There are many libraries out there that can be used in machine learning projects. Explore a comprehensive guide on which libraries to use in your projects.
I want to highlight the five scripts/tools that I believe will have the biggest influence on your development work, mostly related to real-time data stream processing.
Interested in open-source observability? Learn about automating service discovery and how to scale your observability in dynamic cloud native environments.
From Google Analytics to deep-dive data analytics for your APIs, big data matters when it comes to understanding your company. Learn about platform analytics.
Have the right mix of tools to achieve the unified observability of the applications running in the cloud. Know your responsibilities while migrating to the cloud.
'Drop-in' Kafka Streams State Store implementation that persists data to Apache Cassandra / ScyllaDB. Stateless to run, no changelog, no state restore.
Automation, simplicity, and making robust supply chain security a seamless default for developers is the next evolution of software supply chain security.
Array reversal in Python is easily achieved using slicing or a custom algorithm with pointers, empowering programmers to manipulate arrays efficiently.
Learn what GitOps is, GitOps goals and ideals, limitations, tools that support GitOps, and the practical implications of adopting GitOps in your own organization.
Despite being a relatively new profession, platform engineers already have some tried and true wisdom to rely on. Here's what I've learned from the best minds.