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Advancing Application Performance With NVMe Storage, Part 2

DZone

Normally, GPU nodes don't have much room for SSDs, which limits the opportunity to train very deep neural networks that need more data. For example, one well-respected vendor's standard solution is limited to 7.5TB of internal storage, and it can only scale to 30TB.

Storage 100
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Designing Instagram

High Scalability

Firstly, the synchronous process which is responsible for uploading image content on file storage, persisting the media metadata in graph data-storage, returning the confirmation message to the user and triggering the process to update the user activity. Some of the keys of understanding the user network are listed below.

Design 334
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Bring syslog into Dynatrace using OpenTelemetry to get open source value with enterprise support

Dynatrace

Getting insights into the health and disruptions of your networking or infrastructure is fundamental to enterprise observability. For example, a supported syslog component must support the masking of sensitive data at capture to avoid transmitting personally identifiable information or other confidential data over the network.

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Dynatrace and Red Hat expand enterprise observability to edge computing

Dynatrace

As an example, many retailers already leverage containerized workloads in-store to enhance customer experiences using video analytics or streamline inventory management using RFID tracking for improved security. Moreover, edge environments can be highly dynamic, with devices frequently joining and leaving the network.

Retail 258
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Best practices and key metrics for improving mobile app performance

Dynatrace

Mobile applications (apps) are an increasingly important channel for reaching customers, but the distributed nature of mobile app platforms and delivery networks can cause performance problems that leave users frustrated, or worse, turning to competitors. Load time and network latency metrics. Proactive monitoring.

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SIEM Volume Spike Alerts Using ML

DZone

Key Components in SIEM Log Collection: SEIM systems collect and aggregate log data from Various sources across an organization’s network, including servers, endpoints, firewalls, applications, and other devices. For example, in big organizations, the Linux logs may be around 10 billion, and firewall logs may be around five billion per day.

Storage 136
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Getting answers from data starts with automated log acquisition, at any scale

Dynatrace

Collecting logs that aren’t relevant to their business case creates noise, overloads congested networks, and slows down teams. To control local network data volume and potential congestion, Dynatrace also allows filtering of log data on-source—by specific host, service, or even log content—before data is sent to the cloud.

Storage 226