Below article describes the front-end architecture we created. FEEA is the right choice for every scale business. The framework didn’t materialize just now, it’s an output of years of experience with enterprise delivery we’ve managed.
This essay dispels several very substantial myths about #Scala that we have seen circulating the blogosphere. For each debunked myth, we present an alternative viewpoint backed up by data from reliable sources.
What if you could take a look at our code from above – and instead of seeing just text files – go through colorful graph nodes that instantly and clearly?
Nvidia DeepStream is portrayed as a solution to reliably host and serve deep learning models for live video feeds, especially at the edge where latency and efficiency matter most. The article frames DeepStream as a production-ready tool that brings computer vision techniques into mainstream IT systems.
Spark 3.2.0’s support for Scala 2.13 technically allows Scala 3 Spark jobs—but it remains “an uphill path,” requiring workarounds for encoders and data shapes. Using libraries like Iskra smooths the path, yet production readiness is still experimental.
In this post, we describe how we built a pipeline for the type of “incoming data” situation, and how we came up with a good solution in the end.
Jenkins Kubernetes Operator can help you avoid unexpected downtime in CI/CD and opens doors for doing canary or blue/green deployment.
There has come a time in every company when applications have developed to such an extent that a common content management solution is needed. It’s crucial to choose a proper one, which fits current requirements, but also will be ready for future growth.
Two developers recount their cloud migration of a massive, monolithic financial system—covering everything from Docker image overhaul to multi-cluster Kubernetes scaling—with emphasis on automation, security, and resilience. The article highlights tackling challenges like bulky container images, slow storage, DNS issues, and logging costs while running up to 20,000 pods.
This blog post covers mostly a summary of the significant amount of time spent with the team to help the company drive its large-scale Azure cloud transformation.
The below article describes the solution architecture we created for risk detection that provides results in real-time and at scale. Together with ksqlDB, features in the Kafka Streams framework help engineers focus on delivering real business value.
Kotlin lacks Java’s package-private visibility, exposing everything by default unless explicitly marked, which can bloat APIs and hinder encapsulation. The author praises Java’s manifest-based modular exports for making visibility decisions more conscious and centralized.