Why Monitor?

Monitoring provides several major benefits:

• Monitoring enables systems operators to catch issues before they become problems. This, in turn, maintains high availability and delivers high-quality customer service.
• Monitoring provides tools for making informed decisions about capacity planning.
• Monitoring is an input mechanism for automation.
• Monitoring provides visibility into the cost, utilization, and security of computing resources.

Monitoring is the process of observing and recording resource utilization in real time. Alarms are notifications based on this information in response to a predefined condition. Frequently, this condition involves failure. Alarms can also be configured to send notifications when resources are being underutilized and money is being wasted.

Traditional monitoring tools have been designed around on-premises datacenters with the idea that servers are going to be in place for an extended amount of time. Because of this, these tools have difficulty distinguishing between an Amazon Elastic Compute Cloud (Amazon EC2) instance that has failed and one that was terminated purposely. AWS created its own monitoring service, Amazon CloudWatch, that is integrated with other AWS Cloud services and uses AWS Identity and Access Management (IAM) to keep monitoring data secure.

Amazon CloudWatch

Amazon CloudWatch is a service that monitors the health and status of AWS resources in real time. It provides system-wide visibility into resource utilization, application performance, and operational health by tracking, measuring, reporting, alerting, and reacting to events that occur in an environment.

Amazon CloudWatch Logs collects and monitors log files, can set alarms, and automatically reacts to changes in AWS resources. Logs can be monitored in real time or stored for analysis.

Amazon CloudWatch Alarms monitor a single metric and perform one or more actions based on customer-defined criteria.

Amazon CloudWatch Events delivers a near real-time stream of system events that describe changes in AWS resources. These streams are delivered to Amazon EC2 instances, AWS Lambda functions, Amazon Kinesis Streams, Amazon EC2 Container Service (Amazon ECS) tasks, AWS Step Functions state machines, Amazon Simple Notification Service (Amazon SNS) topics, Amazon Simple Queue Service (Amazon SQS) queues, or built-in targets.

AWS CloudTrail

AWS CloudTrail monitors calls made to the Amazon CloudWatch Events Application Programming Interface (API) for an account. This includes calls made by the AWS Management Console, the AWS Command Line Interface (AWS CLI), and other AWS Cloud services. When AWS CloudTrail logging is turned on, Amazon CloudWatch Events writes log files to an Amazon Simple Storage Service (Amazon S3) bucket.

AWS Config

AWS Config provides a detailed view of the configuration of AWS resources in an AWS account, including how the resources are related to one another. It also provides historical information to show how configurations and relationships have changed over time. Related to monitoring, AWS Config allows customers to create rules that check the configuration of their AWS resources and check for compliance with an organization’s policies. When an AWS Config rule is triggered, it generates an event that can be captured by Amazon CloudWatch Events.

Amazon CloudWatch can monitor AWS resources, such as Amazon EC2 instances, Amazon DynamoDB tables, Amazon Relational Database Service (Amazon RDS) DB instances, custom metrics generated by applications and services, and log files generated by applications and operating systems.

AWS Trusted Advisor

AWS Trusted Advisor is an online resource designed to help reduce cost, increase performance, and improve security by optimizing an AWS environment. It provides real-time guidance to help provision resources following AWS best practices.

AWS Trusted Advisor checks for best practices in four categories:

• Cost Optimization
• Security
• Fault Tolerance
• Performance Improvement

The following four AWS Trusted Advisor checks are available at no charge to all AWS customers to help improve security and performance:

• Service Limits
• Security Groups – Specific Ports Unrestricted
• IAM Use
• Multi-Factor Authentication (MFA) on the Root Account

AWS Service Health Dashboard

The AWS Service Health Dashboard provides access to current status and historical data about every AWS Cloud service. If there’s a problem with a service, it is possible to expand the appropriate line in the details section to get more information.

In addition to the dashboard, it is also possible to subscribe to the RSS feed for any service.

For anyone experiencing a real-time operational issue with one of the AWS Cloud services currently reporting as being healthy, there is a Contact Us link at the top of the page to report an issue.

