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.
If you are running Python on AWS Lambda, you can catch and get alerted for all errors with Dashbird.
Dashbird detects the following types of errors
Errors are detected and parsed Python exceptions and runtime errors from CloudWatch logs, meaning that developers do not need to attach any agents inside their code.
In addition, with each error, you get the context. Logs of the whole invocation, along with memory usage, duration, and other meaningful metrics.
On top of that, Dashbird groups similar errors, making it possible to estimate the scope of the problem and make debugging easier. For example, it might help to better observe the problem if you find some commonalities in the executions.
Here’s how a Python error looks like in Dashbird.
You can find the complete list of Python exceptions here.
Exceptions are parsed out automatically in Dashbird, and include a rundown of traceback and logs of the specific invocation.
Another scenario for errors in AWS Lambda is when you have a third-party module imported in your function code but not found in your Lambda deployment package.
Obs.: Python built-in modules are available out-of-the-box in the Lambda environment, you obviously don’t need to worry about them. Also, boto3 is available in all Python functions by default, there’s no need to include in your Lambda packages.
Here’s how it looks like:
START RequestId: db1e9421-724a-11e7-a121-63fe49a029e8 Version: $LATEST Unable to import module 'lambda_funxction': No module named 'lambda_funxction' REPORT RequestId: db1e9421-724a-11e7-a121-63fe49a029e8 Duration: 15.11 ms Billed Duration: 100 ms Memory Size: 128 MB Max Memory Used: 18 MB
Apart from Python-specific errors, programmers have to think about failures that are specific to Lambda functions. In Runtime-agnostic Best Practices we have covered most of the problems that cause headaches to serverless developers.
We aim to improve Dashbird every day and user feedback is extremely important for that, so please let us know if you have any feedback about our features and error handling! We would really appreciate it!
Can’t find what you’re looking for? We’d love to help. Send us a message through the chat bubble or email us.
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Dashbird is a monitoring, debugging and intelligence platform designed to help serverless developers build, operate, improve, and scale their modern cloud applications on AWS environment securely and with ease.
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.