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.
We’re very proud to say August 2020 marks three years of Dashbird empowering Serverless DevOps teams to regain control over their distributed application through full observability, actionable insights and instant monitoring alerts.
This birthday month, we have plenty of surprises, giveaways, and goodies in our sleeve over the next few weeks, so sign up for our newsletter to be the first one to know.
First off, we are excited to announce that our industry-standard Serverless Insights feature now supports AWS Kinesis and Step Functions.
The Insights engine relies on good practices for Well-Architected and performant serverless applications. It constantly monitors your cloud stack and cross-references against these practices to issue alerts and improvement suggestions to keep systems scalable, secure and reliable.
Dashbird Insights now supports Kinesis Data Firehose, Kinesis Data Streams and Step Functions (both Standard and Express workflows).
The platform will automatically generate alerts when a Kinesis Stream is experiencing write throttles or has an insecure encryption setting, for example. With regards to Step Functions workflows, the Insights feature detects errors related to state machine definitions or task execution failures.
Since its inception, Dashbird has committed to providing full visibility for developers over their serverless stacks. This is another step towards this goal, moved by our vision for well-architected and reliable serverless systems.
Step Functions is a powerful orchestration tool for developers to handle the implementation of complex workflows. Kinesis is a key service for large-scale, data-intensive applications. We are thrilled with the addition of these two great services in our Serverless Insights engine.
We digress, try out the new services yourself and start receiving architectural and security insights and alerts tailored to your cloud stack, subscribe to a free account on Dashbird. It only takes 3 minutes, no code changes and no credit card required.
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.