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.
Up until now, DynamoDB has been the only option of a truly serverless database battle-tested for production environments. Especially after launching the on-demand throughput capacity optimization, is a perfect-fit database engine for serverless projects.
That is one of the main reasons preventing serverless teams to adopt a serverless database. Many have falled back to SQL, by using Aurora Serverless, or to a document DB such as MongoDB. These two databases are supported by open-sourced APIs, releasing the vendor lock-in fears.
The problem is: none of these options offer the level of speed and scalability of DynamoDB. See, for example, our detailed comparison of MongoDB and MongoDB Atlas.
As an example: each node in Cassandra can serve requests directly. Without the need for a Master node, as opposed to Aurora or MongoDB, the scalability and reliability of Cassandra are increased by orders of magnitude.
Cassandra is an open-source database system and can be deployed virtually anywhere, in the cloud or on-premise. Migrating an application relying on Cassandra would be greatly faster and cheaper in comparison to one tied to the proprietary DynamoDB API.
The only downside so far is pricing: ~16% more expensive than DynamoDB on-demand mode costs. But considering the flexibility offered by Cassandra, that might be worth paying for.
Serverless Cassandra is still in preview mode. At Dashbird, we are testing it to really confirm it can scale to cope with high throughput of a Lambda application, for example.
We’re publishing a thorough comparison of Cassandra Serverless and
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.