Kubernetes

The integration of AI and ML in products has become a trend in recent years. Companies are trying to incorporate these technologies into their products to improve their efficiency and performance. And this year, particularly with the boom of ChatGPT, almost every company is trying to introduce a feature in this domain. One of the main benefits of AI and ML is their ability to learn and adapt. They can analyze data and use it to improve their performance over time. This means that products that incorporate these…

Learn the basics of Kubernetes, docker, and Intel® AI Analytics Toolkit for building distributed AI AppsImage SourceBuilding and deploying high-performance AI applications can be a challenging task that requires a significant amount of computing resources and expertise. Fortunately, modern technologies such as Kubernetes, Docker, and the Intel® AI Analytics Toolkit make it easier to develop and deploy AI applications optimized for performance and scalability. Moreover, by using cloud services like Amazon Web Services…

The second day of Dynatrace Perform kicked off with a great discussion between Kelsey Hightower, distinguished developer advocate at Google Cloud Platform, and Andi Grabner, DevOps evangelist at Dynatrace. The theme of their discussion was redefining the boundaries of people, processes, and platforms. There were so many great insights in this discussion; I will cover it in much greater detail in a separate article.  My key takeaways from their discussion: Computers don’t have an emotional connection to the real world.…

SaaS applications are the new normal nowadays, and software providers are looking to transform their applications into a Software As a Service application. For this, the only solution is to build a multi-tenant architecture SaaS application. Have you ever wondered how Slack, Salesforce, AWS (Amazon Web Services), and Zendesk can serve multiple organizations? Does each one have its unique and custom cloud software per customer? For example, have you ever noticed that, on Slack, you have your own URL…

Integrating NVIDIA Multi-Process Service (MPS) in Kubernetes to share GPUs among workloads for maximizing utilization and reducing infrastructure costsPhoto by Growtika on UnsplashMost workloads do not require the full memory and computing resources of each GPU. Therefore, sharing a GPU among multiple processes is essential to increase GPU utilization and reduce infrastructure costs.In Kubernetes, this can be achieved by exposing a single GPU as multiple resources (i.e. slices) of a specific memory and compute size that…

DevOps is not new. Every business in the IT world knows it is the right software development methodology. Indeed, DevOps has enticed the world with its promise of high-quality product delivery at a faster pace. Despite the clear promise of DevOps, many businesses are failing to realize its complete potential. While cultural inertia and skillset sparsity are some of the reasons, the inability to completely automate the DevOps lifecycle remains the greatest impediment for businesses to drive full value from their DevOps…

Get full control of where your images are storedPhoto by Growtika on UnsplashHosting a Docker private registry gives you full control over the storage location of your images and how you can access them. This is especially useful if you develop private projects that shouldn’t be publicly on Docker Hub.In this tutorial, you will learn how to install a private Docker registry in any Kubernetes cluster. It is a follow-up of a tutorial previously released on this blog because it will use a Traefik Ingress Controller to expose…

Using native Python packages onlyManually creating a novel configuration file for every new experiment is a tedious process. Especially if you want to rapidly deploy a vast number of jobs on a Kubernetes cluster, an automated setup is a must. With python, it’s straightforward to build a simple scheduling script that reads an experiment’s configuration, such as the batch size, writes it into the YAML file, and creates a new job. In this post, we’ll discuss the how. The best is that we require no additional packages!Photo…

Creating a scalable search architecture is a popular and important task for many systems. There are different solutions for this task. Choosing the right one depends on the requirements of your project. Sometimes, as a project grows and its requirements change, you may run into new problems that you cannot solve with the search architecture you are using. For example, when increasing the amount of data, including synonyms in the search, adding multilingual search, etc. In this case, you need to think about creating a new,…

Maximize GPU utilization and reduce infrastructure costs.Photo by Growtika on UnsplashTo minimize infrastructure expenses, it’s crucial to use GPU accelerators in the most efficient way. One method to achieve this is by dividing the GPU into smaller partitions, called slices, so that containers can request only the strictly necessary resources. Some workloads may only require a minimal amount of the GPU’s compute and memory, so having the ability in Kubernetes to divide a single GPU into multiple slices, which can be…