158 Google courses in Potters Bar delivered Live Online

Duration 1 Days 6 CPD hours This course is intended for This course is intended for the following participants: Individuals planning to deploy applications and create application environments on Google Cloud Platform Developers, systems operations professionals, and solution architects getting started with Google Cloud Platform Executives and business decision makers evaluating the potential of Google Cloud Platform to address their business needs. Overview This course teaches participants the following skills: Identify Google Cloud counterparts for Azure IaaS, Azure PaaS, Azure SQL, Azure Blob Storage, Azure Application Insights, and Azure Data Lake Configure accounts, billing, projects, networks, subnets, firewalls, VMs, disks, auto scaling, load balancing,storage, databases, IAM, and more Manage and monitor applications Explain feature and pricing model differences This 1-day instructor led course introduces Azure professionals to the core capabilities of Google Cloud in the four technology pillars: networking, compute, storage, and database. It is designed for Azure system administrators, Solution Architects and SysOps Administrators familiar with Azure features and setup; and want to gain experience configuring Google Cloud products immediately. With presentations, demos, and hands-on labs, participants get details of similarities, differences, and initial how-tos quickly. Introducing Google Cloud Explain the advantages of Google Cloud. Define the components of Google's network infrastructure, including: Points of presence, data centers, regions, and zones. Understand the difference between Infrastructure-as-a-Service (IaaS) and Platform-as-a-Service (PaaS). Getting Started with Google Cloud Identify the purpose of projects on Google Cloud. Understand how Azure's resource hierarchy differs from Google Cloud's Understand the purpose of and use cases for Identity and Access Management. Understand how Azure AD differs from Google Cloud IAM. List the methods of interacting with Google Cloud. Launch a solution using Cloud Marketplace. Virtual Machines in the Cloud Identify the purpose and use cases for Google Compute Engine Understand the basics of networking in Google Cloud. Understand how Azure VPC differs from Google VPC. Understand the similarities and differences between Azure VM and Google Compute Engine. Understand how typical approaches to load-balancing in Google Cloud differ from those in Azure. Deploy applications using Google Compute Engine Storage in the Cloud Understand the purpose of and use cases for: Cloud Storage, Cloud SQL, Cloud Bigtable and Cloud Datastore. Understand how Azure Blob compares to Cloud Storage. Compare Google Cloud?s managed database services with Azure SQL. Learn how to choose among the various storage options on Google Cloud. Load data from Cloud Storage into BigQuery Containers in the Cloud Define the concept of a container and identify uses for containers. Identify the purpose of and use cases for Google Container Engine and Kubernetes. Understand how Azure Kubernetes Service differs from from Google Kubernetes Engine. Provision a Kubernetes cluster using Kubernetes Engine. Deploy and manage Docker containers using kubectl Applications in the Cloud Understand the purpose of and use cases for Google App Engine. Contrast the App Engine Standard environment with the App Engine Flexible environment. Understand how App Engine differs from Azure App Service. Understand the purpose of and use cases for Google Cloud Endpoints. Developing, Deploying and Monitoring in the Cloud Understand options for software developers to host their source code. Understand the purpose of template-based creation and management of resources. Understand how Google Cloud Deployment Manager differs from Azure Resource Manager. Understand the purpose of integrated monitoring, alerting, and debugging Understand how Google Monitoring differs from Azure Application Insights and Azure Log Analytics. Create a Deployment Manager deployment. Update a Deployment Manager deployment. View the load on a VM instance using Google Monitoring. Big Data and Machine Learning in the Cloud Understand the purpose of and use cases for the products and services in the Google Cloud big data and machine learning platforms. Understand how Google Cloud BigQuery differs from Azure Data Lake. Understand how Google Cloud Pub/Sub differs from Azure Event Hubs and Service Bus. Understand how Google Cloud?s machine-learning APIs differ from Azure's. Load data into BigQuery from Cloud Storage. Perform queries using BigQuery to gain insight into data Summary and Review Review the products that make up Google Cloud and remember how to choose among them Understand next steps for training and certification Understand, at a high level, the process of migrating from Azure to Google Cloud.

