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Virtual consensus in Delos

The Morning Paper

Virtual consensus in Delos , Balakrishnan et al. Back in 2017 the engineering team at Facebook had a problem. If you think of this a bit like mapping memory addresses to data in memory, then another parallel comes to mind: the virtual address space. We propose the novel abstraction of a virtual shared log (or VirtualLog).

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What Is a Workload in Cloud Computing

Scalegrid

Various forms can take shape when discussing workloads within the realm of cloud computing environments – examples include order management databases, collaboration tools, videoconferencing systems, virtual desktops, and disaster recovery mechanisms. Storage is a critical aspect to consider when working with cloud workloads.

Cloud 130
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How to Assess MySQL Performance

HammerDB

Regardless of whether the computing platform to be evaluated is on-prem, containerized, virtualized, or in the cloud, it is crucial to consider several essential factors. As database performance is heavily influenced by the performance of storage, network, memory, and processors, we must understand the upper limit of these key components.

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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. Conclusion.

Storage 56
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HammerDB for Managers

HammerDB

HammerDB is a software application for database benchmarking. Databases are highly sophisticated software, and to design and run a fair benchmark workload is a complex undertaking. The Transaction Processing Performance Council (TPC) was founded to bring standards to database benchmarking, and the history of the TPC can be found here.

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The top 5 reasons to run your own database benchmarks

HammerDB

Some opinions claim that “Benchmarks are meaningless”, “benchmarks are irrelevant” or “benchmarks are nothing like your real applications” However for others “Benchmarks matter,” as they “account for the processing architecture and speed, memory, storage subsystems and the database engine.”

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Percona Monitoring and Management 2 Scaling and Capacity Planning

Percona

PMM2 uses VictoriaMetrics (VM) as its metrics storage engine. Please note that the focus of these tests was around standard metrics gathering and display, we’ll use a future blog post to benchmark some of the more intensive query analytics (QAN) performance numbers. Virtual Memory utilization was averaging 48 GB of RAM.