The AWS Service Health Dashboard is available at http://status.aws.amazon.com/.

AWS Personal Health Dashboard

The AWS Personal Health Dashboard provides alerts and remediation guidance when AWS is experiencing events that impact customers. While the AWS Service Health Dashboard displays the general status of AWS Cloud services, the AWS Personal Health Dashboard provides a personalized view into the performance and availability of the AWS Cloud services underlying provisioned AWS resources.

The dashboard displays relevant and timely information to help manage events in progress and provides proactive notification to help plan scheduled activities. Alerts are automatically triggered by changes in the health of AWS resources and provide event visibility and also guidance to help diagnose and resolve issues quickly.

Now let’s take a deep dive into each of these services.

Metrics

At the core of Amazon CloudWatch are metrics, which are time-ordered sets of data points that contain information about the performance of resources. By default, several services provide some metrics at no additional charge. These metrics include information from Amazon EC2 instances, Amazon Elastic Block Store (Amazon EBS) volumes, and Amazon RDS DB instances. It is also possible to enable detailed monitoring for some resources, such as Amazon EC2 instances.

Custom Metrics

In addition to monitoring AWS resources, Amazon CloudWatch can be used to monitor data produced from applications, scripts, and services. A custom metric is any metric provided to Amazon CloudWatch via an agent or an API.

Custom metrics can be used to monitor the time it takes to load a web page, capture request error rates, monitor the number of processes or threads on an instance, or track the amount of work performed by an application.

Ways to create custom metrics include the following:

• The PutMetricData API.
• AWS-provided sample monitoring scripts for Windows and Linux.
• The Amazon CloudWatch collectd plugin.
• Applications and tools offered by AWS Partner Network (APN) partners.

Custom metrics come at an additional cost based on usage.

Amazon CloudWatch Metrics Retention

In November 2016, Amazon CloudWatch changed the length of time metrics are stored inside the service as follows:

• One-minute data points are available for 15 days.
• Five-minute data points are available for 63 days.
• One-hour data points are available for 455 days.

If metrics need to be available for longer than those periods, they can be archived using the GetMetricStatistics API call.

Metrics cannot be deleted. They automatically expire after 15 months if no new data is published to them.

Namespaces

A namespace is a container for a collection of Amazon CloudWatch metrics. Each namespace is isolated from other namespaces. This isolation ensures that data collected is only from services specified and prevents different applications from mistakenly aggregating the same statistics.

There are no default namespaces. When creating a custom metric, a namespace is required. If the specified namespace does not exist, Amazon CloudWatch will create it.

Namespace names must contain valid XML characters and be fewer than 256 characters in length.

Allowed characters in namespace names are as follows:

• Alphanumeric characters (0-9, A-Z, a-z)
• Period (.)
• Hyphen (-)
• Underscore (_)
• Forward Slash (/)
• Hash (#)
• Colon (:)

AWS namespaces use the following naming convention: AWS/service. For example, Amazon EC2 uses the AWS/EC2 namespace. Sample AWS Namespaces are shown in Table 9.1.

Dimensions

A dimension is a name/value pair that uniquely identifies a metric and further clarifies the metric data stored. A metric can have up to 10 dimensions.

Every metric has specific characteristics that describe it. Think of dimensions as categories or metadata for those characteristics. The categories can aid in the design of a structure for a statistics plan. Because dimensions are part of the unique identifier for a metric, whenever a unique name/value pair is added to a metric, a new metric is created.

Dimensions can be used to filter the results from Amazon CloudWatch. For example, it is possible to get statistics for a specific Amazon EC2 instance by specifying the instance ID dimension when doing a search.

