Name: From VMware to the Future
Start: 2024-06-11T14:30:00Z
End: 2024-06-11T14:31:00.000Z
Location: BrightTALK
Rating: 0

Get the most in depth information about the Ubuntu technology and services from Canonical. 

Learn why Ubuntu is the preferred Linux platform and how Canonical can help you make the most out of your Ubuntu environment.

Deploying a PostgreSQL instance on Ubuntu is as simple as running a single command (i.e. sudo apt install postgresql-<version>). Yet, running a single instance of PostgreSQL is a recipe for downtime and reputation damage to your company.

To run a highly available PostgreSQL deployment you need to leverage several techniques such as replication, automatic failovers, failure isolation and backups. 

In this webinar, we will examine advanced techniques to implement fail-safe replication and automatic fail-overs. We will cover the following:
Replication techniques
Automatic fail-over techniques on client and server side
Demo

A deep dive into PostgreSQL replication and automatic failover techniques

On May 9th we released Ubuntu Core 24, the fifth release of Canonical's immutable, production-grade operating system designed for deploying embedded systems.

In this webinar, we will introduce Ubuntu Core, give you an overview of how it works and its use cases, and dive into each of the new features that come with this most recent release. 

Join us and discover:
- Everything you need to know about Ubuntu Core; from its architecture to its tooling. 
- A recap of the latest features of Ubuntu Core 24; including device management and graphics support. 
- How Ubuntu Core 24 enable companies to deploy cybersecurity-compliant solutions. is the embedded operating.

An Introduction to Ubuntu Core 24

Data Science Stack (DSS) is an out-of-the-box solution for data scientists and machine learning engineers, published by Canonical. It is a ready-made environment for ML enthusiasts that enables them to develop and optimise models without spending time on the necessary underlying tooling.  It is designed to run on any AI workstation that runs Ubuntu, maximising the GPU’s capability and simplifying its usage.

Join us in our next webinar to learn more about data science tools, with a focus on DSS and its capabilities. During the webinar, Michal Hucko, MLOps engineer at Canonical and Andreea Munteanu, AI Product Manager, will talk about:

Key considerations when getting started with data science
Data science through the open source lenses
Deep dive into Data science stack (DSS)
Demo of the DSS

Prepare your questions and join us live to get insights into how DSS improves the developer experience of Ubuntu users who are active in the data science or ML space.

Data science tools on Ubuntu: how can you quickly get started?

As AI dominates the tech stage, the intersection of Internet of Things (IoT) and artificial intelligence is taking up more of the spotlight. From AI-powered healthcare instruments to autonomous vehicles, there are many cases where artificial intelligence can be used and benefited from on edge devices. However, building an end-to-end architecture to enable such a solution comes with different challenges to other AI stacks, both in training models and in deploying them to the edge. 

## Open source at the edge
Open source solutions enable edge devices in different ways. From operating systems to ML platforms, enterprises can choose from a wide variety of solutions. This abundance of choice can be overwhelming, leading to organisations delaying decisions and not scaling their AI at the edge initiatives.
Join this webinar about AI at the edge

Join Andreea Munteanu, Product Manager for AI, Steve Barriault, VP of IoT Field Engineering and Alex Lewontin, IoT Field Engineering Manager, to discuss AI at the edge. 

During the webinar, you will learn:
- The main challenges rolling out AI at the edge and how to address them
- How to secure your ML infrastructure, from the data centre to the edge
- Key considerations to start and scale your ML embedded projects
- Benefits of running AI at the edge
- Common use cases and how to get them started quickly
- Role of open source in the Edge AI space

AI on the edge: solving enterprise challenges with embedded machine learning

In this webinar, you’ll learn about Canonical's release schedule for Ubuntu and its security updates, and how you can use this information to set optimal manual and automated security patching maintenance intervals.

There are a variety of tools, such as Livepatch, Landscape, Snaps, and command line utilities like unattended-upgrades that provide security patching automation capabilities. We’ll cover how each one works, and how you can combine them for maximum benefit. We’ll also cover the nuances between reboot recommended and reboot required.

