Cloud Computing Training in New York

This instructor-led, live training in New York (online or onsite) is aimed at beginner-level data engineers who wish to use Azure Data Factory to implement scalable and efficient data integration solutions in the cloud.

By the end of this training, participants will be able to:

• Understand the core concepts and architecture of Azure Data Factory (ADF).
• Learn to create, schedule, and monitor data pipelines.
• Integrate with various data sources, perform data transformation, and manage data flows.
• Implement best practices for error handling and performance optimization.
• Secure and monitor data pipelines for production environments.

This instructor-led, live training in New York (online or onsite) is aimed at intermediate-level IT professionals who wish to gain expertise in managing cloud infrastructure and services on Google Cloud.

By the end of this training, participants will be able to:

• Set up and configure cloud environments using Google Cloud services.
• Manage and configure virtual machines, storage, and networking.
• Deploy and monitor applications in GCP environments.
• Implement security best practices and identity management.
• Use Google Cloud tools for automation and troubleshooting.

Google Colab Pro is a cloud-based environment for scalable Python development, offering high-performance GPUs, longer runtimes, and more memory for demanding AI and data science workloads.

This instructor-led, live training (online or onsite) is aimed at intermediate-level Python users who wish to use Google Colab Pro for machine learning, data processing, and collaborative research in a powerful notebook interface.

By the end of this training, participants will be able to:

• Set up and manage cloud-based Python notebooks using Colab Pro.
• Access GPUs and TPUs for accelerated computation.
• Streamline machine learning workflows using popular libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
• Integrate with Google Drive and external data sources for collaborative projects.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

This instructor-led, live training in New York (online or onsite) is aimed at intermediate-level data scientists and healthcare professionals who wish to leverage AI for advanced healthcare applications using Google Colab.

By the end of this training, participants will be able to:

• Implement AI models for healthcare using Google Colab.
• Use AI for predictive modeling in healthcare data.
• Analyze medical images with AI-driven techniques.
• Explore ethical considerations in AI-based healthcare solutions.

This instructor-led, live training in New York (online or onsite) is aimed at intermediate-level data scientists and engineers who wish to use Google Colab and Apache Spark for big data processing and analytics.

By the end of this training, participants will be able to:

• Set up a big data environment using Google Colab and Spark.
• Process and analyze large datasets efficiently with Apache Spark.
• Visualize big data in a collaborative environment.
• Integrate Apache Spark with cloud-based tools.

This instructor-led, live training in New York (online or onsite) is aimed at beginner-level system administrators who wish to learn essential concepts and practical skills required for effective management and optimization of Nutanix environments.

By the end of this training, participants will be able to:

• Understand Nutanix Enterprise Cloud Platform and its components.
• Install, configure, and manage Nutanix Clusters.
• Gain proficiency in administering the Acropolis Hypervisor (AHV).
• Perform advanced management tasks and troubleshooting.
• Implement best practices for high availability, disaster recovery, and security.

This instructor-led, live training in New York (online or onsite) is aimed at intermediate-level data professionals who wish to apply time series forecasting techniques to real-world data using Google Colab.

By the end of this training, participants will be able to:

• Understand the fundamentals of time series analysis.
• Use Google Colab to work with time series data.
• Apply ARIMA models to forecast data trends.
• Utilize Facebook’s Prophet library for flexible forecasting.
• Visualize time series data and forecasting results.

This instructor-led, live training in New York (online or onsite) is aimed at beginner-level IT professionals who wish to manage and operate the Google Cloud Platform.

By the end of this training, participants will be able to:

• Understand the core services and infrastructure of GCP.
• Learn how to manage networks and virtual machines.
• Understand and apply general security best practices in GCP.
• Explore Kubernetes and container management in GCP.
• Learn about storage options and how to configure them.
• Deploy and configure databases on GCP.

