use AWS resources using AWS services such as AWS Systems Manager, AWS CloudTrail, and AWS Config. Develop a resource deployment strategy utilizing metadata tags, Amazon Machine Images, and Control tower to deploy and maintain an AWS cloud environment. Automate resource deployment using AWS services such as AWS CloudFormation and AWS Service Catalog. Use AWS services to manage AWS resources through SysOps lifecycle processes such as deployments and patches. Configure a highly available cloud environment that leverages AWS services such as Amazon Route 53 and Elastic Load Balancing to route traffic for optimal latency and performance. Configure AWS Auto Scaling and Amazon Elastic Compute Cloud auto scaling to scale your cloud environment based on demand. Use Amazon CloudWatch and associated features such as alarms, dashboards, and widgets to monitor your cloud environment. Manage permissions and track activity in your cloud environment using AWS services such as AWS CloudTrail and AWS Config. Deploy your resources to an Amazon Virtual Private Cloud (Amazon VPC), establish necessary connectivity to your Amazon VPC, and protect your resources from disruptions of service. State the purpose, benefits, and appropriate use cases for mountable storage in your AWS cloud environment. Explain the operational characteristics of object storage in the AWS cloud, including Amazon Simple Storage Service (Amazon S3) and Amazon S3 Glacier. Build a comprehensive costing model to help gather, optimize, and predict your cloud costs using services such as AWS Cost Explorer and the AWS Cost & Usage Report. This course teaches systems operators and anyone performing system operations functions how to install, configure, automate, monitor, secure, maintain and troubleshoot the services, networks, and systems on AWS necessary to support business applications. The course also covers specific AWS features, tools, andbest practices related to these functions. Module 1: Introduction to System Operations on AWS Systems operations AWS Well-Architected Framework AWS Well-Architected Tool Module 2a: Access Management Access management Resources, accounts, and AWS Organizations Module 2b: System Discovery Methods to interact with AWS services Introduction to monitoring services Tools for automating resource discovery Inventory with AWS Systems Manager and AWS Config Troubleshooting scenario Hands-On Lab: Auditing AWS Resources with AWS Systems Manager and AWS Config Module 3: Deploying and Updating Resources Systems operations in deployments Tagging strategies Deployment using Amazon Machine Images (AMIs) Deployment using AWS Control Tower Troubleshooting scenario Module 4: Automating Resource Deployment Deployment using AWS CloudFormation Deployment using AWS Service Catalog Troubleshooting scenario Hands-On Lab: Infrastructure as Code Module 5: Manage Resources AWS Systems Manager Troubleshooting scenario Hands-On Lab: Operations as Code Module 6a: Configure Highly Available Systems Distributing traffic with Elastic Load Balancing Amazon Route 53 Module 6b: Automate Scaling Scaling with AWS Auto Scaling Scaling with Spot Instances Managing licenses with AWS License Manager Troubleshooting scenario Module 7: Monitor and Maintaining System Health Monitoring and maintaining healthy workloads Monitoring distributed applications Monitoring AWS infrastructure Monitoring your AWS account Troubleshooting scenario Hands-On Lab: Monitoring Applications and Infrastructure Module 8: Data Security and System Auditing Maintain a strong identity and access foundation Implement detection mechanisms Automate incident remediation Troubleshooting scenario Hands-On Lab: Securing the Environment Module 9: Operate Secure and Resilient Networks Building a secure Amazon Virtual Private Cloud (Amazon VPC) Networking beyond the VPC Troubleshooting scenario Module 10a : Mountable Storage Configuring Amazon Elastic Block Storage (Amazon EBS) Sizing Amazon EBS volumes for performance Using Amazon EBS snapshots Using Amazon Data Lifecycle Manager to manage your AWS resources Creating backup and data recovery plans Configuring shared file system storage Module 10b: Object Storage Deploying Amazon Simple Storage Service (Amazon S3) with Access Logs, Cross-Region Replication, and S3 Intelligent-Tiering Hands-On Lab: Automating with AWS Backup for Archiving and Recovery Module 11: Cost Reporting, Alerts, and Optimization Gain AWS expenditure awareness Use control mechanisms for cost management Optimize your AWS spend and usage Hands-On Lab: Capstone lab for SysOps Additional course details: Nexus Humans Systems Operations on AWS training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Systems Operations on AWS course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 3 Days 18 CPD hours This course is intended for Developers who have some familiarity with serverless and experience with development in the AWS Cloud Overview In this course, you will learn to: Apply event-driven best practices to a serverless application design using appropriate AWS services Identify the challenges and trade-offs of transitioning to serverless development, and make recommendations