Whether you'd like to perform security maintenance as little as possible or you’d like to perform it as aggressively and often as possible, this webinar will help you make informed choices to minimise your risk.

(Asia Pacific) Best practices for scheduling security patching automations

In this webinar, you’ll learn about Canonical's release schedule for Ubuntu and its security updates, and how you can use this information to set optimal manual and automated security patching maintenance intervals. 
There are a variety of tools, such as Livepatch, Landscape, Snaps, and command line utilities like unattended-upgrades that provide security patching automation capabilities. We’ll cover how each one works, and how you can combine them for maximum benefit. We’ll also cover the nuances between reboot recommended and reboot required.
Whether you'd like to perform security maintenance as little as possible or you’d like to perform it as aggressively and often as possible, this webinar will help you make informed choices to minimise your risk.

Best practices for scheduling security patching automations

Developing solutions with open source software provides rapid time-to-market and extensive community support, empowering businesses to deliver innovative products swiftly by leveraging the collective expertise and diverse support of developers and users. Despite these advantages, open source software is susceptible to security vulnerabilities, and addressing a Common Vulnerabilities and Exposures (CVE) issue within your solution can be time-consuming and costly, potentially disrupting development cycles and impacting your bottom line. Google and Canonical have a decade-long partnership based on the belief that software and infrastructure can be seamless and versatile without compromising scale, security, compliance, or reliability.

Join our webinar to discover how you can enhance the security of your complete software supply chain using Ubuntu Pro on Google Cloud. Explore the extensive coverage provided by the Ubuntu Universe, ensuring security for diverse workloads such as MongoDB, Apache Spark, Redis, Kafka, MySQL, NGINX, PostgreSQL, and language ecosystems including Python, Java, Ruby, and JavaScript/Node.js. 

In this webinar, you’ll learn:
-How to host your fully secured software supply chain on Google Cloud
-How Google Cloud provides the secure, open source, scalable infrastructure that enables organizations to run workloads on premises, in Google Cloud, or in any other public or private cloud.
-How Ubuntu Pro’s vulnerability patching process reduces the average CVE exposure time from 98 days to 1 day
-How Ubuntu Pro serves as a single trusted source for security patching for over 30,000 software packages
-How to easily upgrade from Ubuntu to Ubuntu Pro on GCP

Secure your supply chain on Google Cloud with Ubuntu Pro

Join us for a deep dive into the role of vector databases in generative AI applications. Vector databases facilitate efficient data representation, retrieval and manipulation, enabling AI systems to generate high-fidelity outputs across various domains, from natural language processing to image synthesis.

This webinar will discuss various concepts, such as generative AI, retrieval augmented generation (RAG), the importance of search engines, and efficient open source tooling that enables developers and enthusiasts to build their generative AI applications.

Vector databases for generative AI applications

In this webinar, we’ll share how confidential computing can bring hardware-level security to your sensitive AI workloads, both on-prem and on the public cloud.

Secure your AI workloads with Confidential VMs

As organisations increasingly look to take advantage of AI technologies, there are several critical considerations that they must contend with, including intellectual property, data security and costs related to computing infrastructure. Private cloud solutions are ideally suited to solving these challenges. Canonical Openstack, for instance, is a great example of a cloud platform that can be used to build and deploy machine learning applications securely and cost-effectively.

Why consider a private cloud for AI?
Private clouds are a handy solution for enterprises when it comes to AI/ML since they deliver many of the key capabilities that organisations report as important, including:
1) Cost optimisation: Private clouds enable businesses to optimise their costs by always running their workloads where it makes more sense from an economic standpoint.
2) Digital sovereignty: Private clouds offer a safe environment for data and applications by ensuring that the organisation owns access and controls the level of sharing amongst the different teams using the cloud.
3) Performance acceleration: Private clouds offer GPU virtualisation and other capabilities to improve performance and therefore project delivery, confidentiality, efficiency and time to setup as required by sophisticated AI/ML workloads. 

Learn more about AI on the private cloud in this webinar:
Join the webinar on 30 April 2024, where Tytus Kurek, OpenStack Product Manager, and Andreea Munteanu, AI Product Manager, will talk more about private clouds for AI projects. The presentation will cover:
1) Key considerations when building a private cloud for AI projects
2) Performance acceleration options for private cloud
3) Guidance for Kubernetes on OpenStack for AI initiatives
And more…

[APAC] AI on Private Cloud: why is it relevant in the hyperscalers era?