This instructor-led, live training in New York (online or onsite) is aimed at advanced-level professionals who wish to deepen their understanding of reinforcement learning and its practical applications in AI development using Google Colab.

By the end of this training, participants will be able to:

• Understand the core concepts of reinforcement learning algorithms.
• Implement reinforcement learning models using TensorFlow and OpenAI Gym.
• Develop intelligent agents that learn through trial and error.
• Optimize agents' performance using advanced techniques such as Q-learning and deep Q-networks (DQNs).
• Train agents in simulated environments using OpenAI Gym.
• Deploy reinforcement learning models for real-world applications.

This instructor-led, live training in New York (online or onsite) is aimed at advanced-level professionals who wish to deepen their understanding of computer vision and explore TensorFlow's capabilities for developing sophisticated vision models using Google Colab.

By the end of this training, participants will be able to:

• Build and train convolutional neural networks (CNNs) using TensorFlow.
• Leverage Google Colab for scalable and efficient cloud-based model development.
• Implement image preprocessing techniques for computer vision tasks.
• Deploy computer vision models for real-world applications.
• Use transfer learning to enhance the performance of CNN models.
• Visualize and interpret the results of image classification models.

This instructor-led, live training in New York (online or onsite) is aimed at advanced-level professionals who wish to enhance their knowledge of machine learning models, improve their skills in hyperparameter tuning, and learn how to deploy models effectively using Google Colab.

By the end of this training, participants will be able to:

• Implement advanced machine learning models using popular frameworks like Scikit-learn and TensorFlow.
• Optimize model performance through hyperparameter tuning.
• Deploy machine learning models in real-world applications using Google Colab.
• Collaborate and manage large-scale machine learning projects in Google Colab.

Cloud Computing is a scalable, flexible model for delivering IT resources and services on demand.

This instructor-led, live training (online or onsite) is aimed at beginner-level to advanced-level cloud practitioners who wish to master AWS and Azure technologies while preparing for globally recognized certifications.

Upon completion of this program, participants will be equipped to:

• Understand foundational cloud principles across AWS and Azure.
• Configure, secure, and manage Azure resources effectively.
• Implement AWS compute, storage, networking, and security services.
• Apply architectural best practices and integrate generative AI concepts for executive-level planning.

Format of the Course

• Instructor-guided sessions supported by real-world cloud demonstrations.
• Extensive hands-on exercises across both AWS and Azure environments.
• Practical labs designed to build readiness for multiple certification exams.

Course Customization Options

• For tailored content aligned with your organizational cloud roadmap, please contact us to customize this training.

This instructor-led, live training in New York (online or onsite) is aimed at intermediate-level data scientists and developers who wish to apply NLP techniques using Python in Google Colab.

By the end of this training, participants will be able to:

• Understand the core concepts of natural language processing.
• Preprocess and clean text data for NLP tasks.
• Perform sentiment analysis using NLTK and SpaCy libraries.
• Work with text data using Google Colab for scalable and collaborative development.

This instructor-led, live training in New York (online or onsite) is aimed at intermediate-level data scientists and developers who wish to understand and apply deep learning techniques using the Google Colab environment.

By the end of this training, participants will be able to:

• Set up and navigate Google Colab for deep learning projects.
• Understand the fundamentals of neural networks.
• Implement deep learning models using TensorFlow.
• Train and evaluate deep learning models.
• Utilize advanced features of TensorFlow for deep learning.

This instructor-led, live training in New York (online or onsite) is aimed at intermediate-level data engineers, cloud architects, and business intelligence professionals who wish to master data management in industry-specific cloud environments.

By the end of this training, participants will be able to:

• Understand the principles and components of data fabrics.
• Design and implement data integration and orchestration solutions.
• Ensure data quality and governance within industry cloud platforms.
• Utilize data fabrics to support industry-specific data analysis and decision-making.
• Stay current with emerging trends and technologies in cloud data management.

