17%
30.01.2020
are available for them during this period. A single slow-drain device can lead to a massive drop in the performance of many SAN devices (fabric congestions). Although most FC switch manufacturers have now
17%
09.08.2015
leading open source groupware alternatives.
Table 1 compares the LDAP support in the open source groupware tools Open-Xchange [1], Tine 2.0 [2], Zarafa [3], Kolab [4], EGroupware [5], Scalix [6
17%
02.06.2020
of deep learning in recent years is largely the result of the availability of extremely high computing power and masses of training data. Even more computing power and even more data will certainly lead
17%
02.06.2020
, a continuous stream of incoming vehicles tends to bunch together. The size of the bunch depends on the width of the exit. This bunching of traffic inevitably leads to additional accidents. Throughput is reduced
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09.06.2018
process, so to speak.
Combining several services and programs into the container against your better judgement almost inevitably leads to problems. You then have to work with shell scripts
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04.12.2024
data', which goes further than what many proprietary or ostensibly Open Source models do today," said Ayah Bdeir, who leads AI strategy at Mozilla.
Read the full text of the definition at OSI: https
17%
30.01.2024
, potentially leading to the kind of operational disruptions that monitoring is intended to avoid. This article is not about security monitoring of tier 0 systems, but about classic status and event monitoring
17%
01.06.2024
environment to reconstruct the plaintext password (offline cracking). Because the leading ransomware gangs already tapped into the as-a-service business model some time ago, the GPU power required for cracking
17%
07.04.2022
roads lead to Rome.
Juniper itself offers a proprietary automation engine in its Junos OS switch and router operating system. It is simply known as "Junos automation" and offers several interfaces
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26.03.2025
and the protection it provides against re-identification. However, it can lead to a loss of information and reduced data quality if the generalization is not sufficiently granular.
Table 1
k
