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Logging solutions are a must-have for any company with software systems. They are necessary to monitor your software solution’s health, prevent issues before they happen, and troubleshoot existing problems. The market has many solutions which all focus on different aspects of the logging problem. These solutions include both open source and proprietary software and tools built into cloud provider platforms, and give a variety of different features to meet your specific needs.
One of the most important uses of Artificial Intelligence (AI) and Machine Learning (ML) lies in the detection and prevention of criminal activities. Today, companies are widely using AI-powered computer vision devices to predict and detect crimes ranging from frauds and theft to violence and cybercrimes. The developments in computer vision technologies enabled authorities to simplify incident reporting and crime detection more efficiently.
Open source is eating the world. Companies have realized and embraced that, and ever more companies today are built around a successful open source project. But there’s also a disturbing counter-movement: vendors relicensing popular open source projects to restrict usage. Last week it was Grafana Labs which announced relicensing Grafana, Loki and Tempo, its popular open source monitoring tools, from Apache2.0 to the more restrictive GNU AGPLv3 license.
In most cases, when users start to access and use a new application or a new release, app performs pretty well. As the user base grows and usage increases, the app can outgrow its infrastructure. Users can start experiencing a dip in performance. Latency increases, bandwidth and memory get exhausted quickly, and some code architectures start to fail because they do not scale well with the increased amount of users.
Here's a quick two-minute video demonstrating the power of Ivanti's UEM for Mobile and Mobile Threat Defense and this time detecting a leaky app, specifically the very popular video-sharing TikTok app. Tiktok has had a history of vulnerabilities where the personal information of users was exposed and could have potentially been harvested and leaked out by malicious cyber threat actors.