Duration 3 Days 18 CPD hours This course is intended for Application developers who want to build cloud-native applications or redesign existing applications that will run on Google Cloud Platform Overview This course teaches participants the following skills: Use best practices for application development. Choose the appropriate data storage option for application data. Implement federated identity management. Develop loosely coupled application components or microservices. Integrate application components and data sources. Debug, trace, and monitor applications. Perform repeatable deployments with containers and deployment services. Choose the appropriate application runtime environment; use Google Container Engine as a runtime environment and later switch to a no-ops solution with Google App Engine flexible environment. Learn how to design, develop, and deploy applications that seamlessly integrate components from the Google Cloud ecosystem. This course uses lectures, demos, and hands-on labs to show you how to use Google Cloud services and pre-trained machine learning APIs to build secure, scalable, and intelligent cloud-native applications. Best Practices for Application Development Code and environment management. Design and development of secure, scalable, reliable, loosely coupled application components and microservices. Continuous integration and delivery. Re-architecting applications for the cloud. Google Cloud Client Libraries, Google Cloud SDK, and Google Firebase SDK How to set up and use Google Cloud Client Libraries, Google Cloud SDK, and Google Firebase SDK. Lab: Set up Google Client Libraries, Cloud SDK, and Firebase SDK on a Linux instance and set up application credentials. Overview of Data Storage Options Overview of options to store application data. Use cases for Google Cloud Storage, Cloud Firestore, Cloud Bigtable, Google Cloud SQL, and Cloud Spanner. Best Practices for Using Cloud Firestore Best practices related to using Cloud Firestore in Datastore mode for:Queries, Built-in and composite indexes, Inserting and deleting data (batch operations),Transactions,Error handling. Bulk-loading data into Cloud Firestore by using Google Cloud Dataflow. Lab: Store application data in Cloud Datastore. Performing Operations on Cloud Storage Operations that can be performed on buckets and objects. Consistency model. Error handling. Best Practices for Using Cloud Storage Naming buckets for static websites and other uses. Naming objects (from an access distribution perspective). Performance considerations. Setting up and debugging a CORS configuration on a bucket. Lab: Store files in Cloud Storage. Handling Authentication and Authorization Cloud Identity and Access Management (IAM) roles and service accounts. User authentication by using Firebase Authentication. User authentication and authorization by using Cloud Identity-Aware Proxy. Lab: Authenticate users by using Firebase Authentication. Using Pub/Sub to Integrate Components of Your Application Topics, publishers, and subscribers. Pull and push subscriptions. Use cases for Cloud Pub/Sub. Lab: Develop a backend service to process messages in a message queue. Adding Intelligence to Your Application Overview of pre-trained machine learning APIs such as Cloud Vision API and Cloud Natural Language Processing API. Using Cloud Functions for Event-Driven Processing Key concepts such as triggers, background functions, HTTP functions. Use cases. Developing and deploying functions. Logging, error reporting, and monitoring. Managing APIs with Cloud Endpoints Open API deployment configuration. Lab: Deploy an API for your application. Deploying Applications Creating and storing container images. Repeatable deployments with deployment configuration and templates. Lab: Use Deployment Manager to deploy a web application into Google App Engine flexible environment test and production environments. Execution Environments for Your Application Considerations for choosing an execution environment for your application or service:Google Compute Engine (GCE),Google Kubernetes Engine (GKE), App Engine flexible environment, Cloud Functions, Cloud Dataflow, Cloud Run. Lab: Deploying your application on App Engine flexible environment. Debugging, Monitoring, and Tuning Performance Application Performance Management Tools. Stackdriver Debugger. Stackdriver Error Reporting. Lab: Debugging an application error by using Stackdriver Debugger and Error Reporting. Stackdriver Logging. Key concepts related to Stackdriver Trace and Stackdriver Monitoring. Lab: Use Stackdriver Monitoring and Stackdriver Trace to trace a request across services, observe, and optimize performance.