This instructor-led, live training in New York (online or onsite) is aimed at beginner-level IT professionals, business analysts, and project managers who wish to understand the fundamentals of cloud computing and its applications in various industries.

By the end of this training, participants will be able to:

• Identify the key characteristics and benefits of cloud computing.
• Understand the differences between various cloud service and deployment models.
• Recognize the importance of industry-specific cloud solutions.
• Assess the security and compliance aspects of cloud platforms.
• Explore emerging trends and future directions in cloud technology.

This instructor-led, live training in New York (online or onsite) is aimed at intermediate-level cloud engineers and operations managers who wish to improve their cloud infrastructure management using Kubiya AI.

By the end of this training, participants will be able to:

• Integrate Kubiya AI into cloud infrastructure.
• Automate cloud resource provisioning and management.
• Optimize cloud costs using AI-powered analytics.
• Enhance cloud security with AI-driven monitoring.

This instructor-led, live training in New York (online or onsite) is aimed at intermediate-level data scientists and developers who wish to apply machine learning algorithms efficiently using the Google Colab environment.

By the end of this training, participants will be able to:

• Set up and navigate Google Colab for machine learning projects.
• Understand and apply various machine learning algorithms.
• Use libraries like Scikit-learn to analyze and predict data.
• Implement supervised and unsupervised learning models.
• Optimize and evaluate machine learning models effectively.

This instructor-led, live training in New York (online or onsite) is aimed at IT professionals who wish to learn the fundamentals of Alibaba Cloud and how to use its cloud computing services.

By the end of this training, participants will be able to:

• Understand the Alibaba Cloud solution architecture.
• Learn about the Alibaba Cloud core products and services.
• Understand the capabilities of Alibaba Cloud in dealing with big data and databases.

This instructor-led, live training in New York (online or onsite) is aimed at beginner-level data scientists who wish to learn how to create meaningful and visually appealing data visualizations.

By the end of this training, participants will be able to:

• Set up and navigate Google Colab for data visualization.
• Create various types of plots using Matplotlib.
• Utilize Seaborn for advanced visualization techniques.
• Customize plots for better presentation and clarity.
• Interpret and present data effectively using visual tools.

This instructor-led, live training in New York (online or onsite) is aimed at advanced-level professionals who wish to deepen their understanding of DevOps practices and streamline development processes using AWS Cloud9.

By the end of this training, participants will be able to:

• Set up and configure AWS Cloud9 for DevOps workflows.
• Implement continuous integration and continuous delivery (CI/CD) pipelines.
• Automate testing, monitoring, and deployment processes using AWS Cloud9.
• Integrate AWS services such as Lambda, EC2, and S3 into DevOps workflows.
• Utilize source control systems like GitHub or GitLab within AWS Cloud9.

This instructor-led, live training in New York (online or onsite) is aimed at beginner-level developers and data analysts who wish to learn Python programming from scratch using Google Colab.

By the end of this training, participants will be able to:

• Understand the basics of Python programming language.
• Implement Python code in Google Colab environment.
• Utilize control structures to manage the flow of a Python program.
• Create functions to organize and reuse code effectively.
• Explore and use basic libraries for Python programming.

VMware vSphere is a leading virtualization platform used to build resilient IT infrastructure.

This instructor-led, live training (online or onsite) is aimed at intermediate-level IT professionals who wish to gain practical skills in identifying and resolving issues in VMware vSphere environments.

By the end of this training, participants will be able to:

• Diagnose and resolve common problems related to virtual machines and vSphere services.
• Use VMware tools to analyze and fix performance and configuration issues.
• Troubleshoot virtual networking and storage configurations.
• Perform root cause analysis in production environments.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

This instructor-led, live training in New York (online or onsite) is aimed at intermediate to advanced-level integration developers and system administrators who wish to learn advanced Boomi techniques for building, managing, and deploying cloud-based solutions on integration platforms.

