Monitoring platform for keeping systems up and running at all times.
Full stack visibility across the entire stack.
Detect and resolve any incident in record time.
Conform to industry best practices.
One of the serverless best practices is one-purpose functions. You should keep your Lambda functions small and solve exactly one use-case. This way, you can optimize them better and keep potential security problems contained. But creating many small functions can get overwhelming quickly. Even small projects can end up with more than 20 Lambda functions.
If your serverless systems get bigger with time and solve more and more use-cases, you tend to have multiple sub-systems that use multiple Lambda functions. This makes it rather hard to stay on top of things in terms of monitoring. You want to know what your whole system does, but you also want insight into your sub-systems. You don’t want one sub-system monitoring data to get mixed up with other sub-systems monitoring data.
As a solution to this problem, Dashbird offers Project Views.
Project Views are a way to group your Lambda functions freely, to get a metrics dashboard just for this group.
You are completely free to assign which Lambda functions will be tracked by one project view. This allows you to group by sub-systems, but it also allows you to group by purpose. You could, for example, create a project view for all your Lambda functions that integrate with third-party APIs to monitor the stability and performance of your external integrations on a cross-project.
If you look at the Dashbird app menu, you find Project Views in the Dashbird console’s sidebar.
When navigating to the Project Views, you can create groups of Lambda functions called projects.
For demonstration purposes, I deployed two of the CDK example projects. Each of them has at least one Lambda function. Since these projects have nothing to do with each other, it’s a good idea to split them into two projects. You can see in the below example how to create a new project and how to add Lambda functions.
The project requires a unique title that must not include special or whitespace characters. I selected the five Lambda functions of the API Lambda CRUD example and added it to the list of Tracked Lambdas.
Next, I create a project for my second deployment, the Cognito Protected API. The next example shows how I chose to configure it.
After the creation, I have two projects in the Project Views list, as shown in the below example. These can be selected and even directly linked to. This way, the dashboard is filtered for each of these Lambda functions.
Dashbird’s Project Views is an easy way to split the mass of Lambda functions. Group them per project or group them in any other way that makes sense for your business.
This way, you can stay up-to-date on different parts of your applications without getting overwhelmed by looking at everything at once.
You can try it out yourself with Dashbird for free:
Further reading:
Log-based monitoring for AWS Lambda
Best practices for logging in AWS Lambda
Why AWS Console isn’t the best for serverless debugging?
Today we are announcing a new, updated pricing model and the end of free tier for Dashbird.
In this article, we’re covering 4 tips for AWS Lambda optimization for production. Covering error handling, memory provisioning, monitoring, performance, and more.
In this article we’ll go through the ins and outs of AWS Lambda pricing model, how it works, what additional charges you might be looking at and what’s in the fine print.
Dashbird was born out of our own need for an enhanced serverless debugging and monitoring tool, and we take pride in being developers.
Dashbird gives us a simple and easy to use tool to have peace of mind and know that all of our Serverless functions are running correctly. We are instantly aware now if there’s a problem. We love the fact that we have enough information in the Slack notification itself to take appropriate action immediately and know exactly where the issue occurred.
Thanks to Dashbird the time to discover the occurrence of an issue reduced from 2-4 hours to a matter of seconds or minutes. It also means that hundreds of dollars are saved every month.
Great onboarding: it takes just a couple of minutes to connect an AWS account to an organization in Dashbird. The UI is clean and gives a good overview of what is happening with the Lambdas and API Gateways in the account.
I mean, it is just extremely time-saving. It’s so efficient! I don’t think it’s an exaggeration or dramatic to say that Dashbird has been a lifesaver for us.
Dashbird provides an easier interface to monitor and debug problems with our Lambdas. Relevant logs are simple to find and view. Dashbird’s support has been good, and they take product suggestions with grace.
Great UI. Easy to navigate through CloudWatch logs. Simple setup.
Dashbird helped us refine the size of our Lambdas, resulting in significantly reduced costs. We have Dashbird alert us in seconds via email when any of our functions behaves abnormally. Their app immediately makes the cause and severity of errors obvious.