that suit your development organization and environment Build serverless applications using patterns that connect AWS managed services together, and account for service characteristics, including service quotas, available integrations, invocation model, error handling, and event source payload Compare and contrast available options for writing infrastructure as code, including AWS CloudFormation, AWS Amplify, AWS Serverless Application Model (AWS SAM), and AWS Cloud Development Kit (AWS CDK) Apply best practices to writing Lambda functions inclusive of error handling, logging, environment re-use, using layers, statelessness, idempotency, and configuring concurrency and memory Apply best practices for building observability and monitoring into your serverless application Apply security best practices to serverless applications Identify key scaling considerations in a serverless application, and match each consideration to the methods, tools, or best practices to manage it Use AWS SAM, AWS CDK, and AWS developer tools to configure a CI/CD workflow, and automate deployment of a serverless application Create and actively maintain a list of serverless resources that will assist in your ongoing serverless development and engagement with the serverless community This course gives developers exposure to and practice with best practices for building serverless applications using AWS Lambda and other services in the AWS serverless platform. You will use AWS frameworks to deploy a serverless application in hands-on labs that progress from simpler to more complex topics. You will use AWS documentation throughout the course to develop authentic methods for learning and problem-solving beyond the classroom. Introduction Introduction to the application you will build Access to course resources (Student Guide, Lab Guide, and Online Course Supplement) Thinking Serverless Best practices for building modern serverless applications Event-driven design AWS services that support event-driven serverless applications API-Driven Development and Synchronous Event Sources Characteristics of standard request/response API-based web applications How Amazon API Gateway fits into serverless applications Try-it-out exercise: Set up an HTTP API endpoint integrated with a Lambda function High-level comparison of API types (REST/HTTP, WebSocket, GraphQL) Introduction to Authentication, Authorization, and Access Control Authentication vs. Authorization Options for authenticating to APIs using API Gateway Amazon Cognito in serverless applications Amazon Cognito user pools vs. federated identities Serverless Deployment Frameworks Overview of imperative vs. declarative programming for infrastructure as code Comparison of CloudFormation, AWS CDK, Amplify, and AWS SAM frameworks Features of AWS SAM and the AWS SAM CLI for local emulation and testing Using Amazon EventBridge and Amazon SNS to Decouple Components Development considerations when using asynchronous event sources Features and use cases of Amazon EventBridge Try-it-out exercise: Build a custom EventBridge bus and rule Comparison of use cases for Amazon Simple Notification Service (Amazon SNS) vs. EventBridge Try-it-out exercise: Configure an Amazon SNS topic with filtering Event-Driven Development Using Queues and Streams Development considerations when using polling event sources to trigger Lambda functions Distinctions between queues and streams as event sources for Lambda Selecting appropriate configurations when using Amazon Simple Queue Service (Amazon SQS) or Amazon Kinesis Data Streams as an event source for Lambda Try-it-out exercise: Configure an Amazon SQS queue with a dead-letter queue as a Lambda event source Writing Good Lambda Functions How the Lambda lifecycle influences your function code Best practices for your Lambda functions Configuring a function Function code, versions and aliases Try-it-out exercise: Configure and test a Lambda function Lambda error handling Handling partial failures with queues and streams Step Functions for Orchestration AWS Step Functions in serverless architectures Try-it-out exercise: Step Functions states The callback pattern Standard vs. Express Workflows Step Functions direct integrations Try-it-out exercise: Troubleshooting a Standard Step Functions workflow Observability and Monitoring The three pillars of observability Amazon CloudWatch Logs and Logs Insights Writing effective log files Try-it-out exercise: Interpreting logs Using AWS X-Ray for observability Try-it-out exercise: Enable X-Ray and interpret X-Ray traces CloudWatch metrics and embedded metrics format Try-it-out exercise: Metrics and alarms Try-it-out exercise: ServiceLens Serverless Application Security Security best practices for serverless applications Applying security at all layers API Gateway and application security Lambda and application security Protecting data in your serverless data stores Auditing and traceability Handling Scale in Serverless Applications Scaling considerations for serverless applications Using API Gateway to manage scale Lambda concurrency scaling How different event sources scale with Lambda Automating the Deployment Pipeline The importance