By the end of this training, participants will be able to:

• Use AtomSphere and work with Boomi documents.
• Create and design complex integration processes for advanced logic and data processing.
• Manage deploy integration processes, logging, and reporting.
• Capture and handle errors.
• Apply best practices and techniques for integrating with Boomi.

This instructor-led, live training in New York (online or onsite) is aimed at beginner-level data scientists and IT professionals who wish to learn the basics of data science using Google Colab.

By the end of this training, participants will be able to:

• Set up and navigate Google Colab.
• Write and execute basic Python code.
• Import and handle datasets.
• Create visualizations using Python libraries.

This instructor-led, live training in New York (online or onsite) is aimed at intermediate-level professionals who wish to learn how to effectively build, deploy, and maintain serverless applications on AWS Cloud9 and AWS Lambda.

By the end of this training, participants will be able to:

• Understand the fundamentals of serverless architecture.
• Set up AWS Cloud9 for serverless application development.
• Develop, test, and deploy serverless applications using AWS Lambda.
• Integrate AWS Lambda with other AWS services such as API Gateway and S3.
• Optimize serverless applications for performance and cost efficiency.

This instructor-led, live training in New York (online or onsite) is aimed at intermediate-level developers, system administrators, and cloud architects who wish to use NoCloud for their cloud solutions.

By the end of this training, participants will be able to:

• Set up a development environment that includes NoCloud, Docker, Kubernetes, and Helm.
• Create and manage cloud services with NoCloud.
• Understand the lifecycle of a cloud service in NoCloud.
• Integrate NoCloud with existing infrastructure or virtual resources.
• Troubleshoot common issues in a NoCloud environment.

This instructor-led, live training in New York (online or onsite) is aimed at developers, system administrators, and cloud enthusiasts who wish to gain practical knowledge of OpenNebula and use it for their cloud solutions.

By the end of this training, participants will be able to:

• Set up a development environment that includes OpenNebula.
• Create and manage virtual machines in OpenNebula.
• Understand the lifecycle of a virtual machine.
• Integrate OpenNebula with existing infrastructure.
• Troubleshoot common issues in an OpenNebula environment.

This instructor-led, live training in New York (online or onsite) is aimed at intermediate-level system administrators who wish to use VMware vCenter to manage complex virtual environments.

By the end of this training, participants will be able to:

• Understand the architecture and components of VMware vSphere and vCenter Server.
• Install, configure, and manage VMware ESXi and vCenter Server.
• Implement advanced networking and storage configurations.
• Create, manage, and migrate virtual machines.
• Ensure high availability and disaster recovery in a virtualized environment.
• Automate vSphere tasks and manage lifecycle and upgrades.
• Troubleshoot common issues and apply best practices.

In this instructor-led, live training in New York, participants will learn how to set up and manage a production-scale container environment using Kubernetes on Google Cloud. 

By the end of this training, participants will be able to:

• Configure and manage Kubernetes on Google Cloud.
• Deploy, manage and scale a Kubernetes cluster.
• Deploy containerized (Docker) applications on Google Cloud.
• Migrate an existing Kubernetes environment from on-premise to Google Cloud.
• Integrate Kubernetes with third-party continuous integration (CI) software.
• Ensure high availability and disaster recovery in Kubernetes.

This instructor-led, live training in New York (online or onsite) is aimed at technical persons who wish to gain a practical understanding of available cloud solutions, the data analysis processes needed to work with data in the cloud, and the hands-on practice to apply tools such as Power BI to analyze data.

By the end of this training, participants will be able to:

• Install and configure Power BI.
• Evaluate the various data solutions offered by cloud providers such as Azure.
• Gain an understanding of the different structures, modeling approaches, and data warehouse designs used to store, manage and access Big Data.
• Apply tools and techniques to clean data in preparation for analysis.
• Build reporting and analytics solutions based on on-premise as well as cloud data.
• Integrate data analytics solutions with a data warehouse.
• Mitigate data security risks and ensure data privacy.

