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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 237
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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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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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Understanding How MySQL Collation and Charset Settings Impact Performance

Percona

Character encoding refers to the method used to represent characters as binary data for storage and transmission. How Character Sets Affect Data Storage and Retrieval You can specify the character set for each column when you create a table, indicating the set of characters allowed in that column.

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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.

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HammerDB for Managers

HammerDB

An important concept was to simulate database users called Virtual Users in parallel (rather than concurrently) to accurately simulate a real database workload with multiple users running from separate systems. The workload also outputted the data from the Virtual Users by simulating individual terminals. Derived Workloads.

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Continuous Performance Analysis with Lighthouse CI and GitHub Actions

CSS - Tricks

Here’s the simplest configuration that will run and collect Lighthouse reports for a static website project, and upload them to temporary public storage. // lighthouserc.js public', }, upload: { target: 'temporary-public-storage', }, }, }; The ci.collect object offers several options to control how the Lighthouse CI collects test reports.