of CI/CD in serverless applications Tools in a serverless pipeline AWS SAM features for serverless deployments Best practices for automation Course wrap-up Additional course details: Nexus Humans AWS Developing Serverless Solutions on AWS training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the AWS Developing Serverless Solutions on AWS course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 5 Days 30 CPD hours Additional course details: Nexus Humans 9000 System Manager 2.8 (3-day) 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 9000 System Manager 2.8 (3-day) 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 Additional course details: Nexus Humans 9000 System Manager 2.9 (4-day) 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 9000 System Manager 2.9 (4-day) 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 The target audience for the DevOps Test Engineering course is anyone involved in defining a DevOps Testing strategy, such as: Delivery Staff DevOps Engineers IT Managers Project Managers Lab Staff Maintenance and Support Staff Quality Assurance Managers Quality Assurance Teams Release Managers Testers Software Engineers Overview The learning objectives for DTE include a practical understanding of: The purpose, benefits, concepts and vocabulary of DevOps testing How DevOps testing differs from other types of testing DevOps testing strategies, test management and results analysis Strategies for selecting test tools and implementing test automation Integration of DevOps testing into Continuous Integration and Continuous Delivery workflows How DevOps testers fit with a DevOps culture, organization and roles This comprehensive course addresses testing in a DevOps environment and covers concepts such as the active use of test automation, testing earlier in the development cycle, and instilling testing skills in developers, quality assurance, security, and operational teams. The course is relevant for every modern IT professional involved in defining or deploying a DevOps testing strategy for their organization, as test engineering is the backbone of DevOps and the primary key for successful DevOps pipeline to support digital transformation. This course prepares you for the Continuous Testing Foundation(CTF) certification. Course Objectives and Modules, Logistics What is DevOps Testing and its Business Benefits?Relation of DevOps Testing in other Test MethodologiesDevOps Testing Best Practices DevOps Testing Terminology Culture changes Organization changes Process and team friction Motivation strategies Measuring Success Continuous Evolution Troubleshooting What is the DevOps pipeline? DevOps Testing on the pipeline Test strategy choices Pre-Flight strategies Continuous Integration Testing System, Delivery and Customer Testing Test Environments Lab Management Topology orchestration Test Automation Frameworks Test Tools Selection criterion Automated metrics Key concepts Test Case Best Practices & Design Exercise Test Suite Best Practices & Design Exercise Principles of DevOps Management DevOps Test Management Metrics DevOps Management Tools DevOps Test Results Analysis Integrating DevOps Results Analysis Test Management Exercise Fictitious Product Test Requirements Individual Exercise Class discussion Exam Preparation

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 1 Days 6 CPD hours This course is intended for This introductory-level course is great for experienced technical professionals working in a wide range of industries, such as software development, data science, marketing and advertising, finance, healthcare, and more, who are looking to use the latest AI and machine learning techniques in their day to day. The hands-on labs in this course use Python, so you should have some familiarity with Python scripting basics. Overview Working in an interactive learning environment, led by our engaging OpenAI expert you'll: Understand the capabilities and products offered by OpenAI and how to access them through the OpenAI API. set up an OpenAI environment on Azure, including creating an Azure virtual machine and configuring the environment to connect to Azure resources. Gain hands-on experience building a GPT-3 based chatbot on Azure and implement advanced natural language processing capabilities. Use the OpenAI API to access GPT-3 and generate high-quality text Learn how to use Whisper to improve the quality of text generation. Understand the capabilities of DALL-E and use it to generate images for unique and engaging visuals. Geared for technical professionals, Quick Start to Azure AI Basics for Technical Users is a fun, fast paced course designed to quickly get you up to speed with OpenAI?s powerful tools and functionality, and to provide hands-on experience in setting up an OpenAI environment on Azure. Guided by our AI expert, you?ll explore the capabilities of OpenAI's GPT-3, Whisper and DALL-E, and build a chatbot on Azure. It will provide you with the knowledge and resources to continue your journey in AI and machine learning and have a good understanding of the potential of OpenAI and Azure for your projects. First, you?ll dive into the world of OpenAI, learning