CloudOps Performance Tuning: Applying Performance Principles

CloudOps Performance Tuning: Applying Performance Principles

• discover the key concepts covered in this course
• identify common CloudOps deployment performance problems and describe the systemic tuning approach that can help improve overall system performance
• define the concept of a performance engineering approach and identify its phases that help ensure non-functional requirements are managed efficiently
• outline a performance tuning roadmap that includes quantifying performance objectives, measuring performance metrics, locating system bottlenecks, and minimizing the impact of bottlenecks in traditional or legacy deployments
• classify post-deployment performance diagnostic techniques for large-scale software systems deployed on-premises and in cloud environments
• specify checklists that are productive in optimizing application performance and are deployed in data centers and the cloud
• describe the functional and non-functional components and layers to consider when planning for application and infrastructure performance management
• outline the steps involved in configuring performance testing and the approach to analyzing test results using patterns of system behavior
• recognize the key performance indicators and metrics that help build ROIs from cloud computing
• describe the research methodology to decide the best cloud computing architecture model and services to run on it when implementing cloud computing service performance measurement
• recognize the cloud service metric ecosystem, model characteristics, and prominent cloud service model uses cases that help identify gaps in hybrid and multi-cloud deployment architectures
• specify how to measure the performance of private or hybrid clouds and describe the instrumentation architecture used to collect required performance and throughput metrics
• recall the performance management challenges for cloud-hosted services and outline the recommended solution architecture
• summarize the key concepts covered in this course

When designing solutions, CloudOps practitioners need to mitigate typical performance issues. In this course, you'll explore some common performance problems and the systemic tuning approach to improving performance.

You'll examine what comprises a performance engineering approach before outlining a practical performance tuning roadmap. Next, you'll identify post-deployment performance diagnostic techniques for large-scale software systems, essential steps when optimizing application performance, and functional and non-functional components and layers to consider when planning performance management.

Moving on, you'll outline the steps involved in configuring performance testing and identify critical cloud computing KPIs and metrics. You'll investigate use cases that help identify gaps in hybrid and multi-cloud deployment architectures. You'll examine performance management challenges and recommended solution architecture for cloud-hosted services. Lastly, you'll outline how to measure private and hybrid cloud performance.

CloudOps Performance Tuning: Managing Multi-cloud Performance

CloudOps Performance Tuning: Managing Multi-cloud Performance

• discover the key concepts covered in this course
• recognize the scope and potential challenges of multi-cloud design considerations and categorize the primary multi-cloud building blocks into foundation resources, workload management, and service consumption
• recall the essential characteristics that are a must-have for successful and robust hybrid or multi-cloud deployments
• specify the steps involved in creating a multi-cloud performance optimization strategy
• recognize the need to monitor hybrid and multi-cloud environments and specify the approach that can be adopted to monitor hybrid and multi-cloud distributed infrastructure and track performance issues
• recall the common multi-cloud performance challenges along with the solutions that can be adopted to counter these challenges
• describe some of the prominent use cases of multi-cloud networking and the critical issues that may be encountered while configuring multi-cloud networks and identify recommended solutions
• specify the different types of non-functional tests that need to be conducted to derive a multi-cloud performance benchmark, including BGP routing tests, end-to-end and path tests, page load and HTTP tests, synthetic transaction tests, DNS server and trace tests, and VoIP RTP and SIP tests
• recognize the critical performance tuning tasks that need to be conducted on multi-cloud architectures to ensure business and service continuity
• outline how to tune multi-cloud integrator components to resolve connectivity issues between two participating clouds
• summarize the key concepts covered in this course

Managing the performance of cloud deployments extends to managing multi, hybrid, and multi/hybrid distributed cloud infrastructures. In this course, you'll explore the challenges, goals, and strategies for performance optimization in these environments.

You'll start by identifying desired characteristics for successful and robust hybrid or multi-cloud designs. Next, you'll outline how to create a multi-cloud performance optimization strategy and monitor hybrid and multi-cloud distributed infrastructures. You'll then identify common multi-cloud performance challenges and associated solutions.

Furthermore, you'll investigate prominent use cases of multi-cloud networking, recommended solutions to resolve multi-cloud network configuration issues, and the different non-functional tests available to determine a multi-cloud performance benchmark. You'll examine significant business and service continuity performance tuning tasks. Lastly, you'll outline how to tune multi-cloud integrator components to resolve connectivity issues between two participating clouds.

CloudOps Performance Tuning: Tuning Cloud Performance for Deployment

CloudOps Performance Tuning: Tuning Cloud Performance for Deployment

• discover the key concepts covered in this course
• describe the performance management challenges for cloud-hosted services from the perspective of cloud consumers and cloud service providers
• list the prominent cloud monitoring and performance management tools and describe the role of application performance management in CloudOps in improving performance of applications deployed in hybrid and multi-cloud environments
• recognize the common cloud infrastructure parameters that help determine the performance of IT infrastructures and applications running on top of cloud infrastructures
• compare performance and scalability and describe the approaches to measuring, identifying, and then optimizing problems
• define the key virtualization metrics and describe the impact of virtualization on performance management with a focus on monitoring applications in virtualized environments
• describe the five pillars of the AWS framework along with the patterns to implement them while architecting technology solutions to realize expected performance
• illustrate the steps involved in installing CloudWatch Agent to collect memory utilization and analyze how that new data point can help during EC2 right-sizing
• set up an Amazon QuickSight account and illustrate efficiency through visualizations
• evaluate the compute options provided by AWS that help select the optimal compute choice for particular workloads
• describe the critical cloud application scenarios that show how development teams use load tests and metrics to diagnose performance issues with Azure cloud
• recall the design principles that can help make applications more scalable, resilient, and manageable in Azure
• use Azure Monitor to depict performance aspects and provide a view of all monitored VMs deployed across workgroups in the subscription or environment
• set up Application Insight to automatically detect performance anomalies and diagnose performance issues
• state the best practices and solutions that can help improve the performances of compute VMs, storage, networks, databases, and applications on Google Cloud Platform (GCP)
• recognize the role of IBM Cloud Application Performance Management in helping increase the efficiency of cloud and deriving the desired performance
• recall the practices that can help recognize, minimize, and prevent trouble in situations that apply to the cloud
• troubleshoot unreachability and connectivity issues associated with EC2 instances
• summarize the key concepts covered in this course

Managing the performance of cloud-hosted services doesn't come without challenges. Luckily, there are tools to help you monitor, measure, and improve performance.

You'll start this course by exploring common performance management challenges and solutions. You'll then examine parameters to track IT infrastructure and application performance, differentiate between performance and scalability, and identify key metrics to monitor virtualized environments.

Next, you'll look in-depth at the purpose of various tools and services, such as the purpose of the five pillars of the AWS framework, how to improve infrastructure resources on Google Cloud Platform, and the role of IBM Cloud Application Performance Management in increasing cloud efficient.

You'll also work with CloudWatch Agent, AWS Compute services, Amazon QuickSight, and Application Insight to increase performance efficiency and visibility and troubleshoot issues. Finally, you'll outline how to ensure applications are more scalable, resilient, and manageable in Azure.