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By agmatei
Clouds, be they private or public, surprisingly remain one of the most DIY-favouring markets. Perhaps due to the nebulous and increasingly powerful technologies, a series of myths, or even unnecessary egos, the majority of non-tech-centric enterprises (meaning, companies whose primary business scope rests outside the realm of IT software and hardware) still try to build and nurture in-house cloud management teams, without considering outsourcing even part of their workload.
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By Philip Williams
Artificial intelligence is the most exciting technology revolution of recent years. Nvidia, Intel, AMD and others continue to produce faster and faster GPU’s enabling larger models, and higher throughput in decision making processes. Outside of the immediate AI-hype, one area still remains somewhat overlooked: AI needs data (find out more here).
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By Canonical
New subscription for IoT deployments brings security and long term compliance to the most advanced open source stack.
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By Lukas Märdian
As the maintainer and lead developer of Netplan, I’m proud to announce the general availability of Netplan v1.0 after more than 7 years of development efforts. Over the years, we’ve had approximately 80 individual contributors from around the globe. This includes many contributions from our Netplan core-team at Canonical as well as organisations like Microsoft and Deutsche Telekom.
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By Bertrand Boisseau
Canonical is proud to announce it is joining the ELISA (Enabling Linux in Safety Applications) project. By joining ELISA, Canonical will work side-by-side with other industry leaders to make Linux a trusted and dependable option for safety-critical environments.
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By Tytus Kurek
One of the biggest challenges that cloud service providers (CSPs) face these days is to deliver an extension of the public cloud they host to a small-scale piece of infrastructure that runs on customers’ premises. While the world’s tech giants, such as Amazon or Azure, have developed their own solutions for this purpose, many smaller, regional CSPs rely on open source projects like OpenStack instead.=
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By Bertrand Boisseau
I had the pleasure to be invited by Canonical’s AI/ML Product Manager, Andreea Munteanu, to one of the recent episodes of the Canonical AI/ML podcast. As an enthusiast of automotive and technology with a background in software, I was very eager to share my insights into the influence of artificial intelligence (AI) in the automotive industry.
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By Jehudi
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.
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By Benjamin Ryzman
Telecommunications companies (telcos) are well on their way to transforming their infrastructure from the legacy, unadaptable, complex network of dedicated hardware from yesteryears to agile, modular and scalable software-defined systems running on common off-the-shelf (COTS) servers. Within this space, the current trend, driven by 5G deployments, is to complement tried and tested network function virtualisation (NFV) infrastructure with cloud-native network functions (CNFs).
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By Carlos Bravo
In our previous post, we discussed how to generate Images using Stable Diffusion on AWS. In this post, we will guide you through running LLMs for text generation in your own environment with a GPU-based instance in simple steps, empowering you to create your own solutions. Text generation, a trending focus in generative AI, facilitates a broad spectrum of language tasks beyond simple question answering.
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By Canonical
Safety is a key element in navigating AI within the automotive ecosystem. 🚗 Listen on Spotify about the future implications of AI in automotive, as discussed by Bertrand Boisseau, our automotive industry lead at Canonical.
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By Canonical
The emergence of DevOps has changed the way enterprises handle software delivery processes, leading to faster and improved quality. After DevOps has been coined, other practices such as DataOps, MLOps, and AIOps have emerged. In the podcast, Michelle and Andreea, Data PM and AI Product Managers, respectively, will be discussing the significance of these Ops processes in streamlining and optimizing enterprise data, machine learning, and AI projects and use cases.
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By Canonical
This video will teach you how you can launch a Ubuntu instance on Google Vertex AI, which embodies the AI/ML tools you need for training LLM.
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By Canonical
AI is at the heart of a revolution in the technology space. Organisations from all industries are looking for ways to put AI to work. Once they have finalised use case assessment, their next question is typically related to the environment they will use to develop and deploy their AI initiatives. They often prefer the public clouds as an initial environment, because of the computing power and ability to scale as projects mature. In addition to the infrastructure, enterprises need software where they can develop and deploy the machine learning models.
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By Canonical
Introducing Charmed MongoDB – Canonical’s enterprise-grade MongoDB database offering. Charmed MongoDB simplifies the operations of MongoDB applications through automation, security, scalability, availability and monitoring. Charmed MongoDB is the cost-effective, reliable, secure and scalable way to use MongoDB on any cloud, hybrid cloud or on-premise. It also provides additional support, managed services, and expert services, so enterprises can run MongoDB in production at a lower cost, bug-free and in the most optimised way.