about its products and the capabilities they offer. You'll also discover how Azure's offerings for AI and machine learning can complement OpenAI's tools and resources, providing you with a powerful combination for your projects. And don't worry if you're new to Azure, we'll walk you through the process of setting up an account and creating a resource group. As you progress through the course, you'll get the chance to work with OpenAI's GPT-3, one of the most advanced large language models available today. You'll learn how to use the OpenAI API to access GPT-3 and discover how to use it to generate high-quality text quickly and easily. And that's not all, you'll also learn how to build a GPT-3 based chatbot on Azure, giving you the opportunity to implement advanced natural language processing capabilities in your chatbot projects. The course will also cover OpenAI Whisper, an OpenAI tool that can improve the quality of text generation, allowing you to create more coherent and natural language content. And you will learn about OpenAI DALL-E, an OpenAI tool that can generate images, giving you the ability to create unique and engaging visuals to enhance your content and projects. Introduction to OpenAI and Azure Explore OpenAI and its products, as well as Azure's offerings for AI and Machine Learning, allowing you to understand the tools and resources available to you for your AI projects. Explore OpenAI and its products Explore Azure and its offerings for AI and Machine Learning Get Hands-On: Setting up an OpenAI environment on Azure Walk through the process of setting up an OpenAI environment on Azure, giving you the hands-on experience needed to start building your own projects using OpenAI and Azure. Create an Azure virtual machine and installing the OpenAI SDK Configure the OpenAI environment and connecting to Azure resources Explore OpenAI GPT-3 Learn about GPT-3, one of OpenAI's most powerful language models, and how to use it to generate high quality text, giving you the ability to create natural language content quickly and easily. Review GPT-3 and its capabilities Use the OpenAI API to access GPT-3 Get Hands-on: Building a GPT-3 based chatbot on Azure Learn how to build a GPT-3 based chatbot on Azure, giving you the opportunity to learn how to implement advanced natural language processing capabilities in your chatbot projects. Setup an Azure Function and creating a chatbot Integrate GPT-3 with the chatbot OpenAI Whisper Explore Whisper, an OpenAI tool that can improve the quality of text generation, allowing you to create more coherent and natural language content. Explore Whisper and its capabilities Use Whisper to improve the quality of text generation OpenAI DALL-E Explore DALL-E, an OpenAI tool that can generate images, giving you the ability to create unique and engaging visuals to enhance your content and projects. Explore DALL-E and its capabilities Use the OpenAI API to access DALL-E What?s Next: Keep Going! Other ways OpenAI can impact your day to day Explore great places to check for expanded tools and add-ons for Azure OpenAI Where to go for help and support Quick Look at Generative AI and its Business Implications Understanding Generative AI Generative AI in Business Ethical considerations of Generative AI

Duration 0.5 Days 3 CPD hours This course is intended for Individuals and organizations seeking a foundational understanding of DevOps Overview Please refer to Overview This course brings a high-level understanding of DevOps, the cultural and professional movement that stresses communication, collaboration, integration, and automation to improve the flow of work between software developers and IT operations professionals. Course introductionWhat is DevOps? Why Now?Emerging DevOps PracticesCultureAutomationLeanMeasurement and MetricsSharingGetting Started: Implementing DevOpsNext Steps

Duration 3 Days 18 CPD hours This course is intended for This course is designed for IT professionals with baseline skills in computer hardware, software support, and development who want to learn how to design, develop, implement, operate, and manage Internet of Things devices and related systems. It is for those interested in learning more about embedded systems, microcontroller programming, IoT security, and the development life cycle for IoT projects. While students will gain hands-on experience assembling a prototype IoT device and using software development tools, these activities are closely guided, so previous experience in electronics assembly and programming are not required. This course prepares students for taking the CertNexus Certified Internet of Things (IoT) Practitioner (Exam ITP-110). Overview In this course, you will learn how to apply Internet of Things technologies to solve real-world problems. You will: Construct and program an IoT device. Communicate with an IoT device using wired and wireless connections. Process sensor input and control an actuator on an IoT device. Manage security, privacy, and safety risks on IoT projects. Plan an IoT prototyping and development project. In this course, you will learn general strategies for planning, designing, developing, implementing, and