This instructor-led, live training in New York (onsite or remote) is aimed at engineers who wish to deploy and manage IoT devices on AWS.

By the end of this training, participants will be able to build an IoT platform that includes the deployment and management of a backend, gateway, and devices on top of AWS.

This instructor-led, live training in New York (online or onsite) is aimed at developers who wish to install, configure, and manage AWS IoT Greengrass capabilities to create applications for various devices.

By the end of this training, participants will be able to use AWS IoT Greengrass to build, deploy, manage, secure, and monitor applications on intelligent devices.

This instructor-led, live training in New York (onsite or remote) is aimed at developers who wish to use AWS Lambda to build and deploy services and applications to the cloud, without needing to worry about provisioning the execution environment (servers, VMs and containers, availability, scalability, storage, etc.).

By the end of this training, participants will be able to:

• Configure AWS Lambda to execute a function.
• Understand FaaS (Functions as a Service) and the advantages of serverless development.
• Build, upload and execute AWS Lambda functions.
• Integrate Lambda functions with different event sources.
• Package, deploy, monitor and troubleshoot Lambda based applications.

This instructor-led, live training in New York (online or onsite) is aimed at integration developers, sysadmins, and system integrators who wish to use Boomi to build, manage, and deploy integration platforms for cloud-based solutions.

By the end of this training, participants will be able to:

• Set up the necessary environment to start building integrations with Boomi.
• Understand Boomi AtomSphere's features, architecture, and core concepts.
• Learn how to design, build, and deploy integration processes with Boomi.
• Use Boomi's dashboard and reporting options to monitor applications.
• Manage configurations and deployments for Atom, Molecule, and Atom Cloud.
• Enable web services and API integration and management with Boomi.

Audience

Software Engineer/Computer Scientists with adequate concepts of algorithms and familiarity with at least one programming/scripting language but without any experience of Cloud Computing

This instructor-led, live training in New York (online or onsite) is aimed at sysadmins or IT administrators who wish to use Citrix Hypervisor to deploy, manage, and optimize data center virtualization across desktop, servers, and cloud.

By the end of this training, participants will be able to:

• Set up the necessary environment to start managing desktop, server, and cloud virtualization with Citrix Hypervisor.
• Simplify virtualization management and operations by utilizing the full features and architecture of Citrix Hypervisor.
• Configure and manage the Citrix Hypervisor environment using XenCenter and CLI commands.
• Learn how to install, configure, and manage virtual machines, GPUs, and storage repositories.
• Optimize the overall performance of Citrix Hypervisor pools by implementing high availability and workload balancing.

This 7-day programme provides a comprehensive, hands-on journey into designing, deploying, and operating cloud-native applications using modern DevOps practices.

Participants will explore how to design scalable microservices architectures, optimise container environments, and manage production workloads using Kubernetes. The course covers advanced deployment strategies, GitOps-based automation, and observability practices to ensure system reliability and performance.

A strong focus is placed on real-world operational challenges, including incident response, failure simulation, and root cause analysis. The programme concludes with the use of AI-powered tools to support troubleshooting and accelerate operational decision-making.

By the end of the training, participants will have a clear understanding of how to build, deploy, monitor, and maintain resilient distributed systems in a Kubernetes-based environment.

Day 1 - provides end-to-end coverage of fundamental cloud computing topics as they relate to both technology and business. The module is divided into a series of sections, each of which is accompanied by a hands-on exercise.

Day 2 - explores technology-related topics that relate to cloud computing platforms. It does not get into implementation or programming details, but instead keeps coverage at a conceptual level, focusing on topics that address cloud service architecture, cloud security threats and technologies, virtualization and data processing.