Dimensions: Server=Prod, Domain=Titusville, Unit: Count, Timestamp: 2017-05-18T12:30:00Z, Value: 105
 
Dimensions: Server=Test, Domain=Titusville, Unit: Count, Timestamp: 2017-05-18T12:31:00Z, Value: 115
 
Dimensions: Server=Prod, Domain=Rockets, Unit: Count, Timestamp: 2017-05-18T12:32:00Z, Value: 95
 
Dimensions: Server=Test, Domain=Rockets, Unit: Count, Timestamp: 2017-05-18T12:33:00Z, Value: 97

Statistics

Statistics are metric data aggregations over specified periods of time. Amazon CloudWatch provides statistics based on the metric data points provided by custom data or by other services in AWS to Amazon CloudWatch. Aggregations are made using the namespace, metric name, dimensions, and the data point unit of measure within the time period specified. Available CloudWatch statistics are provided in Table 9.2.

Pre-calculated statistics can be added to Amazon CloudWatch. Instead of data point values, specify values for SampleCount, Minimum, Maximum, and Sum. Amazon CloudWatch calculates the average for you. Values added in this way are aggregated with any other values associated with the matching metric.

Units

Each statistic has a unit of measure. Example units include bytes, seconds, count, and percent.

A unit can be specified when creating a custom metric. If one is not specified, Amazon CloudWatch uses None as the unit. Units provide conceptual meaning to data.

Metric data points that specify a unit of measure are aggregated separately. When getting statistics without specifying a unit, Amazon CloudWatch aggregates all data points of the same unit together. If there are two identical metrics that have different units, two separate data streams are returned—one for each unit.

Periods

A period is the length of time associated with a specific Amazon CloudWatch statistic. Each statistic represents an aggregation of the metrics data collected for a specified period of time. Although periods are expressed in seconds, the minimum granularity for a period is one minute.

Because of this minimum granularity, period values are expressed as multiples of 60. By varying the length of the period, the data aggregation can be adjusted.

When retrieving statistics, specify a period, start time, and an end time. These parameters determine the overall length of time associated with the collected statistic.

Default values for the start time and end time return statistics from the past hour.

The values specified for the start time and end time determine how many periods Amazon CloudWatch will return.

Periods are also important for Amazon CloudWatch Alarms. When creating an alarm to monitor a specific metric, Amazon CloudWatch will compare that metric to a specified threshold value. Customers have extensive control over how Amazon CloudWatch makes comparisons. In addition to the period length, the number of evaluation periods can be specified as well. For example, if three evaluation periods are specified, Amazon CloudWatch compares a window of three data points. Amazon CloudWatch only sends a notification if the oldest data point is breaching and the others are breaching or are missing.

Aggregation

Amazon CloudWatch aggregates statistics according to the period length specified when retrieving statistics. When publishing as multiple data points with the same or similar timestamps, Amazon CloudWatch aggregates them by period length.

Data points for a metric that share the same timestamp, namespace, and dimension can be published, and Amazon CloudWatch will return aggregated statistics for them. It is also possible to publish multiple data points for the same or different metrics with any timestamp.

For large datasets, a pre-aggregated dataset can be inserted called a statistic set. With statistic sets, give Amazon CloudWatch the Min, Max, Sum, and SampleCount for a number of data points. This is commonly used data that needs to be collected many times in a minute.

Amazon CloudWatch doesn’t differentiate the source of a metric. If a metric is published with the same namespace and dimensions from different sources, Amazon CloudWatch treats it as a single metric. This can be useful for service metrics in a distributed, scaled system.

Dashboards

Amazon CloudWatch dashboards are customizable pages in the Amazon CloudWatch console that can be used to monitor resources in a single view. Monitored resources can be in a single region or multiple regions. Use Amazon CloudWatch dashboards to create customized views of the metrics and alarms for AWS resources.

With dashboards, it is possible to create the following:

• A single view for selected metrics and alarms to help assess the health of resources and applications across one or more regions
• An operational playbook that provides guidance for team members during operational events about how to respond to specific incidents
• A common view of critical resource and application measurements that can be shared by team members for faster communication flow during operational events

Percentiles

A percentile indicates the relative standing of a value in a dataset and is often used to isolate anomalies. For example, the 95th percentile means that 95 percent of the data is below this value and 5 percent of the data is above this value. Percentiles help in a better understanding of the distribution of metric data.