Duration 3 Days 18 CPD hours This course is intended for This class is intended for the following job roles: [Cloud] information security analysts, architects, and engineers Information security/cybersecurity specialists Cloud infrastructure architects Additionally, the course is intended for Google and partner field personnel who work with customers in those job roles. The course should also be useful to developers of cloud applications Overview This course teaches participants the following skills: Understanding the Google approach to security Managing administrative identities using Cloud Identity. Implementing least privilege administrative access using Google Cloud Resource Manager, Cloud IAM. Implementing IP traffic controls using VPC firewalls and Cloud Armor Implementing Identity Aware Proxy Analyzing changes to the configuration or metadata of resources with GCP audit logs Scanning for and redact sensitive data with the Data Loss Prevention API Scanning a GCP deployment with Forseti Remediating important types of vulnerabilities, especially in public access to data and VMs This course gives participants broad study of security controls and techniques on Google Cloud Platform. Through lectures, demonstrations, and hands-on labs, participants explore and deploy the components of a secure Google Cloud solution. Participants also learn mitigation techniques for attacks at many points in a Google Cloud-based infrastructure, including Distributed Denial-of-Service attacks, phishing attacks, and threats involving content classification and use. Foundations of GCP Security Google Cloud's approach to security The shared security responsibility model Threats mitigated by Google and by GCP Access Transparency Cloud Identity Cloud Identity Syncing with Microsoft Active Directory Choosing between Google authentication and SAML-based SSO GCP best practices Identity and Access Management GCP Resource Manager: projects, folders, and organizations GCP IAM roles, including custom roles GCP IAM policies, including organization policies GCP IAM best practices Configuring Google Virtual Private Cloud for Isolation and Security Configuring VPC firewalls (both ingress and egress rules) Load balancing and SSL policies Private Google API access SSL proxy use Best practices for structuring VPC networks Best security practices for VPNs Security considerations for interconnect and peering options Available security products from partners Monitoring, Logging, Auditing, and Scanning Stackdriver monitoring and logging VPC flow logs Cloud audit logging Deploying and Using Forseti Securing Compute Engine: techniques and best practices Compute Engine service accounts, default and customer-defined IAM roles for VMs API scopes for VMs Managing SSH keys for Linux VMs Managing RDP logins for Windows VMs Organization policy controls: trusted images, public IP address, disabling serial port Encrypting VM images with customer-managed encryption keys and with customer-supplied encryption keys Finding and remediating public access to VMs VM best practices Encrypting VM disks with customer-supplied encryption keys Securing cloud data: techniques and best practices Cloud Storage and IAM permissions Cloud Storage and ACLs Auditing cloud data, including finding and remediating publicly accessible data Signed Cloud Storage URLs Signed policy documents Encrypting Cloud Storage objects with customer-managed encryption keys and with customer-supplied encryption keys Best practices, including deleting archived versions of objects after key rotation BigQuery authorized views BigQuery IAM roles Best practices, including preferring IAM permissions over ACLs Protecting against Distributed Denial of Service Attacks: techniques and best practices How DDoS attacks work Mitigations: GCLB, Cloud CDN, autoscaling, VPC ingress and egress firewalls, Cloud Armor Types of complementary partner products Application Security: techniques and best practices Types of application security vulnerabilities DoS protections in App Engine and Cloud Functions Cloud Security Scanner Threat: Identity and Oauth phishing Identity Aware Proxy Content-related vulnerabilities: techniques and best practices Threat: Ransomware Mitigations: Backups, IAM, Data Loss Prevention API Threats: Data misuse, privacy violations, sensitive/restricted/unacceptable content Mitigations: Classifying content using Cloud ML APIs; scanning and redacting data using Data Loss Prevention API Additional course details: Nexus Humans Security in Google Cloud 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 Security in Google Cloud 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 1 Days 6 CPD hours This course is intended for This class is intended for the following: Data analysts, Data