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What are quality gates? How to use quality gates to deliver better software at speed and scale

Dynatrace

To remain competitive in today’s fast-paced market, organizations must not only ensure that their digital infrastructure is functioning optimally but also that software deployments and updates are delivered rapidly and consistently. They help foster confidence and consistency throughout the entire software development lifecycle (SDLC).

Speed 206
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Service level objectives: 5 SLOs to get started

Dynatrace

In today’s fast-paced digital landscape, ensuring high-quality software is crucial for organizations to thrive. Service level objectives (SLOs) provide a powerful framework for measuring and maintaining software performance, reliability, and user satisfaction. But the pressure on CIOs to innovate faster comes at a cost.

Latency 177
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Service level objective examples: 5 SLO examples for faster, more reliable apps

Dynatrace

In today’s fast-paced digital landscape, ensuring high-quality software is crucial for organizations to thrive. Service level objectives (SLOs) provide a powerful framework for measuring and maintaining software performance, reliability, and user satisfaction. But the pressure on CIOs to innovate faster comes at a cost.

Traffic 173
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Observability platform vs. observability tools

Dynatrace

Complex information systems fail in unexpected ways. Observability gives developers and system operators real-time awareness of a highly distributed system’s current state based on the data it generates. With observability, teams can understand what part of a system is performing poorly and how to correct the problem.

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Extending Vector with eBPF to inspect host and container performance

The Netflix TechBlog

by Jason Koch , with Martin Spier , Brendan Gregg , Ed Hunter Improving the tools available to our engineers to help them diagnose, triage, and work through software performance challenges in the cloud is a key goal for the cloud performance engineering team at Netflix. to the broader community.

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Accelerate Machine Learning with Amazon SageMaker

All Things Distributed

Amazon SageMaker then sets up the distributed compute cluster, installs the software, performs the training, and tears down the cluster when complete. Amazon SageMaker takes care of launching the instances, deploying the model, and setting up the HTTPS endpoint for your application to achieve low latency / high throughput prediction.

Tuning 94