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Kubernetes in the wild report 2023

Dynatrace

Most Kubernetes clusters in the cloud (73%) are built on top of managed distributions from the hyperscalers like AWS Elastic Kubernetes Service (EKS), Azure Kubernetes Service (AKS), or Google Kubernetes Engine (GKE). Accordingly, the remaining 27% of clusters are self-managed by the customer on cloud virtual machines.

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Netflix Cloud Packaging in the Terabyte Era

The Netflix TechBlog

Virtual Assembly Figure 3 describes how a virtual assembly of the encoded chunks replaces the physical assembly used in our previous architecture. It downloads the part(s) that contain the referenced, uploaded bytes and keeps them in an LRU active cache. For write operations, those challenges do not apply.

Cloud 237
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Building an elastic query engine on disaggregated storage

The Morning Paper

Building an elastic query engine on disaggregated storage , Vuppalapati, NSDI’20. If all data was read from S3 every time, performance would suffer, so of course Snowflake has a caching layer – a distributed ephemeral storage service shared by all the nodes in a warehouse. joins) during query processing.

Storage 112
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Dynatrace supports SnapStart for Lambda as an AWS launch partner

Dynatrace

Lambda then takes a snapshot of the memory and disk state of the initialized execution environment, persists the encrypted snapshot, and caches it for low-latency access. Saving your cloud operations and site reliability engineering teams hours of guesswork and manual tagging, the Davis AI engine analyzes billions of events in real time.

Lambda 232
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Percona Toolkit – A Quick Introduction to Summary

Percona

Percona Toolkit is a collection of advanced open source command-line tools, developed and used by the Percona technical staff, that are engineered to perform a variety of MySQL, MariaDB, MongoDB, and PostgreSQL server and system tasks that are too difficult or complex to perform manually. virtual = 2.2G Caches | 12.4G

Cache 99
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A MyRocks Use Case

Percona

I wrote this post on MyRocks because I believe it is the most interesting new MySQL storage engine to have appeared over the last few years. The use case is the TPC-C benchmark but executed not on a high-end server but on a lower-spec virtual machine that is I/O limited like for example, with AWS EBS volumes.

Storage 55
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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. Cached vs Scaled Workloads. The GNU General Public License v3.0 GPLv3) and a quick guide to GPLv3 can be viewed here.