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.
The billing cycle begins on the day you subscribe as a paying customer, either to the Professional or Enterprise tier.
Dashbird charges based on the active resources and ingested data at the end of the billing cycle. The billable count of active resources is based on the average usage of those active resources throughout the billing cycle. The billable amount for ingested data is the sum of all the imported logs data in megabytes (MB) during the billing cycle.
Dashbird only charges for the resources that are active (not disabled) in the Dashbird app. Please follow the tutorial here on how to select which resources to monitor.
The app differentiates billable and non-billable resources. Here are the resources that are billable:
Resource types that aren’t included in the resource usage and are complementary for Dashbird users:
Dashbird currently only imports Lambda logs and therefore will bill for the amount of logs ingested. Within the app, Dashbird estimates the data usage based on the previously imported data during the billing cycle.
Dashbird usage report can be found on the billing page. To estimate future usage and cost, you can also use the cost calculator.
With the Pro and Enterprise plan you have the option to choose between the on-demand (pay-as-you-go) or a reserved (annual) subscription.
On-demand subscription is suitable if you deal with an uneven amount of resources and/or ingested data each month. It is more flexible and you will be charged monthly.
Reserved subscription is suitable if you have a stable number of resources and/or ingested data each month. It is cheaper than the on-demand subscription. With the reserved subscription, you will prepay for the whole year by choosing the monthly reserved resources and/or data ingestion you would like to choose for the year. You will be charged annually.
Both of the billing cycles can be combined together. For example, if you have an even number of resources and an uneven load of data ingestion you may choose to have resources reserved and pay the data ingestion on-demand.
If you exceed your reserved at any point in time, the monthly overage usage will be charged at the on-demand rate.
For more information on subscription tiers, please visit the Dashbird pricing page.
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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.