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Netflix Cloud Packaging in the Terabyte Era

The Netflix TechBlog

From chunk encoding to assembly and packaging, the result of each previous processing step must be uploaded to cloud storage and then downloaded by the next processing step. Since not all projects are terabytes projects, allocating the largest cloud storage to all packager instances is not an efficient use of cloud resources.

Cloud 242
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Kubernetes in the wild report 2023

Dynatrace

Accordingly, the remaining 27% of clusters are self-managed by the customer on cloud virtual machines. In comparison, on-premises clusters have more and larger nodes: on average, 9 nodes with 32 to 64 GB of memory. Java Virtual Machine (JVM)-based languages are predominant. Most organizations, 72%, use Java to some degree.

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Mastering Disk Space Management with MongoDB® Storage Engines

Scalegrid

MongoDB offers several storage engines that cater to various use cases. The default storage engine in earlier versions was MMAPv1, which utilized memory-mapped files and document-level locking. The newer, pluggable storage engine, WiredTiger, addresses this by using prefix compression, collection-level locking, and row-based storage.

Storage 130
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The Best Way to Host MySQL on Azure Cloud

Scalegrid

You’ll learn more about the best instance types and disks to use below, and you can check out this MySQL Provider Comparison to see the advantages and limitations of the top four managed MySQL solutions, ScaleGrid, Compose, Azure Database, and Amazon RDS. Azure Virtual Networks. High Availability Deployment.

Azure 219
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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. Comparison of these metrics between VDAs characterizes load balancing efficiency.

Latency 52
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Optimize Citrix platform performance and user experience with a new extension (Preview)

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. Comparison of these metrics between VDAs characterizes load balancing efficiency.

Latency 164
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Percona Monitoring and Management 2 Scaling and Capacity Planning

Percona

PMM2 uses VictoriaMetrics (VM) as its metrics storage engine. Virtual Memory utilization was averaging 48 GB of RAM. 25 Bytes, or you should plan storage roughly between 500 GB – one TB for a default 30 day retention period. The CPU usage averaged 24% utilization, as you can see in the above picture.