scientists, Business analysts getting started with Google Cloud Platform. Individuals responsible for designing pipelines and architectures for data processing, creating and maintaining machine learning and statistical models, querying datasets, visualizing query results and creating reports. Executives and IT decision makers evaluating Google Cloud Platform for use by data scientists. Overview This course teaches students the following skills:Identify the purpose and value of the key Big Data and Machine Learning products in the Google Cloud Platform.Use Cloud SQL and Cloud Dataproc to migrate existing MySQL and Hadoop/Pig/Spark/Hive workloads to Google Cloud Platform.Employ BigQuery and Cloud Datalab to carry out interactive data analysis.Train and use a neural network using TensorFlow.Employ ML APIs.Choose between different data processing products on the Google Cloud Platform. This course introduces participants to the Big Data and Machine Learning capabilities of Google Cloud Platform (GCP). It provides a quick overview of the Google Cloud Platform and a deeper dive of the data processing capabilities. Introducing Google Cloud Platform Google Platform Fundamentals Overview. Google Cloud Platform Big Data Products. Compute and Storage Fundamentals CPUs on demand (Compute Engine). A global filesystem (Cloud Storage). CloudShell. Lab: Set up a Ingest-Transform-Publish data processing pipeline. Data Analytics on the Cloud Stepping-stones to the cloud. Cloud SQL: your SQL database on the cloud. Lab: Importing data into CloudSQL and running queries. Spark on Dataproc. Lab: Machine Learning Recommendations with Spark on Dataproc. Scaling Data Analysis Fast random access. Datalab. BigQuery. Lab: Build machine learning dataset. Machine Learning Machine Learning with TensorFlow. Lab: Carry out ML with TensorFlow Pre-built models for common needs. Lab: Employ ML APIs. Data Processing Architectures Message-oriented architectures with Pub/Sub. Creating pipelines with Dataflow. Reference architecture for real-time and batch data processing. Summary Why GCP? Where to go from here Additional Resources Additional course details: Nexus Humans Google Cloud Platform Big Data and Machine Learning Fundamentals 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 Google Cloud Platform Big Data and Machine Learning Fundamentals 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 1 Days 6 CPD hours This course is intended for This course is intended for the following participants: Application developers, Cloud Solutions Architects, 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 At the end of the course, students will be able to: Understand container basics. Containerize an existing application. Understand Kubernetes concepts and principles. Deploy applications to Kubernetes using the CLI. Set up a continuous delivery pipeline using Jenkins Learn to containerize workloads in Docker containers, deploy them to Kubernetes clusters provided by Google Kubernetes Engine, and scale those workloads to handle increased traffic. Students will also learn how to continuously deploy new code in a Kubernetes cluster to provide application updates. Introduction to Containers and Docker Acquaint yourself with containers, Docker, and the Google Container Registry. Create a container. Package a container using Docker. Store a container image in Google Container Registry. Launch a Docker container. Kubernetes Basics Deploy an application with microservices in a Kubernetes cluster. Provision a complete Kubernetes cluster using Kubernetes Engine. Deploy and manage Docker containers using kubectl. Break an application into microservices using Kubernetes? Deployments and Services. Deploying to Kubernetes Create and manage Kubernetes deployments. Create a Kubernetes deployment. Trigger, pause, resume, and rollback updates. Understand and build canary deployments. Continuous Deployment with Jenkins Build a continuous delivery pipeline. Provision Jenkins in your Kubernetes cluster. Create a Jenkins pipeline. Implement a canary deployment using Jenkins. Additional course details: Nexus Humans Getting Started with Google Kubernetes Engine 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 Getting Started with Google Kubernetes Engine 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 Cloud Solutions Architects  DevOps Engineers  Individuals using Google Cloud Platform who deploy applications, monitor operations, and manage enterprise solutions Overview At course completion, you will have attained knowledge of: Fundamentals of Google Cloud Platform (GCP) Google Cloud Storage Google Compute Engine Google Cloud SQL Load Balancing (LB) Google Cloud Monitoring Auto-Scaling Virtual Private Cloud (VPC) Network Cloud Identity and Access