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Implementing service-level objectives to improve software quality

Dynatrace

By implementing service-level objectives, teams can avoid collecting and checking a huge amount of metrics for each service. Instead, they can ensure that services comport with the pre-established benchmarks. This process includes benchmarking realistic SLO targets based on statistical and probabilistic analysis from Dynatrace.

Software 263
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Why you should benchmark your database using stored procedures

HammerDB

HammerDB uses stored procedures to achieve maximum throughput when benchmarking your database. HammerDB has always used stored procedures as a design decision because the original benchmark was implemented as close as possible to the example workload in the TPC-C specification that uses stored procedures. On MySQL, we saw a 1.5X

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Netflix at AWS re:Invent 2019

The Netflix TechBlog

We’ve compiled our speaking events below so you know what we’ve been working on. In this session, we discuss the technologies used to run a global streaming company, growing at scale, billions of metrics, benefits of chaos in production, and how culture affects your velocity and uptime. We look forward to seeing you there!

AWS 100
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Netflix at AWS re:Invent 2019

The Netflix TechBlog

We’ve compiled our speaking events below so you know what we’ve been working on. In this session, we discuss the technologies used to run a global streaming company, growing at scale, billions of metrics, benefits of chaos in production, and how culture affects your velocity and uptime. We look forward to seeing you there!

AWS 100
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HammerDB v4.0 New Features Pt1: TPROC-C & TPROC-H

HammerDB

For example HammerDB has not used tpmC terminology to report TPC-C based metrics instead using TPM and NOPM nomenclature. The HammerDB TPROC-C workload by design intended as CPU and memory intensive workload derived from TPC-C – so that we get to benchmark at maximum CPU performance at a much smaller database footprint.

C++ 40
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Netflix at AWS re:Invent 2019

The Netflix TechBlog

We’ve compiled our speaking events below so you know what we’ve been working on. In this session, we discuss the technologies used to run a global streaming company, growing at scale, billions of metrics, benefits of chaos in production, and how culture affects your velocity and uptime. We look forward to seeing you there!

AWS 37
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Real user monitoring vs. synthetic monitoring: Understanding best practices

Dynatrace

RUM gathers information on a variety of performance metrics. Data collected on page load events, for example, can include navigation start (when performance begins to be measured), request start (right before the user makes a request from the server), and speed index metrics (measure page load speed). Tools may be limited.