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Observability platform vs. observability tools

Dynatrace

With observability, teams can understand what part of a system is performing poorly and how to correct the problem. Traces provide performance data about tasks that are performed by invoking a series of services. A database could start executing a storage management process that consumes database server resources.

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SQL Server I/O Basics Chapter #2

SQL Server According to Bob

KB sectors run on smaller sectors   14 System and sample databases   15 Determining the formatted sector size of database   15 What sector sizes does SQL Server support? KB boundary   12 Larger transaction logs   13 Restore and attach   14 Format for 4 ?KB

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ChatGPT, Author of The Quixote

O'Reilly

To me, the analogy breaks down before it begins: firstly, LLMs don’t merely blur, but perform highly non-linear transformations, which means you can’t just squint and get a sense of the original; secondly, for the photocopier, the error is a bug, whereas, for LLMs, all errors are features. .” joined Flickr.

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Simple Parameterization and Trivial Plans — Part 2

SQL Performance

For the time being, let’s look at some examples using the Stack Overflow 2010 database on SQL Server 2019 CU 14. Database compatibility is set to 150, and the cost threshold for parallelism is set to 50 to avoid parallelism for now: ALTER DATABASE SCOPED CONFIGURATION. When simple parameterization isn’t performed, the 1.

Cache 90
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Refreshing SQL Server Tables With Less Interruption Using Partition Switching

SQL Performance

There are several methods to reload entire tables while they’re actively being queried; two decades ago, I took unbridled advantage of sp_rename — I’d play a shell game with an empty shadow copy of the table, happily reloading the shadow copy and then only performing the rename inside a transaction. SQL Server Partition Switching Example.

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The Amazing Evolution of In-Memory Computing

ScaleOut Software

When first introduced, distributed caching offered a breakthrough for applications by storing fast-changing data in memory on a server cluster for consistently fast response times, while simultaneously offloading database servers that would otherwise become bottlenecked.

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The Amazing Evolution of In-Memory Computing

ScaleOut Software

When first introduced, distributed caching offered a breakthrough for applications by storing fast-changing data in memory on a server cluster for consistently fast response times, while simultaneously offloading database servers that would otherwise become bottlenecked.