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How To Use BenchmarkDotNet: 6 Simple Performance-Boosting Tips To Get Started

DZone

As software engineers, we are always striving for high performance and efficiency in our code. Whether it’s optimizing algorithms or fine-tuning data structures, every decision we make can have a significant impact on the overall performance of our applications.

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Kubernetes Observability: Code Profiling With Flame Graphs

Percona

It shows which code paths are more busy on the CPU in given samples. Kubernetes limitations In Linux, by default, performance system events can’t be collected by unprivileged users. This restricts the ability of running profilers to diagnose a performance issue from inside the container.

Code 106
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How to Assess MySQL Performance

HammerDB

Predicting application performance is a difficult art, but an important one when choosing the target deployment environment. In this blog, we aim to call out some key considerations when trying to assess MySQL performance for your application. We will not concern ourselves with the raw throughput of workload.

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Crucial Redis Monitoring Metrics You Must Watch

Scalegrid

Redis® is an in-memory database that provides blazingly fast performance. This makes it a compelling alternative to disk-based databases when performance is a concern. You might already use ScaleGrid hosting for Redis hosting to power your performance-sensitive applications.

Metrics 130
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New web performance insights with additional metrics and enhanced Visually complete for synthetic monitors

Dynatrace

Synthetic monitors are also the perfect tool to monitor performance baselines. This clean-room, lab-like environment allows you to react to slight changes in performance. It also gives you the first indication of whether a new deployment of your application or API leads to a performance improvement or, perhaps, a regression.

Metrics 203
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10 tips for migrating from monolith to microservices

Dynatrace

However, it’s common that teams need to refactor an application to help with performance after the lift-and-shift operation. Likewise, refactoring and rewriting code takes a lot of time and effort. In fact, it can be difficult to make code changes that won’t disrupt the entire system.

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The evolution of single-core bandwidth in multicore processors

John McCalpin

The primary metric for memory bandwidth in multicore processors is that maximum sustained performance when using many cores. This post is about a secondary performance characteristic — sustained memory bandwidth for a single thread running on a single core. Stay tuned! Details in the next blog entry.)