A real time kernel is designed to serve extreme latency-dependent use cases and to provide deterministic response times to service events.

In this webinar we will cover when and how you can deploy a real time kernel, giving examples of applications in healthcare, industrial, automotive, robotics, and more. We will talk about kernel preemption and preemption modes, with a deep dive on PREEMPT_RT (the out-of-tree patch for x86 and Arm architectures) and real time Ubuntu.

This webinar is designed for:
- Embedded software engineers
- Solutions/systems architects
- Developers
- IoT business developers
- Product managers

Real time kernel: use cases and deployment strategies with Ubuntu

You’ve probably heard of Linux, but maybe you’re not quite sure what it is, what you can do with it, and, more importantly, whether you can trust it to run your next project!

In this webinar, Canonical’s Ijlal Loutfi and Henry Coggill discuss the security of Linux and Ubuntu. We’ll start with the basics of why the operating system is important and how it underpins the integrity of any applications running on top. We will provide background information as to what Linux is, for those who might be unfamiliar with its history, and discuss how open-source software is developed and bundled into distributions.

We will discuss how the open-source ecosystem deals with security vulnerabilities, how they are discovered and fixed, and how end users react to this perpetual dance. Then we will go deeper into the range of security technology built into Ubuntu and what this means for protection against unknown threats. Finally, we will explore how Canonical’s enterprise-grade support delivers a comprehensive platform for secure open-source adoption.

Is Linux secure?

What can PostgreSQL do for AI application?

PostgreSQL is capable of efficiently storing and retrieving large amounts of data, such as training data for your models. Its wide support of the SQL standard, including SQL/MED, makes inspecting and querying that data a breeze. Moreover, PostgreSQL comes with similarity search capabilities, providing convenient index structures (GIST, GIN...) and built-in extensions (fuzzystrmatch, pg_trgm...).

Yet, there is more to PostgreSQL's ecosystem than the database server. There are more than 1000 extensions for PostgreSQL, many of which can be useful for AI developers and users, for example pgvector and PostgresML. 


The Role of PostgreSQL in MLOps

MLOps projects such as Kubeflow rely on relational databases for storing different artefacts, and choosing which relational database to use for MLOps is a common dilemma. We approached a similar topic in our recent webinar “PostgreSQL vs MySQL”, where we explored how, despite looking similar on the surface, the two databases are actually very different. The significant structural differences between databases can have a tremendous influence on the performance of any ML project, so understanding the possible impact is critical for both the enterprises who use these platforms and the engineers who develop them.


So how do we use PostgreSQL for machine learning?

Join the live discussion to learn more about using PostgreSQL for AI projects. The webinar will cover:
- An overview of the PostgreSQL ecosystem for AI projects
- Benefits of PostgreSQL for AI projects
- Use cases where PostgreSQL should be used for AI projects

Using PostgreSQL to power your AI applications

What does it mean to be a smarter enterprise, powered by artificial intelligence (AI) and big data? The possibilities reach far beyond today’s chatbots, self-driving cars, and product recommendation engines.

MicroCloud is the newest addition to Canonical’s cloud infrastructure portfolio. It is a low-touch, open-source cloud solution purpose-built for scalable clusters and edge deployments for all types of enterprises. With simplicity, security, and automation at its core, MicroCloud minimises the time and effort required to deploy and maintain a production-grade cloud infrastructure.

Join us as we delve into the features and benefits of MicroCloud, including its suitability for on-premise clouds and edge deployments at remote locations. Learn how MicroCloud caters to distributed environments, offering a simpler, more prescriptive cloud experience that makes zero-ops a reality for many industries.

Furthermore, discover how MicroCloud's lightweight architecture enables cost-effective deployments on both commodity and high-end hardware, with several options to further reduce its footprint depending on workload needs. Take advantage of this opportunity to explore Canonical MicroCloud and learn how it can transform your cloud infrastructure.

