CloudOps Performance Tuning: Applying Performance Principles
CloudOps 2020
14 Videos | 1h 19m 50s - Includes Assessment
- Earns a Badge
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.
WHAT YOU WILL LEARN
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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
IN THIS COURSE
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1.Course Overview1m 21sUP NEXT
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2.Common CloudOps Deployment Performance Problems6m 29s
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3.The Performance Engineering Approach5m 59s
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4.A Performance Tuning Roadmap6m 59s
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5.Post-deployment Performance Diagnostic Techniques5m
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6.Checklists to Optimize Application Performance6m 4s
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7.Functional and Non-functional Layers and Components7m 27s
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8.Performance Testing Configuration Steps6m 31s
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9.Cloud Computing KPIs and Metrics4m 34s
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10.Service Performance Measurement Research Methodology6m 3s
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11.The Cloud Service Metric Ecosystem5m 39s
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12.Private and Hybrid Cloud Performance Measurement3m 46s
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13.Performance Management Challenges5m 59s
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14.Course Summary1m 58s
EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE
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