
This section will help you to acheive an in-depth understanding of CloudWatch, its benefits and configuration. As we move forward, we will learn about different CloudWatch metrics used to guage performance of various resources like EC2, EBS, ElastiCache Nodes, RDS DB Instances and ELB. At the end, there are few lectures based on Billing Alerts, Organizations and Consolidated Billing.
This lecture will help you understand the basic fundamentals of CloudWatch, Metrics, Custom Metrics and Alarms.
This lab session showcases all three functionalities of CloudWatch and how to apply them in real-time scenario.
In this lecture, we will focus upon following two EC2 status checks: Instance Status Checks and System Status Checks.
Let's go through a list of some common metrics to analyze the performance of an Amazon EC2 instance.
This lecture shows a complete process to create and configure custom metrics to analyze the memory and disk utilization of an Amazon EC2 instance.
Let's understand some of the common metrics used to analyze the performance of different EBS volume types.
In this lecture, I have listed and covered all important metrics used to analyze the performance of existing RDS DB instances.
An Elastic Load Balancer is a very critial component of your archirtecture as it helps to distribute and load balance your entire application's traffic automatically. Hence, it is essential that you are well aware of some of the common metrics to analyze the performance of this component.
Let's see how you can monitor both the Memcached and Redis engines within ElastiCache by using some of the common metrics.
This lecture primarily focuses on Consolidated Billing and how it can help you to get volume discounts.
This is a very important lab session showing step-by-step process to configure Organizations on AWS Management Console.
In this lab session, we configure Billing Alerts to send us notifications just in case our monthly threshold is exceeded.
This section covers all important aspects on High Availability, differences between Elasticity and Scalability, how to troubleshoot potential Auto Scaling issues and implementing Multi-AZ on RDS databases.
Let's go through and understand the clear differences between the principle of Elasticity and Scalability.
This lecture includes all possible reasons behind the unsuccessful launching of EC2 instances within your Auto Scaling groups, and how to fix them.
In this lecture, I have covered the concepts of Multi-AZ extensively.
This lab session showcases the practical implementation of Multi-AZ to achieve high availability of your databases.
This is a bonus section based upon previous section on High Availability. Feel free to skip it if you have already take any of the Solutions Architect - Associate courses out there.
This comprehensive lab session shows step-by-step procedure to change the attributes of an existing EC2 instance by changing its instance type, volume size and type.
This comprehensive lab session shows step-by-step procedure to change the attributes of an existing EC2 instance by changing its instance type, volume size and type.
This comprehensive lab session shows step-by-step procedure to change the attributes of an existing EC2 instance by changing its instance type, volume size and type.
This comprehensive lab session shows step-by-step procedure to change the attributes of an existing EC2 instance by changing its instance type, volume size and type.
In this lab session, we will see that how Auto Scaling scales out through Target Tracking Policy if the average CPU utilization of an existing Auto Scaling group shoots up.
In this lab session, we will see that how Auto Scaling scales out through Target Tracking Policy if the average CPU utilization of an existing Auto Scaling group shoots up.
In this lab session, we will see that how Auto Scaling scales out through Target Tracking Policy if the average CPU utilization of an existing Auto Scaling group shoots up.
In this lab session, we will see that how Auto Scaling scales out through Target Tracking Policy if the average CPU utilization of an existing Auto Scaling group shoots up.
In this lab session, we will see that how Auto Scaling scales out through Target Tracking Policy if the average CPU utilization of an existing Auto Scaling group shoots up.
This lab session showcases step-by-step procedure to scale out or scale in using scheduled actions.
Let's see how you can manually scale your architecture by manipulating the desired capacity of an existing Auto Scaling group.
In this course, you will create automatable and repeatable deployments of networks and systems on the AWS platform. We will explore the AWS features and tools related to configuration and deployment and common techniques for configuring and deploying systems.
Course Objectives
In this course, you will learn how to:
Use standard AWS infrastructure features such as Amazon Virtual Private Cloud (Amazon VPC), Amazon Elastic Compute Cloud (Amazon EC2), Elastic Load Balancing (ELB), and AWS Auto Scaling from the command line
Use AWS CloudFormation to produce stacks of AWS resources that can be deployed in an automated, repeatable fashion
Deploy Amazon EC2 instances using command line calls and troubleshoot common problems with instances
Monitor the health of Amazon EC2 instances and other AWS services
Manage user identity, AWS permissions, and security in the cloud
Manage resource consumption in an AWS account using Amazon CloudWatch, tagging, and AWS Trusted Advisor
Select and implement the best strategy for creating reusable Amazon EC2 instances
Configure a set of Amazon EC2 instances that launch behind a load balancer, with the system scaling up and down in response to demand
The AWS Certified SysOps Administrator – Associate exam validates technical expertise in deployment, management, and operations on the AWS platform. Exam concepts you should understand for this exam include:
Deploying, managing, and operating scalable, highly available, and fault-tolerant systems on Amazon Web Services (AWS)
Migrating an existing on-premises application to AWS
Implementing and controlling the flow of data to and from AWS
Selecting the appropriate AWS service based on compute, data, or security requirements
Identifying appropriate use of AWS operational best practices
Estimating AWS usage costs and identifying operational cost-control mechanisms