In this webinar, we will cover:
1) What is MicroCloud?
2) What are the challenges in today’s cloud infrastructure ecosystem and how does MicroCloud address them?
3) What are the use cases for MicroCloud?
4) How can you deploy your own MicroCloud?
5) What’s coming in the next release? 

Tune in live on April 16th, at 18:00 CET or watch on demand at your convenience.

MicroCloud: a low-touch open source cloud for all

Move to the cloud, they said. It will be fun, they said.

So you decided to do so, but now you’re facing an eternal dilemma: use one of the existing public cloud platforms or build your own? You ask yourself more questions: Which option is more convenient for your use case? Which one is more cost-effective? How do you preserve digital sovereignty regardless of the choice?

These are all good questions. We will cover them in this webinar. However, what you’re really searching for is more elementary. It is about how you can make use of available cloud technologies to meet your organisations’ needs. In other words, how you can do computing, your way?

During this webinar we will show you a “do it yourself” approach to cloud infrastructure implementation. By using mature open source technologies we will demonstrate the path towards your own production-grade cloud, preserving digital sovereignty and ensuring cost-effectiveness, while maintaining the versatility provided by global tech giants.

OpenStack is the world's most popular open source cloud platform and its adoption continues to grow exponentially every year. It serves as an extension or a reasonable alternative to hyperscalers, effectively addressing cloud cost optimisation concerns. But at the same time, OpenStack adoption has always been a challenge. Hence through this webinar, we want to help you get started with OpenStack.

In this webinar we will:
1) Discuss the current status of the cloud computing market
2) Delve into the world of OpenStack - the most popular open source cloud platform
3) Walk you through OpenStack’s high-level architecture, its services and their functions
4) Teach you how to get started and break the ice with OpenStack immediately

What is OpenStack and why does it matter?

AI is at the heart of a revolution in the technology space. From oil & gas to public sector, from telco to retail, all departments from all industries are looking for ways to put AI to work. Once organisations 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. Open source tools such as Jupyter Notebooks or MLflow are a great starting point and enable you to have a consistent experience on any cloud for your ML workloads. When scaling projects, the need for MLOps platforms such as Charmed Kubeflow is absolutely obvious.

Join our webinar to learn more about open source tooling for AI on public cloud. Led by Aaron Whitehouse, Senior Public Cloud Enablement Director, and Andreea Munteanu, AI Product Manager, the webinar will cover:

Scenarios in which open source tooling on public cloud solves a problem for AI initiatives
Main benefits of using open source tooling on the public cloud for AI projects
Use cases from our customers 
Hybrid cloud and multi cloud opportunities for AI projects

AI on public cloud with open source

Recent changes at VMware have compelled existing customers to consider alternatives. Many have turned their eyes to open source, looking for total cost of ownership (TCO) reduction and no vendor lock-in. But as a lead architect or an infrastructure owner, you know that this is easier said than done.

Join our webinar on 11 June at 4:30 pm CET and learn how to move from VMware to the future.

From VMware to the future:
Cloud computing is now a central piece of enterprise IT estates. According to Gartner, overall spending on cloud infrastructure will approach 50% of organisations’ IT budgets by 2025. However, moving from VMware to the cloud comes with many potential challenges that only a well-educated and trained infrastructure team can handle with no friction. In this webinar, we’ll present Canonical’s proven path to data centre cloudification.

Gain another decade of stability:
Canonical’s open source infrastructure comes with long-term support, security, and price commitment. This means that a successful transition results in at least another decade of stability. Even though the migration process is usually more tricky than a simple click, full data centre and workload cloudification leads to tangible business benefits. Don’t trust empty promises set by alleged industry leaders and learn how to execute this transition the right way.

Join this webinar to learn:
1) What the future of the infrastructure is going to look like
2) Details of data centre and workload cloudification process
3) About Canonical infrastructure components and their functions
4) How to effectively migrate out of the VMware infrastructure

From VMware to the Future

Open Source

Virtualization

Data Center

OpenStack

Cloud Computing

Private Cloud

Hybrid Cloud

Multi Cloud

Cloud Architecture

Cloud Adoption

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Enterprise Applications

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Application Management

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From VMware to the Future

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