Management (IAM) Cloud CDN and DNS Cloud VPN Google Cloud Deployment Manager Google Container Engine Cloud Run Cloud Bigtable Cloud Datastore Cloud BigQuery Cloud DataFlow Cloud DataProc Cloud Pub/Sub In this course you will attain a deep knowledge of Google Cloud Platform infrastructure and design patterns on developing applications on GCP. This course will prepare you for the Google Cloud Architect Associate Certification Exam. Fundamentals of Google Cloud Platform (GCP) Overview Regions and Zones Review of major GCP services Google Cloud Storage Fundamental APIs Consistency Cloud Storage Namespace Buckets and Objects Bucket and Object Naming Guidelines Encryption Object Versioning Object Lifecycle Management Access Control Access Control Lists Signed URL Multipart upload Resumable upload Understanding Pricing for Cloud Storage Offline Media Import/Export Architecture case study of common Use Cases of Google Cloud Storage Hands-on: Cloud Storage Lab; Creating Buckets, objects, and managing access control Google Compute Engine Compute Engine Architecture VM Instances types Persistence Disks Images Generating Custom Images IP Addresses Static IPs Ephemeral Access Control Options IAM Service Account Monitoring Instances with Google Cloud Monitoring Compute Engine Networks and Firewalls Hands-on: Hosting an Application on Compute Engine Google Cloud SQL Core advantages of Cloud SQL Cloud SQL database instance types Access Control High availability options Failover Read replica Backup options On Demand Automated Understanding Pricing of Cloud SQL Load Balancing (LB) Fundamentals of a Load Balancer Network Load balancing HTTPS Load balancing Cross region Load balancing Content Load balancing Target proxies SSL Load Balancing Internal Load Balancing Network Load Balancing Understanding Pricing for Load Balancer Google Cloud Monitoring Architecture of Cloud Monitoring Supported metrics Stackdriver Monitoring APIs Auto-Scaling Overview of Autoscaling Auto-scaling Fundamentals Instance groups Templates Policies Decisions Hands-on: Deploying a scale application on GCP using Autoscaling, Compute Engine, Cloud SQL, Load Balancers. Virtual Private Cloud (VPC) Network Salient features of Virtual Private Cloud (VPC) Network Infrastructure Virtual Private Cloud (VPC) Networking Fundamentals Subnetworks Firewall Internal DNS Network Routes Hands-on: Hosting Secure Applications in Google Cloud VPC Networks Cloud Identity and Access Management (IAM) Introduction User and Service Accounts IAM Roles Policy Hands-on: Managing Users, Policies and Granting Roles using Service Accounts Cloud CDN and DNS What is CDN Google Cloud CDN Cloud CDN Concepts Some of the Cloud CDN Edge locations Cloud DNS Cloud DNS Terminologies Supported Record Types Hands-on: Moving an Existing Domain Name to Cloud DNS Cloud VPN Cloud VPN overview Types of Cloud VPN Specifications Maintenance and Availability Google Cloud Deployment Manager Deployment Manager Deployment Manager Fundamentals Runtime Configurator Quotas Hands-on: Generating and Creating Cloud Deployment Manager Template Google Container Engine Google Container Engine Overview Docker Overview Kubernetes Terminologies Replication Controller Deployment Price and Quotas Hands-on: Deploying WordPress Cluster using Container Engine Cloud Run Overview of Cloud Run Deploy a Prebuilt Sample container Cloud Bigtable Overview of Cloud Bigtable Access Control Performance Locations Cloud Datastore Overview of Cloud Datastore Limits Storage Size Multitenancy Benefits of Multitenancy Encryption Locations Cloud BigQuery BigQuery Overview Interacting with BigQuery Datasets, Tables, and Views Partitioned Tables Query Plan Explanation Hands-on: Getting Started with BigQuery Cloud DataFlow Overview Programming Model DataFlow SDK 1.x for java Cloud Dataflow SDK 2.x Security and Permissions Advanced Access Control Cloud DataProc Overview Clusters Versioning Cloud Pub/Sub Overview of Cloud Pub/Sub Pub/Sub Concepts and Message Flow Data Model Cleanup of All Services Hands-on: Cloud Pub/Sub Lab with Background Cloud Function Additional course details: Nexus Humans Google Cloud Engineer Associate Certification Bootcamp 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 Google Cloud Engineer Associate Certification Bootcamp 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 1 Days 6 CPD hours This course is intended for Software developers, system administrators, and IT professionals who are focused on Microsoft Windows Overview Configuring Microsoft Windows and Microsoft SQL Server in Google Compute Engine. Deploying ASP.NET MVC applications to Google Compute Engine. Deploying .NET Core applications to Google Compute Engine, Google Compute Engine, and Google Container Engine Learn how to create