Recently, I got my hands dirty working with Apache Flink®. The experience was a little overwhelming. I have spent years working with streaming technologies but Flink was new to me and the resources online were rarely what I needed. Thankfully, I had access to some of the best Flink experts in the business to provide me with first-class advice, but not everyone has access to an expert when they need one.

In the first two parts of our Inside Flink blog series, we explored the benefits of stream processing with Flink and common Flink use cases for which teams are choosing to leverage the popular framework to unlock the full potential of streaming. Specifically, we broke down the key reasons why developers are choosing Apache Flink® as their stream processing framework, as well as the ways in which they are putting it into practice.

In their effort to reduce their technology spend, some organizations that leverage open source projects for advanced analytics often consider either building and maintaining their own runtime with the required data processing engines or retaining older, now obsolete, versions of legacy Cloudera runtimes (CDH or HDP).

gRPC is an open source remote procedure call (RPC) framework that enables client and server applications to communicate with each other remotely and transparently. In this blog post, we are going to discuss gRPC. First, we’ll talk about RPCs and why they are important. Then we’ll explain how gRPC works, taking a closer look at protocol buffers and the architecture of gRPC.

The open source ML tooling ecosystem has become vast in the last few years, with many tools both overlapping in their capabilities as well as complimenting each other nicely. In part because AI/ML is a still-immature practice, the messaging around what all these tools can accomplish can be quite vague. In this article, we’ll dive into three tools to better understand their capabilities, and how they fit into the ML lifecycle.

Here at NodeSource we are focused on fixing issues for the enterprise. This includes adding functionality and features to Node.js that are useful for enterprise-level deployments but would be difficult to upstream. One is the ability to execute commands remotely on Worker threads without the addition of running the inspector, such as capturing CPU profiles or heap snapshots.

Kong Konnect is a powerful SaaS-based API lifecycle management platform that provides a fast path for people looking to get started with Kong API Gateway. For existing users of Kong’s open-source gateway, it offers a way to rapidly take advantage of a scalable, highly-available architecture while upgrading to an Enterprise-class feature set and support options.

Grafana Faro and xk6-browser are both new tools within the Grafana Labs open source ecosystem, but the pairing is already showing a lot of potential in terms of frontend monitoring and performance testing. Faro, which was announced last November, includes a highly configurable SDK that instruments web apps to capture observability signals that can then be correlated with backend and infrastructure data.