maintaining an IoT system through various case studies and by assembling and configuring an IoT device to work in a sensor network. You will create an IoT device based on an ESP8266 microcontroller, implementing various common IoT features, such as analog and digital sensors, a web-based interface, MQTT messaging, and data encryption. The instructor led course includes an exam voucher for the Certified Internet of Things Practitioner (CIoTP) exam (exam ITP-110). Planning an IoT Implementation Select a General Architecture for an IoT Project Identify Benefits and Challenges of IoT Constructing and Programming an IoT Device Select and Configure a Processing Unit Select a Microcontroller Power Source Use a Software Development Kit to Program an IoT Device Communicating with an IoT Device Communicate Using Wired Connections Communicate Using Wireless Connections Communicate Using Internet Protocols Processing IoT Data Process IoT Device Input and Output Process Data in the Cloud Provide Machine to Machine Communication Managing Risks on IoT Projects Identify IoT Security and Privacy Risks Manage IoT Security and Privacy Risks Manage IoT Safety Risks Undertaking an IoT Project Identify Real World Applications for IoT Follow the IoT Development Lifecycle Additional course details: Nexus Humans CertNexus Certified Internet of Things Practitioner (CIoTP) 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 CertNexus Certified Internet of Things Practitioner (CIoTP) 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 Security Professionals working with Kubernetes Clusters Container Orchestration Engineers DevOps Professionals Overview In this course, students will learn and practice essential Kubernetes concepts and tasks in the following sections: Cloud Security Fundamentals Cluster Hardening System Hardening Minimize Microservice Vulnerabilities Supply Chain Security Disaster Recovery Secure Back-up and Restore This class prepares students for the Certified Kubernetes Security Specialist (CKS) exam. Kubernetes is a Cloud Orchestration Platform providing reliability, replication, and stabilitywhile maximizing resource utilization for applications and services. By the conclusion of this hands-on, vendor agnostic training you will be equipped with a thorough understanding ofcloud security fundamentals, along with the knowledge, skills and abilities to secure a Kubernetes cluster, detect threats, and properly resolve a security catastrophe. This courseincludes hands-on instruction which develops skills and knowledge for securing container-based applications and Kubernetes platforms, during build, deployment, and runtime. We prioritizecovering all objectives and concepts necessary for passing the Certified Kubernetes Security Specialist (CKS) exam. You will be provided the components necessary to assemble your ownhigh availability Kubernetes environment and harden it for your security needs. Learning Your Environment Underlying Infrastructure Using Vim Tmux Cloud Security Primer Basic Principles Threat Analysis Approach CIS Benchmarks Securing your Kubernetes Cluster Kubernetes Architecture Pods and the Control Plane Kubernetes Security Concepts Install Kubernetes using kubeadm Configure Network Plugin Requirements Kubeadm Basic Cluster Installing Kubeadm Join Node to Cluster Kubeadm Token Manage Kubeadm Tokens Kubeadm Cluster Upgrade Securing the kube-apiserver Configuring the kube-apiserver Enable Audit Logging Falco Deploy Falco to Monitor System Calls Enable Pod Security Policies Encrypt Data at Rest Encryption Configuration Benchmark Cluster with Kube-Bench Kube-Bench Securing ETCD ETCD Isolation ETCD Disaster Recovery ETCD Snapshot and Restore Purge Kubernetes Purge Kubeadm 3Purge Kubeadm Image Scanning Container Essentials Secure Containers Creating a Docker Image Scanning with Trivy Trivy Snyk Security Manually Installing Kubernetes Kubernetes the Alta3 Way Deploy Kubernetes the Alta3 Way Validate your Kubernetes Installation Sonobuoy K8s Validation Test Kubectl (Optional) Kubectl get and sorting kubectl get kubectl describe Labels (Optional) Labels Labels and Selectors Annotations Insert an Annotation Securing your Application Scan a Running Container Tracee Security Contexts for Pods Understanding Security Contexts AppArmor Profiles AppArmor Isolate Container Kernels gVisor Pod Security Pod Security Policies Deploy a PSP Pod Security Standards Enable PSS Open Policy Agent (OPA) Admission Controller Create a LimitRange Open Policy Agent Policy as Code Deploy Gatekeeper User Administration Contexts Contexts Authentication and Authorization Role Based Access Control Role Based Access Control RBAC Distributing Access Service Accounts Limit Pod Service Accounts Securing Secrets Secrets Create and Consume Secrets Hashicorp Vault Deploy Vault Securing the Network Networking Plugins NetworkPolicy Deploy a NetworkPolicy mTLS Linkerd mTLS with istio istio Threat Detection Active Threat Analysis Host Intrusion Detection Deploy OSSEC Network Intrusion Detection Deploy Suricata Physical Intrusion Detection Disaster Recovery Harsh Reality of Security Deploy a Response Plan Kasten K10 Backups Deploy K10