How to monitor and manage your AWS resources using CloudWatch

AWS CloudWatch is a native service of the Amazon Cloud ecosystem that logs and monitors all other services within Amazon Cloud. Collect and track metrics or log files and set alarms on various activities extracted from them.

Gain system-wide visibility into application performance, resource utilization, and service operational status. You can also use AWS CloudWatch to detect abnormal behavior in your environment, take automated actions, troubleshoot issues, and find insights from your logs to make changes to your systems and operations for the better. You can also perform actions to

Monitoring logs can help detect security threats and identify potential vulnerabilities. Monitoring for suspicious activity or anomalous behavior allows you to respond to suspicious activity and take steps to prevent future attacks.

Additionally, log maintenance and system monitoring are often required activities for compliance purposes. With AWS CloudWatch, you meet these requirements.

These are all direct benefits of using AWS CloudWatch. So let’s see how to get started with all this.

Set up AWS CloudWatch for your service

Your setup can be simple and straightforward, or you can spend weeks tweaking every aspect and property of your logging and monitoring system and still not be completely done (basically, turn this into a life-improving system). process).

But in short, you can get started like this:

1. Assuming you already have an AWS account, go to the CloudWatch console and click the Get Started button to enable CloudWatch.
2. Create a log group to start collecting logs for your service. A log group is a collection of log streams that share the same retention, monitoring, and access control settings. You can create a log group by clicking the Create Log Group button in the CloudWatch console.
3. Create log streams to focus log events to the same source (service). You can create a log stream by clicking the Create Log Stream button in the CloudWatch console.
4. If you want to collect logs from your EC2 instances, install the CloudWatch agent. An agent is software that runs on your instances and sends log data to CloudWatch. You can install the agent using AWS Systems Manager or by running a script on your instance.
5. Create a metric filter to extract metrics from your logs based on a defined match pattern. You can create a metric filter by clicking the Create Metric Filter button in the CloudWatch console.
6. Finally, collect and visualize all extracted data in one place to create a dashboard. A dashboard is a collection of widgets that display metrics and other data that you place on it. You can create a dashboard by clicking the Create Dashboard button in the CloudWatch console.

Monitoring with AWS CloudWatch

As mentioned earlier, you can use AWS Cloudwatch to monitor any service in Amazon Cloud. To provide a more detailed explanation of how such monitoring is done, here’s how to do it for the most common AWS services you’re likely to use in your systems.

EC2 instance

You can monitor your EC2 instances by collecting metrics such as CPU usage, network traffic, disk usage, and memory usage. You can also monitor the status of your EC2 instances and receive notifications when your instances are stopped or terminated.

To monitor your EC2 instances, install the CloudWatch agent on your instances and configure them to send metrics to CloudWatch. As a next step, you can create an alarm to alert you when a metric crosses a certain threshold.

RDS database

You can monitor your Amazon RDS database by collecting metrics such as database CPU usage, memory usage, and disk usage. You can also monitor the status of your database and receive notifications when it is stopped, paused, or terminated.

To monitor your RDS database, enable enhanced monitoring and configure it to send metrics to CloudWatch. Again, you can create an alarm to alert you when a metric goes off.

lambda function

You can monitor your AWS Lambda functions by collecting metrics such as Lambda invocation count, duration, and error rate. You can also monitor the status of your functions and receive notifications if a function fails.

To monitor your Lambda function, you must enable CloudWatch Logs and configure your function to send logs to CloudWatch. You can then create metric filters to extract metrics from your logs and take actions based on the information extracted from your logs.

Elastic Load Balancer

Monitoring your Elastic Load Balancer is done by collecting metrics such as number of requests, latency, and HTTP response codes. You can also monitor the status of your load balancer and receive notifications if your load balancer fails.

To monitor your load balancer, you must enable access logging and configure your load balancer to send logs to CloudWatch. You can then create metric filters to extract metrics from your logs and create alarms when metrics deviate from a defined normal state.

Auto Scaling Group

You can monitor your Auto Scaling group by collecting group size, CPU usage, and network traffic. You can also monitor the status of your group and receive notifications when your group scales up or down.

To monitor your Auto Scaling group, you must enable detailed monitoring and configure it to send metrics to CloudWatch. You can then create alarms to alert you when metrics cross certain thresholds.

Elastic Beanstalk applications

You can monitor your AWS Elastic Beanstalk applications by collecting metrics such as CPU usage and number of requests. You can also monitor the status of your application and receive notifications when it fails.

To monitor your Elastic Beanstalk application, you must enable enhanced health reporting and configure it to send metrics to CloudWatch. You can then create alarms to alert you when metrics exceed predefined thresholds.

Managing CloudWatch alarms

There are key metrics and CloudWatch alarms available for each service. These can be preconfigured according to best practices and can be used to troubleshoot any issues that arise.

By effectively managing alarms, you can be alerted to critical issues and take appropriate actions to maintain the health and performance of your AWS resources and applications.

#1. Setting alarms for metrics

To set up an alarm, first select the metric you want to monitor. Then create an alarm based on that metric by specifying thresholds and comparison operators.

For example, you can create an alarm that triggers when CPU usage exceeds 80% for more than 5 minutes. After you create an alarm, set the action to take when the alarm is triggered. For example, you can send email to a specific list of recipients, send SMS notifications, or even scale up system resources.

