Remove Engineering Remove Latency Remove Metrics
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Optimising for High Latency Environments

CSS Wizardry

This gives fascinating insights into the network topography of our visitors, and how much we might be impacted by high latency regions. Round-trip-time (RTT) is basically a measure of latency—how long did it take to get from one endpoint to another and back again? RTT data should be seen as an insight and not a metric.

Latency 215
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Build systems more reliably with Dynatrace: Chaos Engineering

Dynatrace

This approach enhances key DORA metrics and enables early detection of failures in the release process, allowing SREs more time for innovation. This blog post explores the Reliability metric , which measures modern operational practices. It forms the cornerstone of chaos engineering experiments. Why reliability?

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Enhancing Kubernetes cluster management key to platform engineering success

Dynatrace

Five of the most common include cluster instability, resource and cost management, security, observability, and stress on engineering teams. Engineering teams are overwhelmed with stuff to do.” ” First, Akamas collects metrics, then recommends configuration improvements and applies these recommendations. .

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AI-driven analysis of Spring Micrometer metrics in context, with typology at scale

Dynatrace

Micrometer is used for instrumenting both out-of-the-box and custom metrics from Spring Boot applications. Davis topology-aware anomaly detection and alerting for your Micrometer metrics. Topology-related custom metrics for seamless reports and alerts. Micrometer uses a registry to export metrics to monitoring systems.

Metrics 220
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Why applying chaos engineering to data-intensive applications matters

Dynatrace

Stream processing enables software engineers to model their applications’ business logic as high-level representations in a directed acyclic graph without explicitly defining a physical execution plan. We designed experimental scenarios inspired by chaos engineering. This significantly increases event latency.

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Migrating Netflix to GraphQL Safely

The Netflix TechBlog

By the summer of 2020, many UI engineers were ready to move to GraphQL. The GraphQL shim enabled client engineers to move quickly onto GraphQL, figure out client-side concerns like cache normalization, experiment with different GraphQL clients, and investigate client performance without being blocked by server-side migrations.

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Investigation of a Workbench UI Latency Issue

The Netflix TechBlog

Symptom Machine Learning engineer Luca Pozzi reported to our Data Platform team that their JupyterLab UI on their workbench becomes slow and unresponsive when running some of their Notebooks. Using this approach, we observed latencies ranging from 1 to 10 seconds, averaging 7.4 We then exported the .har

Latency 217