AWS X-Ray vs. CloudWatch

In today's tech-driven world, customers demand low-latency, high-performing applications, and giving top-notch experience is critical for business success.

Therefore, it's essential to have a solution that can effectively monitor the application's performance and the infrastructure that supports them.

You must be wondering why we're going to discuss AWS X-Ray vs. CloudWatch while there're numerous on-premises monitoring solutions. Why not leverage them?

That's because those monitoring tools support a small fraction of overall architecture. It's highly complicated to pinpoint the root cause of problems and correlates those issues with the end user's experience. Besides, those solutions aren't optimized for hybrid clouds.

When you're running applications with AWS (Amazon Web Services) on a hybrid cloud, you need a monitoring approach that can help you gain robust visibility across complex hybrid environments.

Let's discuss the top 2 leading solutions that AWS offers (AWS X-Ray and CloudWatch) to ensure all application services are working correctly and will be able to handle the failure events effectively.

What is AWS X-Ray?

Many firms that are running applications in a hybrid environment are improving development practices by implementing microservices or serverless architectures.

It helps them build high-quality applications at a low cost and fast pace. That's where AWS X-Ray comes in.

It's a distributing trace monitoring tool that helps developers analyze and debug all kinds of applications, even those that run on serverless architecture.

Moreover, it detects issues within the application, whether they're in a production or development phase.

What is AWS X-Ray used for?

AWS X-Ray is used to determine how well the application and its underlying services function to identify and troubleshoot the leading cause of performance errors.

Plus, it also enables DevOps engineers and developers to understand what's impacted and to how much extent.

Customers' accounts also run a variety of applications and workflows. It's crucial to examine each one separately to identify any performance bottlenecks that might be harming end users.

To address this, AWS X-Ray lets users segment their X-Ray service graph and concentrate on specific applications and workflows.

How does AWS X-Ray Work?

1. Gather traces

It collects the required data from the application's services. To do an end-to-end trace, an HTTP header is added. Later, this header is transmitted to further tiers of request handlers.

2. Record traces

It combines all the collected data into a single unit named trace, which spans from the beginning to the end of the application overflow.

3. Observe service map

Using trace data, X-Ray develops service maps that the application uses. This visually represents the connections between the application's services and the gathered data for each service.

4. Inspect issues

Developers can now go deeper into the service to see precisely where and what problem occurs because traces are gathered and organized into a service map.

Developers will be able to spot performance issues, detect high latency areas, and see the frequency of errors.

What are the benefits of AWS X-Ray?

Start right away

By integrating the software development kit (SDK) with your application and installing the AWS X-Ray agent, you can quickly start monitoring applications running on Amazon EC2, Amazon EKS, Amazon Elastic Beanstalk, and Amazon Lambda.

Provide in-depth application visibility

AWS X-Ray employs tracing to monitor requests across the entire application, collecting information on cloud resources and services that make up the applications.

This gives developers a robust view of application performance. This improves the understanding of how the applications operate and makes it simpler to identify the underlying cause of problems encountered.

Enhance user experiences

It digs deeper into trace data with service maps, which provide a thorough overview of the services that make up your apps, how they're connected, and the data they collect.

You can detect performance bottlenecks using this view to enhance end-user experiences.

Allows annotating and filtering data

When specific components or services within an application emit data, AWS X-ray allows you to add annotations to that data. This can be used to append business-specific metadata that aid in problem diagnosis.

You can also browse and filter data for traces by attributes like annotation value, HTTP response status, average latencies, timestamps, and more.

Allows latency detection of server and client-side

Using AWS X-Ray, you can visually spot node and edge latency distribution promptly from the service map. To quickly identify performance issues affecting your application and end users, you can isolate outliers, delve into traces, graph trends and patterns, and filter and custom annotations and built-in keys.

Now that we've understood the basic concepts, working procedures, and benefits of AWS X-Ray, let's delve right into AWS CloudWatch so we can compare AWS X-ray vs. Cloudwatch.

What is Amazon CloudWatch?

Amazon CloudWatch lays the foundation for effective monitoring in your hybrid cloud architecture. CloudWatch, a native to AWS, lets you keep an eye on the functionality and efficiency of the cloud resources supporting the applications.