Percentiles can be used with the following services:

• Amazon EC2
• Amazon RDS
• Amazon Kinesis
• Application Load Balancer
• Elastic Load Balancing
• Amazon API Gateway

Monitoring Baselines

Monitoring is an important part of maintaining the reliability, availability, and performance of Amazon EC2 instances. Collect monitoring data from all of the parts of an AWS solution to be able to debug any multi-point failures easily.

In order to monitor an environment effectively, have a plan that answers the following questions:

• What are the goals for monitoring?
• What resources need to be monitored?
• How often will these resources be monitored?
• What monitoring tools will be used?
• Who will perform the monitoring tasks?
• Who should be notified when something goes wrong?

After the monitoring goals have been defined and the monitoring plan has been created, the next step is to establish a baseline for normal Amazon EC2 performance.

Measure Amazon EC2 performance at various times and under different load conditions. While monitoring Amazon EC2, store a history of collected monitoring data. Over time, the historical data can be compared to current data to identify normal performance patterns and also anomalies.

For example, if monitoring CPU utilization, disk I/O, and network utilization for your Amazon EC2 instances and performance falls outside of an established baseline, reconfigure or optimize the instance to reduce CPU utilization, improve disk I/O, or reduce network traffic (see Table 9.3).

Alarms and Thresholds

Alarms are designed to be triggered when three things happen:

• A monitored metric has reached a particular value or is within a defined range.
• That metric’s value stays at that value or within the specified range for a number of times in a row in a period.
• The value or range of the metric has been consistent for a number of user-defined periods.

In short, an Amazon CloudWatch Alarm is triggered when a monitored metric reaches a value, is reported multiple times in a row, and stays at that value for a period of time.

In Figure 9.2, the alarm threshold is set to three units and the alarm is evaluated over three periods. The alarm goes to ALARM state if the oldest of the three periods evaluated has matched the alarm criteria and the next two periods have met the criteria or are missing.

In the figure, this happens with the third through fifth time periods when the alarm’s state is set to ALARM. At period six, the value drops below the threshold and the state reverts to OK.

Later, during the ninth time period, the threshold is breached again, but for only one period. Because of this, the alarm state remains OK. Figure 9.2 shows this as a graph.

Alarms can also be added to dashboards. When an alarm is on a dashboard, it turns red when it is in the ALARM state, making it easier to monitor its status.

Amazon CloudWatch Events

Amazon CloudWatch Events delivers a near real-time stream of system events that describes changes in AWS resources. Using relatively simple rules, it is possible to route events to one or more targets for processing.

Think of Amazon CloudWatch Events as the central nervous system for an AWS environment. It is connected to supported AWS Cloud services, and it becomes aware of operational changes as they happen. Then, driven by rules, it sends messages and activates functions in response to the changes.

Amazon CloudWatch Logs

Amazon CloudWatch Logs can be used to monitor, store, and access log files from Amazon EC2 instances, AWS CloudTrail, and servers running in an on-premises datacenter. It is then possible to retrieve and report on the associated log data from Amazon CloudWatch Logs.

Amazon CloudWatch Logs can monitor and store application logs, system logs, web server logs, and other custom logs. By setting alarms on these metrics, notifications can be generated for application or web server issues and can take the necessary actions.

Amazon CloudWatch Logs is made up of several components:

• Log agents
• Log events
• Log streams
• Log groups
• Metric filters
• Retention policies

Log Agents A log agent directs logs to Amazon CloudWatch. AWS does not have effective visibility above the Hypervisor as part of the shared responsibility model. Because of this, agents have to send data into Amazon CloudWatch.

Log Events A log event is an activity reported to the log file by the operating system or application along with a timestamp. Log events support only text format.

Log events contain two properties: the timestamp of when the event occurred and the raw log message.

By default, any line that begins with a non-whitespace character closes the previous log message and starts a new log message.

Log Streams A log stream is a group of log events reported by a single source, such as a web server.

