Aspecto Blog

Microservices have tons of benefits.  They enable distributed development of highly scalable applications and unleashing the full potential of public cloud infrastructure. But there can be no good without evil.

I recently worked on an npm package that is supposed to be consumed on both Node.js environment and the browser (using React/Angular/etc..). Things started getting complicated when the node branch

Microservice architectures are quite popular nowadays. A typical application may consist of 10, 50, or even more than 100 microservices. Although it is relatively easy to run five microservices locally

When you have structured data in JavaScript, which needs to be sent over the network (for another microservice, for example) or saved into a storage system, it first needs to

I recently worked on a small TypeScript project which I wanted to deploy as a Lambda to AWS. My project had multiple files and some npm dependencies. I found some resources online, but

In modern web development, we deal with JSON every day. External APIs and our microservices usually have RESTful API and use JSON as the primary format.  Since we often use

At Aspecto, we use Elasticsearch as the primary tool for collecting, processing and searching telemetry traces. Since we enjoy using Elasticsearch internally, we set out to create an Elasticsearch instrumentation

It turns out that running ts-node-dev / ts-node is constantly consuming hundreds of megabytes of RAM even for small and simple applications. In development, it is usually not a big concern, however, it

OpenTelemetry is a CNCF project, which, among other things, enables the collection of distributed traces. At Aspecto, we use OpenTelemetry at the core of our product. While implementing it in our