As devs, we know the age-old question of, “How long do you think it will take?” oh too well. Regardless of experience and position within the development cycle, this inquiry always comes loaded with expectations and complexities, a concept I refer to as Speed to Delivery Time (SDT). To be clear, SDT isn’t just about marking days on a calendar.

I have always had a special fondness for Postgres, particularly captivated by its JSONB capabilities, which is at the core of what I love as it stands as a testament to its adaptability. This functionality exemplifies Postgres’s ability to adapt to modern apps’ rapidly changing needs to support structured and unstructured data to coexist seamlessly within the same database environment. The capabilities of PostgreSQL are not limited to its ability to manage relational and non-relational data.

MongoDB’s flexibility and document-oriented nature have always stood out to me as its most compelling features, setting it apart from the strict schema constraints of traditional relational databases. This adaptability is a boon for application development, allowing for more dynamic data interactions that mirror real-world information complexities and freeing table schemas’ constraints.

Developing a native Android app is a challenging task that requires a deep understanding of the Android SDK, as well as programming languages such as Java or Kotlin. The process requires navigating various tools, frameworks, and APIs, each with its own rules. On top of that, you need to ensure compatibility and optimal performance across the diverse Android ecosystem, with its multitude of devices, screen sizes, and OS versions.

Late last year, during an engaging Twitch livestream by AWS Developer Advocate Darko Mesaroš, I was introduced to a new framework Id seen a few people talking about called Winglang. What really got my attention was this wasn’t just another entry in the list of cloud frameworks, Winglang was on a mission to redefine how we interact with cloud environments. Its ambition to serve as an expansive framework that could effortlessly connect different cloud platforms instantly caught my attention.

Step Function added support for testing individual states . Which lets you execute individual states with the following: And returns the following: With the TestState API, you can thoroughly test every state and achieve close to 100% coverage of a state machine. So, does this eliminate the need for Step Functions Local ? Can we do away with end-to-end tests as well? If not, where should this new API fit into your workflow, and how should you use it?

This is the third and final blog post in a series about shifting Observability left. If you have not yet read the first two, you can find the first post here and the second post here. Observability is fundamental to modern software development, enabling developers to gain deep insights into their application’s behavior and performance.

This is the second post in a 3-part series about shifting Observability left. If you have not had a chance to read the first, you can find it here. In today’s complex microservices deployments, gaining visibility into deployments is vital for optimal system performance and scalability. This has become even more important as the tech industry has moved toward microservice architecture reliance. Navigating through logs has become increasingly complex as requirements have grown.

This is the first post in a 3-part series about shifting Observability left. When it comes to the reliability and performance of your applications, compromise is not an option in the world of software development. This is where observability can help developers achieve a more robust and scalable infrastructure.

One announcement that caught my attention in the EKS space during this year’s AWS re:Invent conference was the addition of the Amazon EKS Pod Identities feature. This new addition helps simplify the complexities of AWS Identity and Access Management (IAM) within Elastic Kubernetes Service (EKS). EKS Pod Identities simplify IAM credential management in EKS clusters, addressing a problematic area over the past few years as Microservice adoption has risen across the industry.