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The latest News and Information on Cloud monitoring, security and related technologies.

6 Security Tips For Companies Using Cloud Technology

As businesses become increasingly reliant upon cloud technology, the need to protect sensitive data is becoming even more crucial. Hackers are constantly finding new vulnerabilities that can be exploited, so having the proper measures in place before any damage is done becomes essential for safeguarding customer information and company assets. Luckily there are a few steps that companies using cloud computing can take right now to make sure their data remains secure.

Decoding Logic App Dilemmas: How to Recurrence Trigger a Logic App at different hours and minutes?

Welcome again to another Decoding Logic App Dilemmas: Solutions for Seamless Integration! This time we will address another widespread problem which is to initiate the workflow at a different timeframe during the day or week with the same Azure Logic App Recurrence Trigger.

What is Azure Service Bus?

In the realm of cloud computing, communication and integration form the backbone of any robust architecture. With the exponential rise in distributed systems, the need for a reliable, scalable, and efficient message delivery system is more pertinent than ever. This is where Azure Service Bus, a cloud-based messaging service provided by Microsoft, becomes a game-changer.

Closer to the edge: what a locally national infrastructure can do for you

Edge computing is defined by bringing compute resources out of remote, centralised facilities and putting them at the source of the data itself. Processing and analysis is done where the data is actually generated. The performance and cost improvements that edge computing delivers are based on this proximity. By situating our data centres close to major populations, we have delivered these benefits to many UK businesses. It is an inherently ‘local’ idea.

Open Source MLOps on AWS

With the rise of generative AI, enterprises are growing their AI budgets, looking for options to quickly set up the infrastructure and run the entire machine learning cycle. Cloud providers like AWS are often preferred to kick-start AI/ML projects as they offer the computing power to experiment without long-term commitments. Starting on the cloud takes away the burden of computing power, reducing start-up time and cost and allowing teams to iterate more quickly.