Measuring Performance - Level 3

DifficultyAdvanced
AVG Duration3h
Students1
Content
14

Description

While there are many indicators of cloud performance exposed across operational dashboards, Service Level Agreements are a core method to setting expectations for uptime and performance across a portfolio of cloud-native applications. The need to understand how to baseline such agreements and level-set goals for system performance and uptime across the organizations is key to success in implementing realistic availability levels.

This learning path teaches Measuring Performance to a level 3 standard. 

Learning Objectives

  • Be able to measure performance of cloud hosted applications and services

Certificate

Your certificate for this learning path

Training Content

1
Course - Intermediate - 16m
An Overview of Amazon CloudWatch
This course takes a high-level look at Amazon CloudWatch and some of its features and components.
2
Hands-on Lab - Beginner - 1h 30m
Introduction to CloudWatch
CloudWatch is a monitoring service that AWS provides. You can use it to monitor AWS resources or custom resources, inside or outside AWS.
3
Hands-on Lab - Beginner - 1h 30m
Monitoring Resources with Azure Monitor
Learn to leverage Azure Monitor to diagnose application and infrastructure with logs, query logs with Azure log queries, and leverage alerts and action groups
4
Hands-on Lab - Intermediate - 1h
Monitor Compute Engine Resources Through Cloud Monitoring
In this lab, you will understand the best practices to monitor a compute engine instance by viewing the usage, creating alert policies and creating a chart.
5
Hands-on Lab - Intermediate - 40m
Find Application Performance Bottlenecks With Google Cloud Trace
Learn how Google Cloud Trace helps you analyze the latency of application code in near real-time in this hands-on lab.
About the Author
Students121111
Labs65
Courses113
Learning paths179

Jeremy is a Content Lead Architect and DevOps SME here at Cloud Academy where he specializes in developing DevOps technical training documentation.

He has a strong background in software engineering, and has been coding with various languages, frameworks, and systems for the past 25+ years. In recent times, Jeremy has been focused on DevOps, Cloud (AWS, Azure, GCP), Security, Kubernetes, and Machine Learning.

Jeremy holds professional certifications for AWS, Azure, GCP, Terraform, Kubernetes (CKA, CKAD, CKS).