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.
Now I’m sure this is not the case for everyone but for me personally, I like watching video tutorials on subjects that I need help with. I spent a good amount of time searching for these tutorials and while there might be a lot more of them out there I believe these are some of the best and easiest tutorials to follow but nevertheless, I’d like to keep this list updated so if you have any suggestions please let me know.
Let’s start small and go from there. Python has been getting a lot of interest and this has got to be one of the best tutorials I’ve seen so far.
I might be biased here but NodeJS has finally met its match with AWS Lambda. The simplicity of Node is enhanced by the graceful scalability of AWS Lambda, provided you can stay under the concurrency limits.
Running Java on AWS Lambda is a great idea if you have a lot of consecutive executions. In this video, you’ll see how to deploy and test a serverless AWS Lambda function written in Java on the Amazon Web Services platform.
Learn how Gousto built a robust, asynchronous message bus using AWS Lambda, Amazon SNS, and Amazon SQS to integrate a microservices platform with ERP and warehouse management systems (WMS), which enabled a near real-time flow of events.
APIs are the backbone of any modern applications but building efficiency can be really tricky. With API Gateway and Lambdas you can get an API online in less time which makes launching new features a walk in the park.
That’s all I have for you this time but like I’ve said in the beginning, I’d love to keep this updated so if there’s a tutorial that you thought stood out from the rest please let me know and I’ll update the list.
In this guide, we’ll talk about common problems developers face with serverless applications on AWS and share some practical strategies to help you monitor and manage your applications more effectively.
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.
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.