2 to 3 Months
Online + Offline
15 Students Only Batch Size
Anyone
Beginner to Advanced Training
Cloud Computing Overview: IaaS, PaaS, and SaaS On-demand access to resources Cloud Computing Reference Model: Definition of "cloud" Components and relationships Guiding cloud system architecture Characteristics and Benefits: On-demand services Cost efficiency Scalability Agility Focus on core functions Challenges: Security concerns Data privacy issues Potential downtimes Solutions to challenges Introduction to Virtualization: Foundational technology Creation of virtual resources Enhancing efficiency and flexibility Characteristics of Virtualized Environments: Abstraction Isolation Flexibility Running multiple workloads on a single server Taxonomy of Virtualization Techniques: Server virtualization Storage virtualization Network virtualization Distinct purposes for each technique Examples of Virtualization Technologies: VMware Microsoft Hyper-V Tools for managing virtualized environments Software Licenses and Cloud Cost Models: Navigating software licenses Compliance in the cloud Understanding pay-as-you-go Reserved instances Spot instances Optimal resource utilization
Cloud Reference Model and Architecture: Explore the Cloud Reference Model, including architectural components and interactions. Service Models (IaaS, PaaS, SaaS): Understand Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS) with a focus on components and advantages. Cloud Deployment Models: Distinguish between public, private, hybrid, and community clouds, discussing use cases and challenges. Economics of the Cloud: Examine cost models, pricing structures, and financial considerations associated with cloud services. Interoperability and Standards: Discuss the importance of interoperability and adherence to standards for seamless integration between different cloud services. Scalability and Fault Tolerance: Explore scalability strategies, including load balancing and auto-scaling, along with fault tolerance measures. Web Application and Machine Image Design: Cover design considerations for web applications, including microservices and serverless architecture, and the creation of machine images for consistent deployment. Security (Privacy, Database, Data, Network, Host): Address security concerns, covering privacy considerations, database security, data encryption, network security measures, and host security practices. Compromise Response: Develop an effective response plan for security compromises, including incident detection, analysis, containment, eradication, recovery, and lessons learned.
Storage as a Service: Overview of cloud storage solutions. Object storage and block storage in the cloud. Data durability and availability considerations.Integration with other cloud services. Database as a Service: Managed database services in the cloud. Types of databases supported (e.g., SQL, NoSQL). Scalability and performance considerations. Backup and recovery options. Process as a Service: Overview of process automation in the cloud. Use cases for serverless computing. Integration with workflow management tools. Benefits of process automation. Information as a Service: Providing information services via the cloud. Data analytics and business intelligence in the cloud. Access control and data privacy considerations. Real-time data streaming services. Integration as a Service: Facilitating seamless integration between cloud and on-premises systems. Enterprise service buses and middleware in the cloud. API management and integration patterns. Data synchronization and consistency. Testing as a Service: Overview of cloud-based testing services. Types of testing supported (e.g., performance testing, security testing). Test automation and continuous testing in the cloud. Collaborative testing environments. Capacity Planning and Cloud Scale: Strategies for capacity planning in the cloud. Auto-scaling and dynamic resource allocation. Monitoring and optimizing resource usage. Handling bursts in demand and unexpected load spikes. Disaster Recovery Planning:Importance of disaster recovery planning in cloud environments. Identifying critical assets and potential risks. Creating and testing disaster recovery plans. Regularly updating and refining recovery strategies. Disasters in the Cloud and Disaster Management: Understanding potential disasters Incident response and disaster recovery coordination. Cloud provider responsibilities vs. customer responsibilities. Continuous improvement in disaster management strategies.
Cloud Computing(AWS): Introduction to AWS, IAM (Identity and Access Management), EC2 Instances, AWS Networking (VPC), AWS Networking (VPC), AWS Route 53, Secure VPC Setup with EC2 Instances, Amazon S3, AWS CLI, AWS CloudFormation, AWS CodeCommit, AWS CodePipeline, AWS CodeBuild, AWS CodeDeploy, AWS CloudWatch, AWS Lambda, AWS CloudWatch Events and EventBridge, AWS CloudFront, AWS ECR (Elastic Container Registry), AWS ECS (Elastic Container Service), AWS EKS (Elastic Kubernetes Service), AWS Systems Manager, Create Infrastructure using Terraform, AWS CloudTrail and Config, AWS Elastic Load Balancer.
Once you have completed the course, assignments, exercise and submit the projects you will be able to generate the certificate.
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