Operations | Monitoring | ITSM | DevOps | Cloud

In this post we will discuss some key considerations and strategies to monitor your AWS Lambda functions. This will include: which Lambda metrics you’ll want to monitor, how to collect AWS Lambda metrics with Prometheus and Logz.io, how to create a monitoring dashboard with alerts, and how to search and visualize your metrics.

When we launched Qovery in January 2020, our product was only supporting app deployment on Amazon Web Services (AWS). 20 months later, 5534 developers from more than 120 countries use Qovery to deploy their apps on AWS and Digital Ocean. Today, more and more European companies would love to benefits from the excellent user experience of Qovery on a European cloud service provider 🇪🇺.

More and more cloud providers are emerging and spreading their business across different regions in the current times. As a result, customers want to reduce their IT workload and migrate their product or application to a cloud-based environment. The primary reason behind this is that the cloud heavily reduces the overheads of investing in IT infrastructure, hardware upgrades, maintenance, etc.

Being alerted to an issue with your application before your customers experience undue interruption is a goal of every development and operations team. While methods for identifying problems exist in many forms, including uptime checks and application tracing, alerts on logs is a prominent method for issue detection. Previously, Cloud Logging only supported alerts on error logs and log-based metrics, but that was not robust enough for most application teams.

AWS Step Functions is a powerful orchestration service that lets you model even the most complex business workflows. It packs a great visualization tool (which you can also use to design your workflows visually now!) and can integrate with many AWS services directly, including Lambda, DynamoDB, and API Gateway. It’s one of my favorite AWS services and I often use it to model complex or business-critical workflows.