Windows virtual machines on Google Cloud so that you can deploy and run Microsoft Windows applications. In this course, you'll learn how to run SQL Server in Compute Engine, how to deploy instances across Google Cloud zones, and how to get more out of ASP.NET on Compute Engine, Google Container Engine, and App Engine. Introduction to Google Cloud Platform Scope and structure of GCP. Options for Windows deployment on GCP. GCP interfaces. Windows Workloads on Google Compute Engine Google Compute Engine virtual machine options. Integrating Active Directory with Google Compute Engine virtual machines. Options for running SQL Server in Google Compute Engine. Configuring SQL Server for high availability. Developing ASP.NET MVC applications Model-view-controller structure. Using Microsoft Visual Studio?s Web Project template to develop in ASP.NET. Deploying applications to Microsoft Internet Information Server (IIS) in GCE. Configuring Resilient Workloads Deploying instances across GCP zones. Using instance groups to create pools of virtual machines. Load balancing Windows applications. Delivering Next-Generation ASP.NET Core on GCP Understanding .NET Core and EF Core. Options for deploying ASP.NET Core applications on Google Cloud Platform. Deploying ASP.NET Core applications on Google Compute Engine. Deploying ASP.NET Core applications on Google Container Engine. Deploying ASP.NET Core applications on Google App Engine. Additional course details: Nexus Humans Develop and Deploy Windows Applications on Google Cloud Platform 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 Develop and Deploy Windows Applications on Google Cloud Platform 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 class is intended for the following customer job roles: Cloud architects, administrators, and SysOps personnel Cloud developers and DevOps personnel Overview This course teaches participants the following skills: Plan and implement a well-architected logging and monitoring infrastructure Define Service Level Indicators (SLIs) and Service Level Objectives (SLOs) Create effective monitoring dashboards and alerts Monitor, troubleshoot, and improve Google Cloud infrastructure Analyze and export Google Cloud audit logs Find production code defects, identify bottlenecks, and improve performance Optimize monitoring costs This course teaches you techniques for monitoring, troubleshooting, and improving infrastructure and application performance in Google Cloud. Guided by the principles of Site Reliability Engineering (SRE), and using a combination of presentations, demos, hands-on labs, and real-world case studies, attendees gain experience with full-stack monitoring, real-time log management and analysis, debugging code in production, tracing application performance bottlenecks, and profiling CPU and memory usage. Introduction to Google Cloud Monitoring Tools Understand the purpose and capabilities of Google Cloud operations-focused components: Logging, Monitoring, Error Reporting, and Service Monitoring Understand the purpose and capabilities of Google Cloud application performance management focused components: Debugger, Trace, and Profiler Avoiding Customer Pain Construct a monitoring base on the four golden signals: latency, traffic, errors, and saturation Measure customer pain with SLIs Define critical performance measures Create and use SLOs and SLAs Achieve developer and operation harmony with error budgets Alerting Policies Develop alerting strategies Define alerting policies Add notification channels Identify types of alerts and common uses for each Construct and alert on resource groups Manage alerting policies programmatically Monitoring Critical Systems Choose best practice monitoring project architectures Differentiate Cloud IAM roles for monitoring Use the default dashboards appropriately Build custom dashboards to show resource consumption and application load Define uptime checks to track aliveness and latency Configuring Google Cloud Services for Observability Integrate logging and monitoring agents into Compute Engine VMs and images Enable and utilize Kubernetes Monitoring Extend and clarify Kubernetes monitoring with Prometheus Expose custom metrics through code, and with the help of OpenCensus Advanced Logging and Analysis Identify and choose among resource tagging approaches Define log sinks (inclusion filters) and exclusion filters Create metrics based on logs Define custom metrics Link application errors to Logging using Error Reporting Export logs to BigQuery Monitoring Network Security and Audit Logs Collect and analyze VPC Flow logs and Firewall Rules logs Enable and monitor Packet Mirroring Explain the capabilities of Network Intelligence Center Use Admin Activity audit logs to track changes to