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Optimizing data warehouse storage

The Netflix TechBlog

At this scale, we can gain a significant amount of performance and cost benefits by optimizing the storage layout (records, objects, partitions) as the data lands into our warehouse. We built AutoOptimize to efficiently and transparently optimize the data and metadata storage layout while maximizing their cost and performance benefits.

Storage 208
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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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Introducing Netflix’s Key-Value Data Abstraction Layer

The Netflix TechBlog

These include challenges with tail latency and idempotency, managing “wide” partitions with many rows, handling single large “fat” columns, and slow response pagination. It also serves as central configuration of access patterns such as consistency or latency targets. Useful for keeping “n-newest” or prefix path deletion.

Latency 256
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Reducing Your Database Hosting Costs: DigitalOcean vs. AWS vs. Azure

Scalegrid

Since database hosting is more dependent on memory (RAM) than storage, we are going to compare various instance sizes ranging from just 1GB of RAM up to 64GB of RAM so you can see how costs vary across different application workloads. Does it affect latency? Yes, you can see an increase in latency. EC2 instances. VM instances.

Azure 344
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Faster time to value with enhanced handling of OneAgent runtime data

Dynatrace

Storage mount points in a system might be larger or smaller, local or remote, with high or low latency, and various speeds. Sometimes these locations landed on mount points which, due to capacity, availability, or access constraints, weren’t well suited for large runtime storage. See details below. See details below.

Storage 227
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Optimize your environment: Unveiling Dynatrace Hyper-V extension for enhanced performance and efficient troubleshooting

Dynatrace

Firstly, managing virtual networks can be complex as networking in a virtual environment differs significantly from traditional networking. Secondly, determining the correct allocation of resources (CPU, memory, storage) to each virtual machine to ensure optimal performance without over-provisioning can be difficult.

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Optimize Citrix platform performance and user experience with Dynatrace (GA)

Dynatrace

Therefore, it requires multidimensional and multidisciplinary monitoring: Infrastructure health —automatically monitor the compute, storage, and network resources available to the Citrix system to ensure a stable platform. Citrix latency represents the end-to-end “screen lag” experienced by a server’s users. Citrix VDA.

Latency 52