Monitoring and Troubleshooting Serverless Applications

Serverless monitoring is a widely used service that helps businesses monitor, build, and optimize serverless applications. Serverless monitoring's event-driven architecture (EDA) necessitates monitoring tailored to this context. Serverless monitoring employs recognized metrics to alert teams to problems.

What is Serverless?

Serverless is the model of application development and execution that helps developers run apps and execute code without managing servers or backend infrastructure. In essence, a company receiving serverless backend services from a vendor is charged depending on their computation. This means one does not need to reserve and, in turn, pay for a predetermined amount of bandwidth or number of servers since it is in self-scaling. Note that, despite the terminology, real servers are still used, although developers need not be aware of them.

How Does Serverless Monitoring Work?

• Serverless monitoring solutions collect data from your complete serverless infrastructure, compile resource usage statistics, and provide logs and analytics.
• Serverless monitoring also allows you to view serverless function activity, track resource utilization and set up automated alerts to provide actionable insights.
• The dashboards may reduce blindspots by monitoring function health and memory utilization, as well as identifying application bottlenecks.

Why Is Serverless Monitoring and Troubleshooting Important?

• Serverless monitoring enables developers to handle significant performance issues that affect system health and user experience in serverless computing.
• With serverless, the cloud provider manages servers, allowing your developers to focus on running code.
• Although this has many benefits, it implies that organizations have less control and visibility over their settings. As a result, discovering defects or issues can be challenging.
• Serverless monitoring is an important tool for ITDM and BDM to track serverless costs.

How to Monitoring and Troubleshooting Serverless Applications

Below is the step-by-step procedure to monitor and troubleshoot serverless applications:

Step 1: Use Metrics Collection

First, It provides a list of all Lambda functions in your AWS account, including function names, ARNs, and runtime, among other basic details.

aws lambda list-functions --output table

Output:

Step 2: Add Invocation Metrics

You can specify a function name and the required time range instead of and since this returns the total count of invocations for a Lambda function.

aws cloudwatch get-metric-statistics --namespace AWS/Lambda --metric-name Invocations --dimensions Name=FunctionName,Value=<FunctionName> --statistics Sum 
--start-time <start-time> --end-time <end-time> --period 300

Output:

Step 3: Turn on Amazon X-Ray Tracing

Then, you use the AWS Management Console or CLI to enable tracing.

aws lambda update-function-configuration --function-name <FunctionName> --tracing-config Mode=Active

Output:

Step 4: Make Alerts and Notifications

When Lambda function failures surpass a given threshold, the below command triggers an alarm to sound.

aws cloudwatch put-metric-alarm --alarm-name HighErrorRate --alarm-description "Alarm when error rate exceeds threshold" --metric-name Errors --namespace AWS

Output:

Step 5: Handle Errors

Function name, runtime, role, handler, memory size, timeout, and last changed time are among the details displayed for Lambda functions in the below command.

aws lambda list-functions --query 'Functions[*].[FunctionName,Runtime,Role,Handler,MemorySize,Timeout,LastModified]' --output table

Output:

Step 6: Configure and Deployment Issues

You can manage deployments and customizations with the aid of this command, which lists all versions and aliases of a Lambda function.

aws lambda list-versions-by-function --function-name <FunctionName>

Output:

Step 7: Check Security Issues

Lastly, you have to check a Lambda function's security configuration and permissions by retrieving its resource-based policy.

aws lambda get-policy --function-name <FunctionName>

Output:

Best Practices for Monitoring Serverless Applications

• Visualizing Data: It will track performance data and metrics, and custom dashboards can be set up for a view of all performance data and metrics in one location.
• Advanced techniques: Leverage AI-powered advanced analytics can evaluate historical data and accurately forecast future trends.
• Configuring alerts: Setting threshold alerts for crucial metrics such as invocation errors, concurrency, memory use, and so on allows you to monitor your apps and resources more proactively.

Conclusion

In conclusion, Serverless monitoring is a crucial part of overall observability. Serverless observability improves insight into system outputs, allowing concerned teams to identify and resolve possible concerns more effectively.

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Article Tags :

• Amazon Web Services
• DevOps
• AWS