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Why you need Dynatrace on Azure Workloads

Dynatrace

In addition to the OneAgent collecting all these metrics, Dynatrace has an integration with Azure Monitor to capture additional metrics for platform services such as Storage Accounts, Redis Cache, API Management Services, Load Balancers among others. Dynatrace does this by querying Azure monitor APIs to collect platform metrics.

Azure 137
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What is a Distributed Storage System

Scalegrid

A distributed storage system is foundational in today’s data-driven landscape, ensuring data spread over multiple servers is reliable, accessible, and manageable. Understanding distributed storage is imperative as data volumes and the need for robust storage solutions rise.

Storage 130
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Redis® Monitoring Strategies for 2024

Scalegrid

To monitor Redis® instances effectively, collect Redis metrics focusing on cache hit ratio, memory allocated, and latency threshold. Advanced monitoring techniques enable you to identify potential issues, such as high latency, CPU utilization, command throughput, and cache hit rate before they become major problems.

Strategy 130
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What is a data lakehouse? Combining data lakes and warehouses for the best of both worlds

Dynatrace

Data warehouses offer a single storage repository for structured data and provide a source of truth for organizations. This approach enables organizations to use this data to build artificial intelligence (AI) and machine learning models from large volumes of disparate data sets. How does a data lakehouse work? Data management.

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5 data integration trends that will define the future of ETL in 2018

Abhishek Tiwari

More importantly, UDM utilizes a single storage backend with benefits of multiple storage systems which avoids moving data across systems hence data duplication, and data consistency issues. Delta implements the unified data management layer by extending the Amazon S3 object storage for ACID transactions and automatic data indexing.

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The Future in Visual Computing: Research Challenges

ACM Sigarch

As a result of these different types of usages, a number of interesting research challenges have emerged in the domain of visual computing and artificial intelligence (AI). The tremendous growth in visual computing is fueled by the rapid increase in deployment of visual sensing (e.g.