Technology

Why Monitoring AWS is Important?

Monitoring AWSImage Source: eginnovations

What is AWS Monitoring?

Monitoring is the collection, analysis, and use of data to track various systems. Amazon Web Services (AWS) monitoring collects data from your AWS resources and applications to ensure that everything is running smoothly and securely. Monitoring your AWS infrastructure aids in the detection of vulnerabilities and issues, the prediction of performance, and the optimization of configurations. This practise collects, analyses, and presents data insights using a variety of AWS monitoring tools and services.

What is AWS & How It Works
What is AWS & How It Works

AWS monitoring vs observability

The distinction between monitoring and observability is frequently debated in the DevOps community. Monitoring is the process of collecting, analysing, and utilising data to track various systems. On the other hand, observability uses all of the data from logs, metrics, and traces to assist development teams in detecting and resolving any issues. Observability is concerned with comprehending the context of all metrics and the internal state of your infrastructure.

Monitoring is simply the capture and display of data, whereas observability is the understanding of system health through inputs and outputs.

Why is AWS Monitoring Necessary?

Proactive monitoring and rapid diagnosis are the key

Most organisations that deploy cloud applications require proactive monitoring and rapid diagnosis. Every minute that your application is down or slow costs your company money. If your applications do not perform well in the cloud, you may need to migrate them back to on-premises infrastructure. After all, end users are concerned with application performance, not where the application is hosted or what infrastructure it employs.

Save money by Right-sizing 

AWS monitoring must also focus on gathering enough information to quickly diagnose problems. After all, if a problem takes hours to diagnose and resolve, it has an impact on both revenue and user satisfaction. AWS monitoring collects a wealth of metrics, which can provide insights for right-sizing AWS infrastructures. Unlike on-premises infrastructure, right-sizing on the AWS cloud can result in immediate cost savings.

Dynamic, autoscaling environments across hybrid/multi-cloud

AWS environments are typically elastic and dynamic. Consider a task-processing system in which tasks are queued and processed by EC2 instances. You might want to have the number of EC2 instances scale dynamically based on the number of tasks in the queue. New EC2 instances and containers (for example, Docker orchestrated by Kubernetes) can appear and disappear across on-premises and multi-cloud environments.

In such cases, you must have visibility into how many instances were spun up or down, as well as whether or not the health improved as a result of the automated scaling. As a result, monitoring systems should automatically detect, instrument, and manage new compute instances as they appear and disappear.

What Should Engineering Teams Monitor in AWS?

You can learn about the right metrics to monitor by following the AWS Well-Architected Framework pillars. Pointers include measuring metrics, logs, and traces to aid in optimization:

  • Performance effectiveness
  • posture of security
  • Cost reduction
  • Reliability
  • Excellence in operations

Here are some AWS resources that your engineers should keep an eye on.

  •  Status check – Displays detailed information about problems that may affect each of your EC2 instances. 
  • CPU utilisation is the percentage of allocated compute units that you use. It can assist you in determining whether a CPU is under- or over-utilized, revealing whether it is a performance bottleneck.
  • Memory utilisation – Tracks memory usage across all AWS services. Consistently high memory usage, for example, may indicate that you need to increase your memory allocation to improve performance.
  • Disk utilization – Assesses whether your node’s storage capacity can support your workload based on its disk volume.  
  • Latency – It refers to the time it takes a cloud provider to respond to a customer request. If you’re experiencing high latency, it could be due to network connectivity, web server dependencies, or backend servers. As a result, the performance of your application may suffer, and your AWS costs may rise. 
  • Swap usage – Describes the amount of disc space dedicated to storing data that should be in memory. High swap usage degrades application performance, which defeats the purpose of in-memory caching. Proactively look into it to make sure that doesn’t happen.
  • AWS Cost Anomaly Detection – Aids in the real-time monitoring of unusual spending to reduce unexpected costs. 
  • Metrics for security – Potential security issues include the following: 
    • Several instances that begin and end programmatically 
    • Temporary security credentials with a long lifespan
    • Activity that wipes out CloudTrail logs 
    • A new user account with the ability to delete multiple users.

Custom metrics can also be used for items that are not covered by native AWS monitoring tools. CloudWatch, for example, does not show default memory utilisation metrics. It does, however, support additional AWS monitoring scripts for this purpose.

 Scripts enable you to report on a variety of metrics, including memory used/available/utilization, disc used/available/utilization, and swap space used/utilization.

AWS Monitoring Best Practices

The following best practises for monitoring AWS resources can help you ensure that no resources are overlooked and that you can troubleshoot efficiently.

Use automation wherever feasible.

AWS production deployments are typically too large and dynamic to manually monitor. The volume of metrics and log data generated is too large for humans to analyse efficiently. To ensure that critical data is not missed and responses are delivered on time, you should automate the majority of your monitoring tasks.

Establish Policies to Define Priority Level

Prioritizing monitoring tasks helps to ensure that critical services continue to operate and data is protected. Prioritizing alerts or alert categories also helps IT teams distribute their time and efforts more effectively.

Early Problem Resolution

Monitoring data should be used to respond proactively to issues such as potential service interruptions. It is far easier to scale resources or throttle traffic ahead of time than it is to manage a service outage. Addressing potential issues early on can also help you avoid wasting resources and money.

Take Advantage of the Cloud

Cloud environments are adaptable, allowing you to experiment with configuration changes without disrupting services. Take the time to test your configurations when optimising based on metrics. This allows you to test whether changes are more efficient before implementing them in production.

To lay a strong foundation for automation, you should first implement the AWS monitoring best practices we discussed here.

The Amazon Web Services monitoring checklist is not exhaustive. However, if you use these best practices and tools, you will be able to prevent minor issues from quickly becoming major, costly problems.

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the authoraddison
Addsion Is a Blogger and an SEO professional. Co-founder of dsnews.co.uk, I have 2 years of experience in SEO & 1 year of Successful blogging @ dsnews.co.uk. I have a passion for SEO & Blogging, Affiliate marketer & also interested to invest on profitable stocks.

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