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Introduction to NoSQL

NoSQL is built for high performance and availability. Let’s learn about why it was created and how it differs from SQL. And no, it doesn’t stand for “No SQL”.

Debugging with Dashbird: Resolving the Most Common API Gateway Request Errors

Errors in the range of 400 to 499 usually point to a problem with the API client, and errors in the range of 500 to 599 mean something on the server is wrong. Let’s take a deeper dive.

AWS Kinesis vs SNS vs SQS  (with Python examples)

Decoupling offers a myriad of advantages, but choosing the right tool for the job may be challenging. In this article we’ll take you though some comparisons between AWS services that allow you to decouple sending and receiving data (covering SNS, SQS and Kinesis). We’ll show you examples using Python to help you choose a decoupling service that suits your use case.

Serverless Stonks checker for Wall Street Bets: week 3 activity report insights

A few weeks ago we posted the “How we built a serverless Stonks checker API for Wall Street Bets” article. And ever since, we’ve seen quite a lot of volume in the Stonks checker app. In this follow-up article, we will show you some interesting findings around the API.

6 Common Pitfalls of AWS Lambda with Kinesis Trigger

The simplicity of setting up a Kinesis trigger for a Lambda function may be deceptive. In this article, we uncover and discuss the 6 most common pitfalls that can cause problems but are usually spotted later in the production environment.

AWS CloudWatch (클라우드 와치) vs Dashbird

AWS에서 실행되는 애플리케이션의 경우 지금까지 CloudWatch (클라우드 와치)로 충분할 수 있습니다. 하지만 저희는 조사를 통해 클라우드 와치에만 의존하는 팀이 문제 발견과 해결에 뒤처지는 경향이 있다는 것을 확인했습니다.

프로덕션을 위한 AWS Lambda 최적화 팁 4가지

이 포스트는 AWS Lambda (람다) 최적화에 관한 내용을 다루고 있으며, 람다 함수의 지속적인 모니터링과 개선, 오류 및 작업 실패에 대한 알림을 받을 수 있도록 하는 워크플로우 개발을 목적으로 하고 있습니다. 

How Can a Shared Slack Channel Improve Your Data Quality?

In this article, we’re looking at how simple process adjustments can increase the team’s engagement and commitment to improving data quality, and how to leverage the power of automation.

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Industry leader in serverless monitoring

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.

What our customers say

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.