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Dashbird Round-Up 2020

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It’s safe to say that 2020 has been quite the year for everyone, and at Dashbird we’ve had quite a few changes of our own. It became the year full of improvements, growth, and feature releases that we had only imagined a year ago. 

This is our round-up of all the feature releases we launched this year. 


Just starting out with Dashbird? Great, you are in the right place. 

If you haven’t tried out Dashbird yet and would like to follow along, feel free to give Dashbird a try yourself – in the worst case scenario you will end up finding errors you didn’t have a clue of. Set up is an easy 2-minute process without any code changes or credit card required.

A loyal user of Dashbird? You’re at the right place too, as we’ve evolved and improved as a monitoring platform a lot this year. And we’re pretty sure you might have missed some of our recent feature releases.

So here we go!

Inventory 

dashbird inventory

Having previously exclusively served AWS Lambda, earlier this year, Dashbird added more AWS services to our roster for serverless monitoring, observability, and optimization opportunities. The Inventory list includes:

Dashbird single function view

The addition of these instrumental services and resources in the Dashbird monitoring platform gives you even greater autonomy and understanding of your Serverless infrastructure. With the ability to drill down into the details, set up alerts, and watch for trends and patterns, Dashbird offers one of the fullest Serverless observability platforms available today. All without any code or architectural changes. You just have to deploy CloudFormation template to your AWS, we’ll do the rest.

Well-Architected and Best-Practice Insights

We don’t only just show you data!

Dashbird features a continuous rule engine for detecting and enforcing Serverless Well-Architected practices. Dashbird is constantly running users’ infrastructure data through its WAF rule engines detecting anomalies and weaknesses within the architecture, and notifying the users of critical errors and/or when improvements should be made.

This allows developers to build and operate complex Well-Architected serverless applications without compromising its reliability over time and also be able to layer on complexity later on.

Metric Alarms

In addition to the Inventory, we also added the Metric Alarms feature. Its simplicity – choosing a metric important to you, setting its status to ‘critical’ or ‘warning’, and pointing to the relevant resources and the person this alarm should reach – lets you cut through the noise, meaning alert fatigue and complex alarms can be a thing of the past. You can be confident that important information reaches the correct person in time!

Used in conjunction with Dashbird Insights Engine, Metric Alarm allows users to gain greater assurance over SLAs/SLIs and to customize their infrastructure based on solid insight. 

For example, here we have configured a critical alarm to be triggered when the queue has reached 10 or more items. This alarm helps detect situations like when the queue consumers cannot keep up with new messages in the queue – that is when messages arrive faster than they can be processed.

So whenever that happens, Alex from our dev team gets notified in real-time via Slack (his preferred channel).

Detailed Usage Report 

The Detailed Usage Report provides another element to the metrics and insights Dashbird already offers. Shown by; Usage by Region and by Type, Data Ingested by Region and by Lambda, and Lambda Invocation, it’s one step easier to spot trends and patterns for better optimization

For example, understanding the pattern of a well-used Lambda from this starting point, users can then look into its related billing and resource usage patterns to identify if savings can be made in either AWS or Dashbird. 

Notifications Channel & New Communication Channels

Dashbird has now enabled alerts and alarms to be sent through AWS SNS and Webhooks, making automation and autoscaling even easier and more seamless. Out-of-the-box notifications can be set up, as can the customized ones. 

Understanding that each company’s workflow is different, the Notification Channel now makes it easier to point alerts to a specific team member or group for faster internal communication, acknowledgement and remediation. 

Dashbird app got a shiny new look

The new and improved Dashbird app’s main screen is designed to give you a quick overview of the most important events and metrics across your serverless environment. Jump in and check it out!

If you’re not a Dashbird user, you can learn more and sign up for free.


This was Team Dashbird’s year 2020 in a nutshell. We’re wishing you quick failure detections to the end of the year and strong reliable infrastructures for 2021!

Made by Developers for Developers

Our history and present are deeply rooted in building large-scale cloud applications on state-of-the-art technology. Dashbird was born out of our own need for an enhanced serverless debugging and monitoring tool, and we take pride in being developers.

10,000+ developers trust Dashbird

Dashbird helped us reduce the time to discovery from 2-4 hours to a matter of seconds. This means we’re saving dozens of hours in developer time, which not only can be funneled into improving the product but also means 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.

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.

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