The Data Mesh is a fascinating approach to designing and developing data architectures – and it’s generating a lot of attention and discussion in the data world. The concept, introduced by Zhamak Dehghani, challenges the status quo idea of a centralized, monolithic data architecture. Instead, advocating for a decentralized domain-driven design.
We are excited to announce the launch of Speedscale CLI, a free observability tool that inspects, detects and maps API calls on local applications or containers. The offering underscores the importance of continued and proactive API testing to quickly detect and debug defects within a shifting array of upstream and downstream interdependencies.
In this blog post we’ll help answer the age old question, “What does this service talk to and what does it say?” We’ll see how to inspect inbound and outbound REST API calls to see what calls are being made and what incoming traffic causes a reaction. This can be pretty handy when you’re taking over maintenance of an existing service, or if your code just isn’t behaving the way you expect.
This blog was co-created by Ricardo Ferreira (Elastic) and Viktor Gamov (Kong). We love our microservices, but without a proper observability (O11y) strategy, they can quickly become cold, dark places cluttered with broken or unknown features. O11y is one of those technologies deemed created by causation: the only reason it exists is that other technologies pushed for it. There wouldn’t be need for O11y if, for example, our technologies haven’t gotten so complex across the years.
In recent years, Observability has become a de-facto standard when discussing development and maintenance of cloud-native applications. The need to develop an observable system and ensure that as it runs in production, engineers will be able to detect performance issues, downtimes, and service disruptions, has evolved into a rich ecosystem of tools and practices.
