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Five-nines availability: Always-on infrastructure delivers system availability during the holidays’ peak loads

Dynatrace

The nirvana state of system uptime at peak loads is known as “five-nines availability.” In its pursuit, IT teams hover over system performance dashboards hoping their preparations will deliver five nines—or even four nines—availability. But is five nines availability attainable? Downtime per year. 90% (one nine).

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The Ultimate Guide to Database High Availability

Percona

To make data count and to ensure cloud computing is unabated, companies and organizations must have highly available databases. This guide provides an overview of what high availability means, the components involved, how to measure high availability, and how to achieve it. Some disruption might occur, but it will be minimal.

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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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Why applying chaos engineering to data-intensive applications matters

Dynatrace

Stream processing One approach to such a challenging scenario is stream processing, a computing paradigm and software architectural style for data-intensive software systems that emerged to cope with requirements for near real-time processing of massive amounts of data. See more fault recovery experiments and insights in our full paper.

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Comparing Approaches to Durability in Low Latency Messaging Queues

DZone

A significant feature of Chronicle Queue Enterprise is support for TCP replication across multiple servers to ensure the high availability of application infrastructure. This is the first time I have benchmarked it with a realistic example.

Latency 275
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Why Tcl is 700% faster than Python for database benchmarking

HammerDB

Python is a popular programming language, especially for beginners, and consequently we see it occurring in places where it just shouldn’t be used, such as database benchmarking. We use stored procedures because, as the introductory post shows, using single SQL statements turns our database benchmark into a network test).

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Implementing service-level objectives to improve software quality

Dynatrace

Instead, they can ensure that services comport with the pre-established benchmarks. Using data from Dynatrace and its SLO wizard , teams can easily benchmark meaningful, user-based reliability measurements and establish error budgets to implement SLOs that meet business objectives and drive greater DevOps automation. Availability.

Software 263