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By Canonical
Weka report from 2024 showed that 47% of respondents will use the public cloud as the primary place to develop their machine learning projects. This is a result of a correlation of factors which include the need for compute power, easy scalability, and the ability to utilise existing infrastructure already in place on both hybrid clouds and public clouds. Join us to talk more about AI on the public cloud: what are the main benefits and what are the best practices an organisation could implement in order to easier adopt AI and leverage the most the public clouds.
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By Canonical
AI models run on large amounts of good quality data, and when it comes to sensitive tasks like medical diagnosis or financial risk assessments, you need access to private data during both training and inference. When performing machine learning tasks in the cloud, enterprises are understandably concerned about data privacy as well as their model’s intellectual property. Additionally, stringent industry regulations often prohibit the sharing of such data.
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By Canonical
It's the grand reveal of Ubuntu 24.04 Noble Numbat 👑 The numbat, a small enigmatic marsupial from Australia may not be the first creature that comes to mind when one ponders nobility. However, looks can be deceiving.
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By Canonical
🚀 AI is reshaping our world, from entertainment to space exploration. Canonical simplifies your AI journey with long-term support and easy-to-use open-source tools. Dive into building, scaling and optimizing tools like Kubelow, MLflow, Kafka, and Spark with Canonical Data & AI solutions.
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By Canonical
From the smallest startups to the largest enterprises alike, organisations are using Artificial Intelligence and Machine Learning to make the best, fastest, most informed decisions to overcome their biggest business challenges. But with AI/ML complexity spanning infrastructure, operations, resources, modelling and compliance and security, while constantly innovating, many organizations are left unsure how to capture their data and get started on delivering AI technologies and methodologies.
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By Canonical
Traditional development methods do not scale into the IoT sphere. Strong inter-dependencies and blurred boundaries among components in the edge device stack result in fragmentation, slow updates, security issues, increased cost, and reduced reliability of platforms. This reality places a major strain on IoT players who need to contend with varying cycles and priorities in the development stack, limiting their flexibility to innovate and introduce changes into their products, both on the hardware and software sides.
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By Canonical
Private cloud, public cloud, hybrid cloud, multi-cloud... the variety of locations, platforms and physical substrate you can start a cloud instance on is vast. Yet once you have selected an operating system which best supports your application stack, you should be able to use that operating system as an abstraction layer between different clouds.
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By Canonical
Container technology has brought about a step-change in virtualisation technology. Organisations implementing containers see considerable opportunities to improve agility, efficiency, speed, and manageability within their IT environments. Containers promise to improve datacenter efficiency and performance without having to make additional investments in hardware or infrastructure. Traditional hypervisors provide the most common form of virtualisation, and virtual machines running on such hypervisors are pervasive in nearly every datacenter.
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By Canonical
Big Software, IoT and Big Data are changing how organisations are architecting, deploying, and managing their infrastructure. Traditional models are being challenged and replaced by software solutions that are deployed across many environments and many servers. However, no matter what infrastructure you have, there are bare metal servers under it, somewhere.
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We deliver open source to the world faster, more securely and more cost effectively than any other company.
We develop Ubuntu, the world’s most popular enterprise Linux from cloud to edge, together with a passionate global community of 200,000 contributors. Ubuntu means 'humanity to others'. We chose it because it embodies the generosity at the heart of open source, the new normal for platforms and innovation.
Together with a community of 200,000, we publish an operating system that runs from the tiny connected devices up to the world's biggest mainframes, the platform that everybody uses on the public cloud, and the workstation experience of the world's most productive developers.
Products:
- Ubuntu: The new standard secure enterprise Linux for servers, desktops, cloud, developers and things.
- Landscape: Updates, package management, repositories, security, and regulatory compliance for Ubuntu.
- MAAS: Dynamic server provisioning and IPAM gives you on-demand bare metal, a physical cloud.
- LXD: The pure-container hypervisor. Run legacy apps in secure containers for speed and density.
- Juju: Model-driven cloud-native apps on public and private infrastructure and CAAS.
- Snapcraft: The app store with secure packages and ultra-reliable updates for multiple Linux distros.
Drive down infrastructure cost, accelerate your applications.