Dashbird blog

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”.

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.

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.

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.

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.

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.

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. 

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.