Systems | Development | Analytics | API | Testing

For decades, machine learning engineers have struggled to manage and automate ML pipelines in order to speed up model deployment in real business applications. Similar to how software developers leverage DevOps to increase efficiency and speed up release velocity, MLOps streamlines the ML development lifecycle by delivering automation, enabling collaboration across ML teams and improving the quality of ML models in production while addressing business requirements.

If you've been on the hunt for a new developer podcast, then you understand just how difficult and fruitless that pursuit can be. You can spend hours online sifting through coding podcasts, programming podcasts, and DevOps podcasts only to realize one simple thing: none of them focus on your preferred programming language! With thousands of different developer podcasts out there, the problem is magnified exponentially. Fortunately, we at Scout APM have nothing but expertise and time on our hands.

Container technology promises to usher in the biggest step change in infrastructure economics since server virtualization. By some estimates, customers are saving as much as 50% on infrastructure costs by switching from hosting cloud native applications in their own data centers to hosting containerized versions of those applications in a private, hybrid or public cloud.