Day 3 - provides a technical insight into foundational cloud computing platforms. Infrastructure-as-a-Service (IaaS), Platform-as-a-Service (PaaS) and Software-as-a-Service (SaaS) environments are explored as compound patterns, comprised of unique and shared building blocks. This module is structured as a guided tour through these architectural layers, describing primary components, highlighting shared components and explaining how building blocks can be assembled and implemented via cloud computing mechanisms and practices

Day 4 - builds upon Day 3 to provide a deep dive into elastic, resilient and multitenant technology architectures, as well as specialized solution architectures, such as cloud bursting and cloud balancing. Through the study of architectural mechanisms, industry technologies and design patterns, both core and extended components are described that combine to realize elasticity, resiliency and multitenancy as primary characteristics of cloud platforms. By leveraging these native and enhanced scalability and failover-related feature-sets, specialized solution architectures are described to enable bursting between clouds and on-premise and cloud environments, as well as the balancing of runtime loads across clouds for performance and failover purposes.

Day 5 - presents participants with a series of exercises and problems that are designed to test their ability to apply their knowledge of topics covered previously.

This instructor-led, live training in New York (online or onsite) is aimed at technical persons who wish to gain a practical understanding of available cloud solutions, the data analysis processes needed to work with data in the cloud, and the hands-on practice to apply tools such as Power BI to analyze data.

By the end of this training, participants will be able to:

• Install and configure Power BI.
• Evaluate the various data solutions offered by cloud providers such as Azure.
• Gain an understanding of the different structures, modeling approaches, and data warehouse designs used to store, manage and access Big Data.
• Apply tools and techniques to clean data in preparation for analysis.
• Build reporting and analytics solutions based on on-premise as well as cloud data.
• Integrate data analytics solutions with a data warehouse.
• Mitigate data security risks and ensure data privacy.

This course is designed to empower non-technical professionals—such as managers, business analysts, QA testers, and operations personnel—with a foundational understanding of cloud computing. Participants will explore the core concepts, benefits, and practical applications of the cloud to make more informed decisions and contribute effectively to cloud migration initiatives. Emphasis will be placed on demystifying cloud jargon, comparing cloud and on-premise infrastructure, understanding service models, and recognizing how cloud impacts various roles within an organization.

By the end of this course, participants will be able to:

• Understand the key definitions and terminology of cloud computing
• Identify different cloud service models (IaaS, PaaS, SaaS)
• Differentiate between cloud deployment models (Public, Private, Hybrid, Multi-Cloud)
• Compare on-premises vs. cloud-based infrastructure
• Understand cloud advantages: scalability, agility, availability, and cost-efficiency
• Recognize common cloud platforms (AWS, Azure, GCP) and their service offerings
• Comprehend cloud responsibilities: shared responsibility model and role-based access
• Grasp the impact of cloud on software testing, deployment, and monitoring
• Participate effectively in cloud adoption and migration projects
• Appreciate cloud security basics, compliance, and governance principles

This instructor-led, live training in New York (online or onsite) is aimed at sysadmins, DevOps, and developers who wish to use CloudForms to manage virtual infrastructures in a centralized interface.

By the end of this training, participants will be able to:

• Install and configure CloudForms on different virtual machine and cloud platforms (OpenStack, OpenShift, and VMware).
• Create a centralized management interface for monitoring multiple clusters.
• Enhance the security control and configuration policies of an entire infrastructure.
• Transform a distributed virtual infrastructure into a unified hybrid environment.
• Optimize workload performance and efficiency by automating orchestration and workflows.

This instructor-led, live training in New York (online or onsite) is aimed at IT architects and IT consultants who wish to employ the best practices for cloud infrastructure and services.

By the end of this training, participants will be able to:

• Leverage cloud infrastructure and services for business implementation.
• Apply advanced cloud security with Cloud Security Alliance standards.
• Migrate legacy systems into the cloud using SOA and Paas synergy.
• Automate on demand resource provisioning for asynchronous cloud services.

