Final Exam: CloudOps Engineer - compare the differences between problem management and incident management along with how they are implemented in supporting CloudOps implementation using multi-cloud and hybrid solutions
- configure Terraform for an automated workflow that can be used to implement change management and deployment pipeline
- create visual drafts of CloudOps solution using prototyping tool to provide a walkthrough of CloudOps solution before finalizing the solution adoption
- describe the approach of design thinking in implementing an agile and iterative process to help enterprises manage changes and CloudOps evolution
- describe the approach that can be adopted by CloudOps engineers for better collaboration and communication with key stakeholders participating in CloudOps management and implementation processes
- describe the concept and objective of redundancy along with the major forms of redundancy that helps increase the reliability of systems
- describe the concept and the prominent use cases of disposable and repeatable infrastructure that enables a high degree of automation
- describe the concept of performance engineering and elaborate on the phases of the performance engineering approach that helps ensure non-functional requirements are management efficiently
- describe the concept of the Novel PaaS framework and its components that can be adapted to support the deployment of multi-tier and stateful applications
- describe the concept of Zero Code multi-cloud automation along with the features afforded by Ansible and Terraform that can be used together to implement Zero Code multi-cloud automation
- describe the features of prominent cloud-enabled automation tools
- describe the features of prominent tools that can be used to enable cloud application deployment across multi and hybrid cloud
- describe the five pillars of the AWS framework along with the patterns to implement them while architecting technology solutions to realize expected performance
- describe the functional and non-functional components and layers that need to be considered for planning performance management that applies to application and infrastructure
- describe the hierarchical network design that uses core, distribution and access layers with redundancy to eliminate a single point of failure in the network
- describe the performance management challenges for cloud-hosted services from the perspective of cloud consumers and cloud service providers
- describe the primary cloud infrastructure components and technologies that CloudOps engineers can use to facilitate automated infrastructure management
- describe the prominent cloud architectures and practices a CloudOps engineer must embrace to ensure productive CloudOps practices
- describe the steps involved in installing CloudWatch Agent to collect memory utilization and analyzing how that new data point can help during EC2 right-sizing
- describe why and how to build Explainability into CloudOps workflow with a focus on eliminating the negative impact of IT
- design redundant multi-region cloud architecture using Visio with a focus on topology and operations to depict the benefits of redundant architecture
- differentiate the traditional functional and non-functional features of DevOps from those of CloudOps, recognizing how the roles of DevOps and CloudOps engineers vary
- evaluate the implications of transitioning to the cloud and how to shift from static infrastructure to dynamic infrastructure to design CloudOps solution
- identify prominent cloud monitoring and performance management tools
- identify the common performance problems and describe the systemic tuning approach that can help improve the overall system performance
- identify the prevalent issues that cause downtime within infrastructure layers along with the mechanisms that can be used to manage challenges by adopting the right solution architecture powered by redundancy
- list and describe the features of prominent design tools that can be used to design diversified architectures and templates
- list and describe the features of prominent SaaS-based tools that can be used to manage redundant multi-cloud environments
- list and describe the features of various type of cloud computing architectures with a focus on single-site, non-redundant and redundant architectures
- list the primary cloud management skills a CloudOps engineer must possess to manage the critical ops processes are applied in cloud architectures
- list the prominent cloud monitoring and performance management tools
- list the stages in the design thinking process involved in developing an empathic approach to craft Explainability for varying users and stakeholders of CloudOps
- outline the process CloudOps engineers need to follow when planning and implementing continuous operations in public and private clouds using DevOps principles
- recall the challenges and opportunities of explainable AI and its impact on DevOps principles integrated into CloudOps
- recall the concept and benefits of continuous automation along with the path that can be adopted to implement continuous automation while solutioning CloudOps
- recall the concept of interpretability and Explainability along with how they can be applied in CloudOps
- recall the different algorithms that can be used to explain CloudOps practices adopted in the enterprise
- recall the essential characteristics that are a must-have for hybrid or multi-cloud for successful and robust deployments
- recall the essential elements of DevOps and automation mindset that helps identify critical areas of CloudOps deployment requiring support
- recall the key cloud redundancy design principles that can help build secure, high-performing, resilient and efficient infrastructure for applications
- recall the recommended best practices for cloud management systems and disaster recovery that need to be adopted to design a robust multi-cloud deployment platform
- recall the significance of creating a knowledge base to integrate and implement self-service capability to support operations in multi-cloud environments using the principles of CloudOps
- recall the steps involved in configuring performance testing and the approach of analyzing test results using patterns of system behavior
- recall the techniques that CloudOps engineers can use to identify the need for continuous application optimization in the cloud
- recognize the challenges associated with managing multi-cloud environments along with the approach of troubleshooting the challenges
- recognize the core factors for deriving a technology upgrade path that can enable enterprises to remain in sync with future technology trends
- recognize the critical issues associated with multi-cloud storage along with the approach of troubleshooting them
- recognize the features and benefits provided by Visual Paradigm to create the visual architecture of multi-cloud solutions for CloudOps practices
- recognize the Five Forces Model that can be adapted to conduct an in-depth analysis of enterprises' requirements and reason for adopting CloudOps solution
- recognize the major challenges faced by CloudOps practitioners when designing CloudOps solution
- recognize the prominent redundancy architectures that can be used to manage reliability in the standard architecture and improve availability and resiliency
- recognize the roadmap of performance tuning that includes the methods to quantify performance objectives, measure performance metrics, locate bottlenecks in the system and minimize the impact of bottlenecks in traditional or legacy deployments
- recognize the role of prototyping tools that can be used to validate the CloudOps model, generate prototypes, allocate required resources and deploy generated prototypes to multi-cloud environments
- recognize the scope and potential challenges of multi-cloud design considerations along with the primary building blocks that include foundation resources, workload management and service consumption
- recognize the scope and potential challenges of multi-cloud design considerations along with the primary building blocks that include foundation resources, workload management and service consumption
- recognize the technology shifts that need to be made to implement continuous automation for CloudOps solution
- set up an Amazon QuickSight account and illustrate efficiency through visualizations
- set up Application Insight to automatically detect performance anomalies and diagnose performance issues
- specify the high-level architecture of CloudOps prototyping tool along with the associated components, responsibilities and interfaces
- specify the steps involved in creating a multi-cloud performance optimization strategy
|
