Name: How many use cases can you cover with PostgreSQL extensions?
Start: 2024-07-17T15:00:00Z
End: 2024-07-17T15:01:00.000Z
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.

Confidential computing is a revolutionary technology that disrupts the conventional threat model of public clouds. In the past, vulnerabilities within the extensive codebase of the cloud’s privileged system software, including the operating system and hypervisor, posed a constant risk to the confidentiality and integrity of code and data in operation. Likewise, unauthorized access by a cloud administrator could compromise the security of your virtual machine (VM). 

To protect your data and code against such threats on Google Cloud, Ubuntu Confidential VMs (CVMs) offer enhanced security for your workloads by utilizing hardware-protected Trusted Execution Environments (TEEs). To achieve such strong security guarantees, Ubuntu Confidential VMs build on Intel’s innovations at the silicon level, and the foundation laid by  Intel® Trust Domain Extensions (Intel® TDX).  Ubuntu also offers further primitives to further secure your CVMs at rest, and offer a strong remote attestation.  

Come join this webinar to learn about the great engineering that goes into making Ubuntu confidential VMs with Intel TDX on Google Cloud, and how you use them to implement a zero trust strategy for your security-sensitive application.

Join this webinar to learn about the intricate engineering that goes into making Ubuntu confidential VMs with Intel TDX on Google Cloud.

Exploring Ubuntu Confidential VMs with Intel TDX on Google Cloud

Across the world, the application of Artificial Intelligence and Machine Learning (AI/ML) to business challenges is a hot topic. But, what does it mean for storage systems, and how can open source storage answer those needs? Without data, and speedy access to it, AI solutions might not deliver the results as quickly as expected, delaying insights and innovation. Canonical Ceph is a great example of a highly scalable open source storage solution that can be used to back modern AI/ML workflows and unlock the full potential of your AI ecosystem.
In this webinar we will explore typical use cases for external storage for AI systems, the workflows, the impact AI has on storage systems, and also the impact that storage systems can have on your AI jobs.

AI Storage with Ceph

If you’re a technology channel organization, you and your customers are probably considering  alternatives for virtualized environments amid shifting market forces, escalating costs, and vendor realignment. The solution needs to be cost-efficient while providing comparable technical capabilities to the status quo. In this webinar, you’ll learn how Canonical (the company behind Ubuntu) fills that need and the ease of reselling the solution. 

Open source private clouds can offer alternatives for everything in your customers’ stack. From virtualization to Hypervisor to storage and more. Canonical offers a cost-effective open source cloud approach that provides a rich set of capabilities and a migration path from existing cloud environments. 

This webinar is for technology companies in the channel that are proactive in creating better solutions for their customers and whose customers are struggling with finding alternatives to their current virtualized environments. Canonical wants to help you get in front of customers with solutions that will free them from the lock-in of legacy Hypervisor vendors.

In this webinar you’ll learn:
- The capabilities of Open Source Private Cloud compared to alternatives
- Reselling Open Source Private Cloud solutions to your customers
- Price Point Comparison between Canonical and alternatives
- The growth of open source for clouds

Private Cloud Alternatives for Channel Partners

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

If you’re a technology channel organization, you and your customers are probably considering  alternatives for virtualized environments amid shifting market forces, escalating costs, and vendor realignment. The solution needs to be cost-efficient while providing comparable technical capabilities to the status quo. In this webinar, you’ll learn how Canonical (the company behind Ubuntu) fills that need and the ease of reselling the solution. 

Open source private clouds can offer alternatives for everything in your customers’ stack. From virtualization to Hypervisor to storage and more. Canonical offers a cost-effective open source cloud approach that provides a rich set of capabilities and a migration path from existing cloud environments. 

This webinar is for technology companies in the channel that are proactive in creating better solutions for their customers and whose customers are struggling with finding alternatives to their current virtualized environments. Canonical wants to help you get in front of customers with solutions that will free them from the lock-in of legacy Hypervisor vendors.

Often, the advantages for you are the same advantages that customers get:
- Flexibility in your solution portfolio 
- Lower Total Cost of Ownership for customers at a crossroads with current providers
- Enterprise grade security for Open Source software packages beyond Ubuntu
- Greater profitability for your business 
- No vendor lock-in which provides flexibility for your customers

Canonical recently announced the availability of the latest version of Real-time Ubuntu and its availability on Raspberry Pi hardware. In this webinar we’ll be discussing:

Real-time fundamentals:
- Key use cases across different market segments
- The role of PREEMPT_RT patchset in enhancing predictability
- RTOS, low latency or real-time Linux?

Understanding Real-time Ubuntu 24.04 LTS:
- Latest developments in Real-time Ubuntu 24.04 LTS
- Support for Raspberry Pi 4 and 5
- Long-term Support and security

Join the webinar for a comprehensive look at the core concepts behind real-time systems and the PREEMPT_RT patch set. You will learn about the latest features and optimisations for Raspberry Pi hardware and discover how Real-time Ubuntu 24.04 LTS can enhance the performance and reliability of your applications. 

Reserve your spot now.

Discover real-time kernel on Ubuntu 24.04 and Raspberry Pi

On June 4th 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

Each type of NoSQL database offers unique strengths and is suited to specific types of applications and data requirements, making them versatile tools in modern data management. Many of them are compatible with an open source approach, giving you advantages such as the acceleration of innovation, flexibility, customisation, and community support. There are also innovations in the space where databases can run in a multi-cloud environment. 
However, these features and benefits come with their own set of challenges, and operating database clusters can be difficult. In addition, databases need to be integrated within a stack of technologies, such as the infrastructure it is deployed on and other data and AI tools. Faced with these and other challenges (like unpredictable costs and industry skill gaps), companies are finding it increasingly difficult to achieve operational excellence with an in-house team to manage databases. This is why they turn to managed service providers (MSPs).

In this webinar, Canonical product managers Michelle Tabirao (NoSQL Databases) and Adrian Matei (Managed Services) will dive into what operational excellence means for NoSQL Databases, and how this can be achieved with a managed service provider. We will explore: 

1) Introduction and main advantages of adopting NoSQL databases
2) Big data and AI use cases that leverage non-relational databases
3) Operational excellence in NoSQL Databases, from key operations to holistic approaches 
4) Benefits and challenges when choosing a managed service provider for your NoSQL database operations 
5) Future of NoSQL databases

Join us on the 18th of June 2024 for 30 minutes of expertise in NoSQL operations!

Managed NoSQL databases for big data and AI-powered applications

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?

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

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

There are benefits to using a specialised database for every new use case you need to support. For example, we can make a case for using a graph database to manipulate graph data, or a specialised vector database to manage vectors. Yet, multiplying your data stores comes with consistency, cost and operability issues that you need to consider carefully.

PostgreSQL is built from the ground up to be extensible, so you can choose from over 1000 extensions to cover more use cases with the same solution – saving you time and resources.

In this webinar, we will examine the use cases you can meet with just PostgreSQL.We will cover the following:
Analytics 
Online transaction processing 
Geospatial data
Graph data 
Search and similarity
AI and ML 
Time Series and more

How many use cases can you cover with PostgreSQL extensions?

Data Analysis

Database Management

Data Architecture

Data Management

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Analytics

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How many use cases can you cover with PostgreSQL extensions?

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