Microservices are now the architecture of choice for many developers when crafting cloud-native applications. A microservices application is a collection of loosely coupled services that communicate with each other, enhancing collaboration, maintainability, scalability, and deployment. There are several options for enabling this communication between microservices. When it comes to Python, gRPC and REST are two extremely popular directions to go.

On November 26, 2024, Anthropic released the Model Context Protocol (MCP)—an open standard for data exchange between applications and data sources. MCP simplifies how Large Language Models (LLMs) interact with external tools and data, addressing the challenges developers face when integrating AI into their systems. At Raygun, we’ve been exploring agentic workflows to improve productivity and saw real potential in MCP.

Amazon Virtual Private Cloud (VPC) is a commercial cloud computing service that enables users to create a logically isolated section within the AWS Cloud. Users can deploy AWS resources in a self-defined virtual network within this isolated section. In essence, it enables customers to build resources within a private, separated area of the AWS cloud, such as databases, Elastic Compute Cloud (EC2) instances, and other AWS services. AWS offers VPC to enterprises as a way to improve cloud security.

This tech paper was created by IIoT World and InfluxDB. This post was originally published on IIoT World. The Industrial Internet of Things (IIoT) is revolutionizing industries like manufacturing, energy, and logistics by creating more intelligent, interconnected systems that elevate productivity and efficiency. With IIoT, machines, systems, and sensors are linked in real-time, streamlining industrial automation and making predictive maintenance a reality—all while reducing downtime and costs.

On the December episode of This Month in Datadog, Jeremy Garcia (VP of Technical Community and Open Source) covers Kubernetes Active Remediation, Datadog IaC Security, and a trio of new features for monitoring AWS resources. Later in the episode, Natasha Goel (Product Manager) spotlights Datadog Cloud Cost Management for OpenAI. Also featured is a short recap of Datadog at KubeCon North America and AWS re:Invent 2024.

It’s been a busy year at Gremlin! We released two new experiments, added an entirely new onboarding process and features for AWS users, added a brand new Test Suite and Detected Risks, and made many UI improvements to our web app. We beefed up our agents with more enterprise capabilities, including support for large Kubernetes clusters and systems with over 64 CPUs, improved experiment behaviors, improved dependency detection, and per-team Private Network Integrations.

This guide provides instructions for setting up an environment for developing, debugging, and programming embedded systems firmware in the Windows Subsystem for Linux (WSL2). WSL2 provides a convenient and stable Linux development environment for working on embedded systems firmware. If you’re curious about toolchain performance, check out this comparison of firmware development environments, but the summary is that WSL2 is about 2x the speed of Windows and similar to “bare metal” Linux.

Kubecon North America took place in Salt Lake City, Utah, from November 12 to 15, and the SolarWinds team was there to showcase updates to our SolarWinds Observability dashboards and join in the conversation. Here are five key talking points from the event.

In the age of digital transformation, adhering to aging cybersecurity rules, policies, and standards set a few decades ago is an open invitation for setbacks. This is why the EU is updating and taking significant steps to strengthen existing regulations and bring new ones to unify existing risk management in individual EU member countries. Keeping pace with the modernization of complex technology is challenging, but resilience in times of adversity is the need of the hour.

Python's logging system provides powerful tools for application monitoring, debugging, and maintenance. This comprehensive guide covers everything from basic setup to advanced implementation strategies, helping you build robust logging solutions for your Python applications.