Monitoring Performance for AWS Lambda
Tags: aws, monitoring, performance, devjournal
Published: 2021-10-13 15:54:49

> Monitoring AWS Lambda performance helps you identify any issues, and it can also send you alerts and notify you of anything you might need to know. The world is slowly getting to a point where machines and computers will be flawless, but until then, if we let them perform various tasks for us, we could at least monitor their performance.

Monitoring your AWS Lambda functions is an important aspect of ensuring the stability and reliability of your application. By keeping track of key performance indicators (KPIs) and monitoring for potential issues, you can proactively identify and fix problems before they affect your users.

Below the top 5 AWS Lambda monitoring tools:

**1. Datadog**

[Datadog](https://www.datadoghq.com/) provides the unity of metrics, logs, and traces. Aggregating events and metrics from more than 200 technologies such as Amazon Web Services, MongoDB, Slack, Docker, Chef, and many others. Datadog also explores enriched data, searches and analyzes log data while tracing requests across the distributed systems, and alerts you on app performance.

**2. Dashbird**

[Dashbird](https://dashbird.io/) is excellent in providing error alerts and also in monitoring support. Dashbird collects and analyzes CloudWatch logs while zeroing the effects on your AWS Lambda performance. Integration with the Slack account is also possible, and that brings alerts about early exits, crashes, cold starts, timeouts, runtime errors, etc., to your development chat. Dashbird’s error diagnostics, advanced log searching, and function statistics are only a few of the benefits Dashbird offers to its users.

**3. Logz**

[Logz](https://logz.io/) offers ELK service the best choice for scaling and performance with ease while there’s no need to perform upgrades or capacity management. Logz.io security is enterprise-grade, and it keeps your data private and secure while also complying with key industry standards. Logz.io goes way beyond the ELK service to provide an Enterprise-Class log analytics platform consisted of features like integrated alerts and multiple sub-accounts.

**4. Thundra**

[Thundra](https://www.thundra.io/) started as a serverless monitoring platform but later switched to targeting more general services. While they’re still a good choice for serverless systems, their tools can now be used for containers and virtual machines too.

**5. Lumigo**

[Lumigo](https://lumigo.io/) offers visual debugging, and it also comes with tracing, metrics, and alert support, but, differing from Thundra, it is more focused on serverless monitoring, from the architecture down to function logs and traces. Lumigo also comes with a Lambda Layer/Extension for Python and Node.js runtimes to instrument Lambda functions.

In conclusion learning about how to approach the serverless monitoring architecture will for sure make your life (and work) much easier. With a proper understanding of the AWS infrastructure, you are one step closer to a new skill called “observability” regarding the lambda functions. The price is set, but it’s a small one compared to the lambda function benefits you’ll obtain.

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