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Charmed MongoDB: use cases for financial services

Financial institutions handle vast amounts of sensitive and confidential data, including customer information, transaction details, and regulatory compliance records. A trusted database ensures the security and privacy of this sensitive information, protecting it from unauthorised access, breaches, or cyber threats. MongoDB is the ideal fit, and it’s one of the most widely used databases in the financial services industry. It provides a sturdy, adaptable and trustworthy foundation.

Cloud storage security best practices

Data is like the crown jewels of any organisation, if lost or exposed there could be severe repercussions. Failure to protect against system failure could lead to the loss of business data rendering a business non-functional and ultimately causing it’s failure. Exposing sensitive data to unauthorised parties not only leads to reputational damage, but can also cause businesses to incur massive fines.

Driving towards Environmental Parity and Software-Defined Vehicles with EB corbos Linux - built on Ubuntu

As the automotive industry continues to advance into the world of high-performance computing (HPC), it becomes increasingly crucial to achieve environmental parity for seamless software integration. In this blog post, we will explore the synergy between Elektrobit and Canonical at the core of ‘EB corbos Linux – built on Ubuntu‘ in the context of automotive computing.

Exploring edge computing in automotive

From autonomous cars to factories: how data processing at the edge will transform automotive Automotive is at the forefront of innovation, but challenges always come with change. One of those challenges is processing data in decentralised environments like factories or vehicles. In this webinar, you will learn about automotive use cases that require local data processing for confidential reasons, or simply due to networking constraints. We will also discuss what edge clouds bring to the table and how Canonical’s MicroCloud addresses the automotive industry’s edge computing challenges.

[Demo] Intel TDX 1.0 technology preview available on Ubuntu 23.10

Securing data at run-time has long been an open security challenge. Whether it is malicious insiders exploiting elevated privileges or attackers exploiting vulnerabilities within the platform’s privileged system software, your data’s confidentiality and integrity was at risk.

Still running Ubuntu 18.04? What you need to know

Ubuntu 18.04 LTS, installed by millions of users and continuing to have a massive footprint on AWS, hit its End of Standard Support in May 2023. When using an unsupported version of Ubuntu LTS, your system and your end users are vulnerable to security risks. Not every company has the time or resources to undertake a migration project to a later and supported Ubuntu LTS distribution which is why many are adopting Ubuntu Pro.

Driving into 2024 - The automotive trends to look out for in the year ahead

With multiple technological innovations all converging at the same time, we are living in an exciting era for the automotive industry. From AI to 5G, and plenty in between, we can expect to see a host of groundbreaking trends emerge this year. As electric vehicles (EVs) completely disrupt the market and the OEMs’ business strategies, the customer focus is shifting away from traditional internal combustion engine (ICE) vehicles, challenging the way that cars are being built and designed.

Introduction to Charmed Spark, A cloud-native Apache Spark solution on Kubernetes

🚀 A cloud-native Apache Spark® solution on Kubernetes with 10 years of support, compliance, and security maintenance, Charmed Spark® is now available! Enterprise data engineers want Apache Spark® with the ease and long-term security commitment of Ubuntu, and Charmed Spark is the first of many Canonical open-source data solutions designed for reliability and multi-cloud operations.

AI on-prem: what should you know?

Organisations are reshaping their digital strategies, and AI is at the heart of these changes, with many projects now ready to run in production. Enterprises often start these AI projects on the public cloud because of the ability to minimise the hardware burden. However, as initiatives scale, organisations often look to migrate the workloads on-prem for reasons including costs, digital sovereignty or compliance requirements.