• Gain foundational knowledge of Citrix Virtual Apps and Desktops 7 
• How to install, configure, and manage a Citrix Virtual Apps and Desktops 7 site and Cloud connectors
• Identify the considerations between Citrix Virtual Apps and Desktops on-premises and the Citrix Virtual Apps and Desktops Service
• How to deliver app and desktop resources

This instructor-led, live training in New York (online or onsite) is aimed at cloud administrators, cloud architects, technology heads, and financial analysts who wish to record, manage, monitor, and process financial assets of an organization in the cloud.

By the end of this training, participants will be able to use FinOps practices in an organization to forecast costs, optimize processes, and perform financial management operations in the cloud.

Summary:

• Basics of IoT architecture and functions
• “Things”, “Sensors”, Internet and the mapping between business functions of IoT
• Essential of all IoT software components- hardware, firmware, middleware, cloud and mobile app
• IoT functions- Fleet manager, Data visualization, SaaS based FM and DV, alert/alarm, sensor onboarding, “thing” onboarding, geo-fencing
• Basics of IoT device communication with cloud with MQTT.
• Connecting IoT devices to AWS with MQTT (AWS IoT Core).
• Connecting AWS IoT core with AWS Lambda function for computation and data storage using DynamoDB.
• Connecting Raspberry PI with AWS IoT core and simple data communication.
• Hands on with Raspberry PI and AWS IoT Core to build a smart device.
• Sensor data visualization and communication with web interface.

This instructor-led, live training in New York (online or onsite) is aimed at cloud engineers who wish to store objects and unstructured data using MinIO.

By the end of this training, participants will be able to:

• Provide an alternative to Unix Commands with the MinIO Client.
• Use MinIO to build high performance infrastructures for machine learning, analytics, and more.
• Deploy MinIO on Kubernetes for orchestrated deployment to scale.

This instructor-led, live training in New York (online or onsite) is aimed at intermediate-level virtualization administrators who wish to use open-source platforms to migrate away from VMware.

By the end of this training, participants will be able to:

• Install and configure KVM, oVirt, and Proxmox VE.
• Migrate virtual workloads from VMware.
• Implement high availability and disaster recovery.
• Optimize performance in open-source virtualization environments.

This instructor-led, live training in New York (online or onsite) is aimed at system administrators and developers who wish to install, configure, monitor, and manage Kubernetes-based environments through VMware PKS (formerly named Pivotal Container Service).

By the end of this training, participants will be able to:

• Install VMware PKS components and tools.
• Deploy with BOSH and Pivotal Ops Manager.
• Integrate PKS with VMware Harbor capabilities.
• Manage and monitor infrastructures and applications using VMware tools.

This instructor-led, live training in New York (online or onsite) is aimed at DevOps engineers and developers who wish to use VMware Tanzu to build, deploy, and orchestrate cloud-native applications in a VSphere environment.

By the end of this training, participants will be able to:

• Set up the necessary environment to start managing Kubernetes clusters with VMWare Tanzu.
• Understand the fundamentals of using VMWare portfolio of products to centralize management of clusters and applications.
• Build, run, deploy, and orchestrate containerized applications using the VMWare Tanzu Kubernetes Grid service.
• Learn how to manage and monitor the lifecycle of VMware Tanzu components in VSphere.

Summery:

• Basics of IoT architecture and functions
• “Things”, “Sensors”, Internet and the mapping between business functions of IoT
• Essential of all IoT software components- hardware, firmware, middleware, cloud and mobile app
• IoT functions- Fleet manager, Data visualization, SaaS based FM and DV, alert/alarm, sensor onboarding, “thing” onboarding, geo-fencing
• Basics of IoT device communication with cloud with MQTT.
• Connecting IoT devices to AWS with MQTT (AWS IoT Core).
• Connecting AWS IoT core with AWS Lambda function for computation and data storage.
• Connecting Raspberry PI with AWS IoT core and simple data communication.
• Alerts and events
• Sensor calibration