the configuration or metadata of resources Use Data Access audit logs to track accesses or changes to user-provided resource data Use System Event audit logs to track GCP administrative actions Managing Incidents Define incident management roles and communication channels Mitigate incident impact Troubleshoot root causes Resolve incidents Document incidents in a post-mortem process Investigating Application Performance Issues Debug production code to correct code defects Trace latency through layers of service interaction to eliminate performance bottlenecks Profile and identify resource-intensive functions in an application Optimizing the Costs of Monitoring Analyze resource utilization cust for monitoring related components within Google Cloud Implement best practices for controlling the cost of monitoring within Google Cloud

Duration 1 Days 6 CPD hours This course is intended for Business decision-makers: directors (managers of managers), managers of individual contributors (ICs) or ICs working in non-IT functions/divisions (such as finance, marketing, sales, HR, product design) interested in understanding the applications of Google?s cloud technology for business improvement opportunities and transformational project(s). Through this interactive training, you?ll learn about core cloud business drivers?specifically Google?s cloud?and gain the knowledge/skills to determine if business transformation is right for you and your team, and build short and long-term projects using the ?superpowers? of cloud accordingly. You?ll also find several templates, guides, and resource links through the supplementary student workbook to help you build a custom briefing document to share with your leadership, technical teams or partners. Why cloud technology is revolutionizing business This module introduces cloud technology as a paradigm shift and explains how it?s irrevocably transforming business globally. It defines the fundamental building blocks of cloud technology?compute power and data?and what they mean for you and your business. And finally, it reveals how these building blocks help to create five superpowers using concrete use cases of their transformative abilities for business, education, and government sectors. Foster an innovation culture Cloud is not just about a technological transformation; it's a business and cultural transformation, too. This module explores how the superpowers of the cloud are brought to life through people. It looks specifically at how to organically create and scale innovation through culture and business practices. It offers key principles, drawing examples from Google?s success and real world scenarios, that you can apply in your day-to-day operations. Define the ideal business transformation challenge Previous modules describe the journey with cloud technology to include business and cultural changes as well. This module sets the groundwork to build a transformational solution using cloud technology for your role or your business. This process starts with distinguishing between scaled improvements and transformations. Next, the module demonstrates how to write an ideal challenge question and use insights generated from a data ecosystem to address the challenge. Finally, it introduces a framework that you can use to assess and refine your challenge ideas, preparing you to build a business case in a later module. Build trust with availability, security, and compliance This module addresses common concerns about data privacy and security when migrating to the cloud. It defines key terms - privacy, security, compliance, and reliability - and reveals today?s top cybersecurity challenges and threats. It discusses how data security and compliance can be maintained when data is in the cloud, as illustrated by the Shared Responsibility Model. And finally, it uses a concrete example to explain how learners can build a high-level security program in their own organization. Build a business case for your transformation challenge This module explains how to identify the most transformative solution for your business challenge. It then breaks down steps to achieve the transformational solution through creating smaller projects and plotting them onto a transformation roadmap. It describes how to use the data ecosystem you mapped in a previous module to support your overall project. Finally, it explains step by step how to build a business case and gives tips to help you pitch your project idea to gain buy-in from leadership, teams, and technical partners. Additional course details: Nexus Humans Business Transformation with Google Cloud 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 Business Transformation with Google Cloud 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.