Artificial intelligence is no longer limited to large data centers and high-powered servers. Today, more organizations are deploying ML models to edge devices such as smartphones, tablets, and IoT hardware. These devices work in environments where connectivity is not guaranteed and computing resources are restricted. By running models directly on edge hardware, businesses reduce latency, enable offline functionality, and improve …

Outdated deployment practices can slow down even the best software teams. When you’re still manually moving files between servers, it’s easy for small mistakes to slip through and updates to take longer than they should. At Keyhole Software, we’ve seen firsthand how this approach can hold back your projects. The solution is to automate deployment pipelines. It brings consistency, reliability, …

A familiar challenge for many businesses is knowing when it’s time to modernize. Legacy applications that once ran smoothly on in-house servers start to feel like a burden as competition increases and technology advances. At Keyhole Software, we help companies migrate legacy applications to AWS or Azure to stay ahead. We take what already works and move it to a …

As organizations look to stay competitive in 2025, one area that can’t be ignored is LLMOps for enterprises. Large language models (LLMs) have become essential for automating tasks, improving productivity, and gaining insights from data. However, most conversations about LLMs focus on public cloud services or small-scale tools. For large enterprises, these solutions often fall short in security, scalability, and …

Virtual machine deployments are no longer the standard for running modern software. If you’re using Docker for event-driven applications, choosing the right hosting solution is essential. At Keyhole Software, we often get asked about the difference between GCP Cloud Run and AWS ECS, and which one makes the most sense for container hosting. Below, we’ll explain how these two options …