Operations | Monitoring | ITSM | DevOps | Cloud

This blog post explores the technical and strategic benefits of deploying open-source AI models on Ubuntu. We’ll highlight why it makes sense to use Ubuntu with open-source AI models, and outline the deployment process on Azure.

From its initial appearance in the dev-tools space, GenAI has had an outsized impact on how developers approach day-to-day tasks (just ask any developer about when they first started using GitHub’s copilot). While any risks are still being evaluated—like potential for introducing anti-patterns or inadvertently running afoul of compliance requirements, many engineering teams have successfully implemented GenAI with measurable gains in collaboration and productivity.

As businesses increasingly move their workloads to the cloud, managing cloud costs has become a critical concern. At Tidal.Cloud, with the roll-out of new features such as Tidal Accelerator’s Business Analytics, we recently realized that our AWS costs were steadily increasing, and we needed to take action to optimize our cloud spending.

Tidal Accelerator has recently made its powerful Business Analytics feature generally available across all existing and new workspaces, as discussed in our previous article. This game-changing capability empowers organizations to make data-driven decisions throughout their migration and modernization journeys. In this article, we’ll dive deeper into four key areas where Tidal Accelerator’s advanced analytics provide invaluable insights.

Ensuring efficient deployment and management of containerized applications is critical to development teams across all possible industries in today’s cloud-native world. A standout service for many has been AWS Elastic Container Service (ECS), which has proven to be scalable and easy to use while integrated into one of the largest cloud ecosystems out there. However, one size does not fit all.

Is your Azure spend management getting out of control? You’re not alone. Countless businesses struggle with the exact problem, often lacking clarity on the reasons behind the cost spike. Especially within larger organizations, where multiple teams deploy Azure resources, the Azure costs can quickly get out of control without the necessary tools to effectively track the spending and evaluate monthly Azure spend against their business needs.

If there's one thing almost every developer has done in their life, it's deploy an application to Heroku. From their launch in 2007, Heroku dominated PaaS and caught the attention of Salesforce who acquired them in 2010. They had the first managed Postgres service in 2011, an easy to use CLI, and, last but not least, it was free to get started which led to a big uptick in initial popularity. Every side project from here to the moon went to Heroku.