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Service level objectives: 5 SLOs to get started

Dynatrace

Fitness app : The fitness app should offer a response time of less than 500 milliseconds for exercise tracking and data recording. This SLO enables a smooth and uninterrupted exercise-tracking experience. This SLO highlights the importance of a smooth and efficient checkout experience. Thus, an ApDex score of 0.85

Latency 171
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Service level objective examples: 5 SLO examples for faster, more reliable apps

Dynatrace

Fitness app : The fitness app should offer a response time of less than 500 milliseconds for exercise tracking and data recording. This SLO enables a smooth and uninterrupted exercise-tracking experience. This SLO example highlights the importance of a smooth and efficient checkout experience. or above for the checkout process.

Traffic 173
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Carving an AWS certification path

Dynatrace

Hosted and moderated by Amazon, AWS GameDay is a hands-on, collaborative, gamified learning exercise for applying AWS services and cloud skills to real-world scenarios. In addition, 45% of them have gone on to implement efficiencies in their roles, and 43% reported they were able to do their job more quickly after getting certified.

AWS 201
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Teaching rigorous distributed systems with efficient model checking

The Morning Paper

Teaching rigorous distributed systems with efficient model checking Michael et al., During the ten week course, students implement four different assignments: an exactly-once RPC protocol; a primary-backup system; Paxos; and a scalable, transactional key-value storage system. Consider the lab exercise to implement Paxos.

Systems 43
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Using SLOs to become the optimization athlete with Dynatrace

Dynatrace

Continuous improvement of services is the most efficient process for all teams that are looking to improve the performance of their applications by considering all layers of their architecture. Similar to an athlete, the objective here is to have teams always push the limits to become faster and stronger.

Metrics 161
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Why the Optimizer Doesn't Use Buffer Pool Knowledge

SQL Performance

Whether the page is dirty or not (a dirty page has changes on it that haven’t yet been written back to durable storage). Let’s pretend there *is* a highly efficient mechanism to determine buffer pool contents the optimizer can use to help it choose which index to use in a query plan.

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Fun with (columnstore) compression on a very large table – part 1

SQL Performance

Of course we can always throw more disk at a table, but I wanted to see if we could scale this more efficiently than the current linear trend. Note that I am not focusing on reporting workload or other read query performance at this time – I merely want to see what impact I can have on storage (and memory) footprint of this data.