Log Groups A log group is a group of log streams from multiple resources, such as a group of web servers managing the same content.

Retention policies and metric filters are set on log groups—not log streams.

Metric Filters Metric filters tell Amazon CloudWatch how to extract metric observations from ingested log events and turn them into Amazon CloudWatch metrics.

For example, with a metric filter called 404_Error, it will filter log events to find 404 access errors. An alarm can be created to monitor those 404 errors on different servers.

Retention Policies Retention policies determine how long events are retained inside Amazon CloudWatch Logs. Policies are assigned to log groups and applied to all of the log streams in the group.

Retention time can be set from 1 day to 10 years. You can also opt for logs to never expire.

Monitoring AWS Charges

Customers can monitor AWS costs using Amazon CloudWatch. With Amazon CloudWatch, it is possible to create billing alerts that send notifications when the usage of provisioned services exceeds a customer-defined limit.

When usage exceeds these thresholds, AWS can send an email notification or publish a notification to an Amazon SNS topic. To create billing alerts and register for notifications, enable them in the AWS Billing and Cost Management console.

AWS CloudTrail

AWS CloudTrail is a service that enables governance, compliance, operational auditing, and risk auditing of an AWS account. With AWS CloudTrail, it is possible to log, continuously monitor, and retain events related to API calls across an AWS infrastructure.

AWS CloudTrail provides a history of AWS API calls for an account. This includes API calls made through the AWS Management Console, AWS SDKs, command-line tools, and other AWS Cloud services. This history simplifies security analysis, resource change tracking, and troubleshooting.

AWS CloudTrail provides visibility into user activity by recording API calls made on an account. It records important information about each API call, including the name of the API, the identity of the caller, the time of the API call, the request parameters, and the response elements returned by the AWS Cloud service. This information can be used in the tracking of changes made to AWS resources and help troubleshoot operational issues. This makes it easier to ensure compliance with internal policies and regulatory standards.

AWS Config

AWS Config is a fully managed service that provides AWS resource inventory, configuration history, and configuration change notifications to enable security and governance. AWS Config can discover existing AWS resources, export a complete inventory of AWS resources with all configuration details, and determine how a resource was configured at any point in time. These capabilities enable compliance auditing, security analysis, resource change tracking, and troubleshooting.

AWS Config makes it easy to track resource configuration without the need for upfront investments and to avoid the complexity of installing and updating agents for data collection or maintaining large databases. After AWS Config is enabled, continuously updated details can be viewed of all configuration attributes associated with AWS resources. Amazon SNS can be configured to provide notifications of every configuration change.

AWS Config provides a detailed view of the configuration of AWS resources in an AWS account. This includes how resources are related to one another and how they were configured in the past to show how configurations and relationships change over time.

An AWS resource is an entity in AWS such as an Amazon EC2 instance, an Amazon EBS volume, a security group, or an Amazon Virtual Private Cloud (Amazon VPC).

With AWS Config, you can do the following:

• Evaluate AWS resource configurations for desired settings.
• Get a snapshot of the current configurations of the supported resources that are associated with an AWS account.
• Retrieve configurations of one or more resources that exist in an account.
• Retrieve historical configurations of one or more resources.
• Receive a notification whenever a resource is created, modified, or deleted.
• View relationships between resources, such as those that use a particular security group.

Summary

Amazon CloudWatch monitors AWS resources and the applications run on AWS in real time. Use CloudWatch to collect and track metrics, which are variables used to measure resources and applications.

Amazon CloudWatch Alarms send notifications or automatically make changes to the resources being monitored based on customer-defined rules. This monitoring data can be used to determine whether additional instances should be launched in order to handle the increased load or stop under-utilized instances to save money.

In addition to monitoring the built-in metrics that come with AWS, custom metrics can be imported and monitored. Custom metrics can include detailed information about an Amazon EC2 Instance or data from servers running in an on-premises datacenter.

Amazon CloudWatch provides system-wide visibility into resource utilization, application performance, and operational health.

