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.
Last week, we raised the limit of our enterprise plan to 100 million requests per month. This is the first step towards improving our value offering for large-scale serverless systems.
Previously, the default limit for enterprise customers was 30 million a month. At the time, this was the range we could promise to import from CloudWatch without getting throttled and also it seemed to be more than enough for basically all of our users. Lately, we have made significant improvements to our log importer system, which now is able to easily import a hundred million request per month. That is, without running into throttling issues with CloudWatch.
With the improvements on the importer and data aggregators (including swapping the database from DynamoDB to MongoDB) we have also significantly improved the importing delays. In January, the mean delay for a request was 40 seconds (down from the range of about 90-120 seconds), with best case scenarios being around 10 or 20 seconds.
We launched project views in December. With project views, you can break down your main dashboard into micro-service or stage level and have more detailed metrics. We believe, this will help you create more relevant dashboards if you have a huge amount of functions.
For the next months, we have a ton of interesting features coming, like custom metrics, custom alerting, API Gateway support and more. Also there’s going to be a push for even bigger limits. We’re also working towards supporting volumes into billions of requests, which will require a different approach on importing (think sampling).
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.
End-to-end observability and real-time error tracking for AWS applications.