#2. Configuring alarm actions

When setting up an alarm action, you can choose from a variety of options, including sending a notification to an SNS topic, triggering an AWS Lambda function (you can do whatever you want the function to do within a Python script), and stopping it. Or terminate your EC2 instance.

You can also set multiple actions for each alarm and perform different actions depending on the severity of the alarm. For example, send an email notification for a minor alarm, but terminate the instance for a major alarm.

#3. Alarm best practices

It’s always good to follow best practices to ensure your alarms are effective and reliable. Some best practices include:

• Set appropriate thresholds based on historical data,
• Detect issues using multiple metrics in parallel
• Test your alarm regularly to ensure that it is working properly.

Avoid creating too many alarms, as creating too many alarms can lead to alert fatigue, clutter your monitoring system, and make it difficult to actually identify the truly critical issues. please.

If you run into issues with your CloudWatch alarms, there are several troubleshooting steps you can take.

• Check the alarm history to see if any actions were taken when the alarm was triggered.
• Check your metric data to see if there are any anomalies or spikes that might have triggered an alarm.
• If the issue persists, you can adjust the alarm thresholds or add metrics to the alarm to improve accuracy.

Analyze and visualize metrics using CloudWatch dashboards

Analyzing and visualizing metrics through dashboards provides easy-to-read insights into the health and performance of your AWS resources and applications. CloudWatch dashboards provide customizable views of your metrics.

You can place various charts, graphs, and other visualizations there to show trends over time and highlight potential problems with your system. The ultimate goal is to be able to extract important information from log file data and provide it in a format that is easier to read and use for those who want to review and monitor system health.

To create a CloudWatch dashboard, you can use the CloudWatch console or the CloudWatch API. Then, just add widgets to your dashboard that display the metrics you want to see on your dashboard. You can also add text and images to provide context and additional information.

Once you create a dashboard, you can customize it to suit your specific needs. You can resize and rearrange widgets, change the time range of data displayed, and add annotations to highlight important events and changes. You can also share your dashboard with other users so they can see the same metrics and visualizations.

Finally, you can easily deploy the same dashboard to different AWS accounts and environments.

Log collection and analysis

Analyzing logs typically means using CloudWatch’s Logs Insights feature.

After you collect log data with CloudWatch Logs, you can start using Logs Insights. CloudWatch Logs Insights allows you to query and visualize your log data using a simple and powerful query language. It is very similar to the SQL selection language, but not exactly the same. However, the results are very similar.

Insights allows you to search for specific log events, filter log data based on specific criteria, and create visualizations such as charts and tables. This provides additional valuable insight into the behavior of your applications and infrastructure, which you can use to troubleshoot issues, optimize performance, and improve security.

Related article: How to query dashboard metrics from AWS service logs using AWS Logs Insights

Automate tasks using CloudWatch Events

When you have enough log data information in CloudWatch, you can use it to trigger actions based on events that occur in your AWS resources or applications. CloudWatch Events provides a way to schedule and automate tasks, such as starting or stopping an EC2 instance whenever the instance’s utilization exceeds its normal usage zone (for example, stopping an instance overnight and stopping it during the business day). (start again).

To automate tasks with CloudWatch Events, you create rules that specify event patterns to match and actions to take when the event occurs. You can do this using the CloudWatch console or the CloudWatch Events API. Next, configure one or more targets for the rule, such as an AWS Lambda function, SNS topic, or EC2 instance.

CloudWatch Events supports a wide range of event sources, including AWS services, custom applications, and third-party services. So whenever you need to scale resources, trigger backups, or respond to security incidents, you can use CloudWatch Events to automate the task.

Automating tasks reduces manual intervention on your systems and ensures that your AWS resources and applications are always running at optimal levels.

Advanced CloudWatch features

There are several advanced CloudWatch features that you can configure to gain deeper insight into your AWS resources. One of them is the log insight that I mentioned earlier. Some of the other important advanced features are listed below.

• CloudWatch Contributor Insights can identify the top contributors of resource utilization, such as EC2 instances and Lambda functions. Contributor Insights allows you to identify the most resource-intensive operations and optimize your resources accordingly.

• CloudWatch Anomaly Detection uses machine learning algorithms to automatically detect anomalous behavior in your metrics. Use anomaly detection to identify abnormal spikes or dips in metrics and take action to address them.

• CloudWatch Synthetics can create canaries that simulate user behavior and test the availability and performance of your applications. Use Synthetics to proactively investigate and detect problems before business users do.

• CloudWatch Logs Insights Query Acceleration speeds up log queries by up to 10x. Query Acceleration allows you to analyze large amounts of log data quickly and efficiently.

Integrating CloudWatch with AWS services

When building an AWS system, Clodwatch integration should always be at the top of your list. Only with this tight integration can you collect and monitor metrics and logs across all services or system components. It’s also easy to set up and use, and integration is native to most AWS services. So there’s little excuse not to take advantage of this benefit with AWS cloud systems.

Gain comprehensive visibility into your AWS resources and applications and monitor their health, performance, and availability. Once all the information is collected, simply use your existing data to set up alarms and automate tasks based on events that occur in your AWS environment.

last word

AWS CloudWatch is a comprehensive cloud service that can cover all your project logging, monitoring, and system status visualization needs.

Including such components in your architecture is exactly how you proactively manage your system and ensure reliability. We recommend starting building a robust monitoring system from Sprint 1 rather than prioritizing it at a later phase. You’ll find out later.

Then check out the best AWS monitoring tools.