AWS CloudTrail is a service that enables governance, compliance, operational auditing, and risk auditing of an AWS account. With CloudTrail, customers can log, continuously monitor, and retain events related to API calls across an AWS infrastructure.

AWS CloudTrail provides a history of AWS API calls for an account. This includes API calls made through the AWS Management Console, AWS SDKs, command-line tools, and other AWS services. This history simplifies security analysis, resource change tracking, and troubleshooting.

AWS Config is a service that enables customers to assess, audit, and evaluate the configurations of their AWS resources. Config continuously monitors and records your AWS resource configurations and allows the automation of the evaluation of recorded configurations against desired configurations.

With AWS Config, review changes in configurations and relationships between AWS resources, dive into detailed resource configuration histories, and determine the overall compliance against the configurations specified in internal guidelines. This simplifies compliance auditing, security analysis, change management, and operational troubleshooting.

Resources to Review

• The Status Heath Dashboard: http://status.aws.amazon.com/
• Amazon CloudWatch: https://aws.amazon.com/cloudwatch/
• Amazon CloudWatch Logs: http://docs.aws.amazon.com/AmazonCloudWatch/ latest/logs/WhatIsCloudWatchLogs.html
• Amazon CloudWatch Events: http://docs.aws.amazon.com/AmazonCloudWatch/ latest/events/WhatIsCloudWatchEvents.html
• AWS CloudTrail: http://docs.aws.amazon.com/awscloudtrail/latest/userguide/cloudtrail-user-guide.html
• Understanding Your Usage with Billing Reports: http://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/billing-reports.html
• Analyzing Your Costs with Cost Explorer: http://docs.aws.amazon.com/ awsaccountbilling/latest/aboutv2/cost-explorer-what-is.html
• Using AWS Trusted Advisor as a Web Service: https://docs.aws.amazon.com/ awssupport/latest/user/trustedadvisor.html
• AWS Config: https://aws.amazon.com/config/
• Amazon CloudWatch Plugin for collectd: https://aws.amazon.com/blogs/aws/ new-cloudwatch-plugin-for-collectd/

• The AWS Well-Architected Framework: http://d0.awsstatic.com/whitepapers/architecture/AWS_Well-Architected_Framework.pdf
• Troubleshoot a Classic Load Balancer—Response Code Metrics: http://docs.aws.amazon.com/elasticloadbalancing/latest/classic/ts-elb-http-errors.html
• Security at Scale—Logging in AWS: https://d0.awsstatic.com/whitepapers/aws-security-at-scale-logging-in-aws.pdf

Exam Essentials

Be familiar with Amazon CloudWatch. Amazon CloudWatch is a monitoring service for AWS cloud resources and the applications that you run on AWS. You can use Amazon CloudWatch to collect and track metrics, collect and monitor log files, and set alarms.

Amazon CloudWatch can monitor AWS resources such as Amazon EC2 instances, Amazon DynamoDB tables, and Amazon RDS DB instances, as well as custom metrics generated by your applications and services and any log files your applications generate.

You can use Amazon CloudWatch to gain system-wide visibility into resource utilization, application performance, and operational health. You can use these insights to react and keep your application running smoothly.

Amazon CloudWatch Events has three components: Events, Rules, and Targets. Events indicate a change in an AWS environment. Targets process events. Rules match incoming events and route them to targets for processing.

Understand what Amazon CloudWatch Alarms is and what it can do. Amazon CloudWatch Logs lets you monitor and troubleshoot systems and applications using existing system, application, and custom log files.

With Amazon CloudWatch Logs, monitor logs in near real time for specific phrases, values, or patterns. Log data can be stored and accessed indefinitely in highly durable, low-cost storage without filling hard drives.

Be able to create or edit an Amazon CloudWatch Alarm. You can choose specific metrics to trigger the alarm and specify thresholds for those metrics. You can then set your alarm to change state when a metric exceeds a threshold that you have defined.