It can be challenging to properly comprehend your new cloud resources in the early phases of AWS adoption. Amazon CloudWatch makes this straightforward through AWS cloud service's automatic monitoring while also providing extensive visibility into your vital applications.

With deeper functionality, you can benefit from the cloud's agility and cost-effectiveness.

What is Amazon CloudWatch used for?

Amazon CloudWatch provides actionable insights to manage resource utilization, optimize application performance, and determine the operational health of the entire system.

You can also monitor the entire stack, including applications, network, infrastructure, and services. It also enables you to use event data, logs, and alarms to take automated actions and minimize MTTR (Mean Time To Resolution).

Besides that, metrics and log data are visible in CloudWatch for up to one second and allow you to perform metrics calculations. You can do historical analysis for cost optimization and gain real-time insights on how to best utilize infrastructure and application resources.

How does AWS CloudWatch work?

1. Monitor and resolve infrastructure problems

It monitors the container ecosystem throughout Amazon EKS, AWS Fargate, Kubernetes, and Amazon ECS (Elastic Container Service) to determine the actual cause of performance issues in the company's AWS resources.

2. Enable robust resource optimization

Its alarms keep an eye on the metrics values compared to thresholds that are either set by the user or CloudWatch using machine learning models to identify anomalous activity.

AWS CloudWatch can take immediate action to activate Amazon EC2 Auto Scaling or terminate an instance in the case when an alarm is raised.

3. Analyzes the log

To address the operational issues, CloudWatch discovers, analyzes, and visualizes the logs, ultimately boosting the application's performance.

If a problem arises, the user can immediately start inquiring about addressing operational challenges efficiently.

What are the benefits of Amazon CloudWatch?

Simple to monitor AWS cloud services

Built-in integrations provide you extensive insight into the cloud resources sustaining your applications.

For more than 70 AWS cloud services, such as Amazon DynamoDB, Amazon Elastic Compute Cloud (Amazon EC2), and Amazon Elastic Block Store (Amazon EBS), Amazon CloudWatch automatically generates one-minute metrics.

Utilize precise, custom application metrics

Using a straightforward API request, you can track precise custom metrics with a granularity of up to one second to support your custom applications.

The AWS Management Console then allows for the visualization of these KPIs.

Enhance the user experience automatically

By implementing high-resolution alarms that activate when metrics deviate from the specified threshold and setting these alarms to activate AWS Lambda functions, you can automate corrective action that enhances the end-user experience while only utilizing the resources you require at the time of need.

Allows to respond to resource changes immediately

You can write rules to specify which events are relevant to your application and what automated action to perform when the rule matches an event.

For instance, you can send an Amazon SNS message, stop an Amazon EC2 instance, and add a message to an Amazon SQS queue when a particular event of interest occurs.

Robust compliance and security

CloudWatch is integrated with AWS IAM (Identity and Access Management) to allow you to gain control over which resources and users are authorized to access the data and how they can access it.

You can also specify data protection policies to protect sensitive data against potential threats. This feature automatically detects and hides information using pattern matching and machine learning based on your defined policy.

Conclusion

As we have discussed multiple aspects of AWS X-Ray and AWS CloudWatch, you might be wondering which you should go for, AWS X-Ray vs. AWS CloudWatch.

Let's not forget that AWS X-Ray is a solution that helps developers determine and debug any distributed application. It's much easier with AWS X-Ray to identify the leading cause of encountered issues by highlighting only the problematic section of the entire application.

However, CloudWatch serves as a foundation for AWS infrastructure management. It provides an efficient mechanism for collecting and storing logs and metrics.

It aggregates and outlines compute utilization information such as network data, memory, disk, CPU, and diagnostic information like container restart failures to help developers isolate and solve issues quickly.

In summary, AWS X-Ray is focused on providing detailed information about the performance of an application. In contrast, Amazon CloudWatch is focused on providing data and metrics for monitoring AWS services' overall health and performance.

Using both for hybrid cloud monitoring gives organizations a comprehensive view of the entire environment.

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