Know how to create a monitoring plan. Creating a monitoring plan involves answering some basic questions. What are your goals for monitoring? What resources will you monitor? How often will you monitor these resources? What monitoring tools will you use? Who will perform the monitoring tasks? Who should be notified when something goes wrong?

Know and understand custom metrics. You can now store your business and application metrics in Amazon CloudWatch. You can view graphs, set alarms, and initiate automated actions based on these metrics, just as you can for the metrics that Amazon CloudWatch already stores for your AWS resources.

Visibility for metrics above the Hypervisor requires an agent. Amazon CloudWatch can tell you CPU and RAM utilization at the Hypervisor level but it has no way of knowing what specific tasks or processes are affecting performance. CloudWatch can see disk I/O but cannot see disk usage. To do this requires an agent.

Be familiar with what an Amazon CloudWatch Alarm is and how it works. You can create a CloudWatch Alarm that watches a single metric. The alarm performs one or more actions based on the value of the metric relative to a threshold over a number of time periods. The action can be an Amazon EC2 action, an Auto Scaling action, or a notification sent to an Amazon SNS topic.

Know the three states of an Amazon CloudWatch Alarm. These are OK, ALARM, and INSUFFICIENT_DATA. If an alarm is in the OK state, a monitored metric is within the range you have defined as acceptable. If the alarm is in the ALARM state, the metric has breached a threshold. If data is missing or incomplete, it is in the INSUFFICIENT_DATA state.

There are two levels of monitoring: Basic and Detailed. Basic Monitoring for Amazon EC2 sends CPU load, disk I/O, and network I/O metric data to Amazon CloudWatch in five-minute periods by default. To send metric data for an instance to CloudWatch in one-minute periods, enable Detailed Monitoring on the instance. Some services, like Amazon RDS, have Detailed Monitoring on by default.

Amazon CloudWatch performs two types of Amazon EC2 status checks: System and Instance. A System Status Check monitors the AWS systems required to use your instance to ensure that they are working properly. These checks detect problems with your instance that require AWS involvement to repair. An Instance Status Check monitors the software and network configuration of your individual instance. These checks detect problems that require your involvement to repair.

Be familiar with some common metrics used for monitoring. There are many metrics available, and not all of them are tested on the exam. Some are tested, however, and it is a good idea to know the common ones: VolumeQueueLength, DatabaseConnections, DiskQueueDepth, FreeStorageSpace, ReplicaLag, ReadIOPS, WriteIOS, ReadLatency, WriteLatency, SurgeQueueLength, and SpilloverCount.

Know how to set up an Amazon CloudWatch Event subscription for Amazon RDS. Amazon RDS uses the Amazon Simple Notification Service (Amazon SNS) to provide notification when an Amazon RDS event occurs. These notifications can be in any notification form supported by Amazon SNS for an AWS Region, such as an email, a text message, or a call to an HTTP endpoint. Details can be found here: http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/USER_Events.html.

Amazon ElastiCache has two engines available: Redis and Memcached. Memcached is multi-threaded, and Redis is single-threaded.

Know the Amazon EBS Volume Status Checks. Degraded and Severely Degraded performance means that the EBS Volume Status Check is in a Warning state and there is some I/O. Stalled or Not Available means that the EBS Volume is in the Impaired state, and there is no I/O.

Learn the metrics SurgeQueueLength and SpilloverCount. When the SurgeQueueLength is exceeded, spillover occurs. Requests are dropped without notifying end users. Customer experience is negatively impacted.

Exercises

By now you should have set up an account in AWS. If you haven’t, now would be the time to do so. It is important to note that these exercises are in your AWS account and thus are not free.

Use the Free Tier when launching resources. For more information, see https://aws.amazon.com/s/dm/optimization/server-side-test/free-tier/free_np/.

If you have not yet installed the AWS Command Line utilities, refer to Chapter 2, “Working with AWS Cloud Services,” Exercise 2.1 (Linux) or Exercise 2.2 (Windows).

The reference for the AWS CLI can be found at http://docs.aws.amazon.com/cli/latest/reference/.