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The Three Cs: Concatenate, Compress, Cache

CSS Wizardry

Caching them at the other end: How long should we cache files on a user’s device? Cache This is the easy one. Caching is something I’ve been a little obsessed with lately , but for static assets as we’re discussing today, we don’t need to know much other than: cache everything as aggressively as possible.

Cache 353
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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 246
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Best practices and key metrics for improving mobile app performance

Dynatrace

As a result, organizations need to monitor mobile app performance metrics that are meaningful and actionable by gaining adequate observability of mobile app performance. There are many common mobile app performance metrics that are used to measure key performance indicators (KPIs) related to user experience and satisfaction.

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The road to observability with OpenTelemetry demo part 1: Identifying metrics and traces

Dynatrace

That is, relying on metrics, logs, and traces to understand what software is doing and where it’s running into snags. In addition to tracing, observability also defines two other key concepts, metrics and logs. When software runs in a monolithic stack on on-site servers, observability is manageable enough. What is OpenTelemetry?

Metrics 245
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What is? OpenTelemetry??An open-source standard for logs, metrics, and traces

Dynatrace

Loosely defined, observability is the ability to understand what’s happening inside a system from the knowledge of the external data it produces, which are usually logs, metrics, and traces. Logs, metrics, and traces make up the bulk of all telemetry data. This occurs once data is safely stored within a local cache.

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Introducing Configurable Metaflow

The Netflix TechBlog

Imagine a ML practitioner on the Netflix Content ML team, sourcing features from hundreds of columns in our data warehouse, and creating a multitude of models against a growing suite of metrics. this could take a few minutes) All packages already cached in s3. All environments already cached in s3. nflxfastdata(2.13.5);nflx(2.13.5);metaboost(0.0.27)

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Seeing through hardware counters: a journey to threefold performance increase

The Netflix TechBlog

We also see much higher L1 cache activity combined with 4x higher count of MACHINE_CLEARS. a usage pattern occurring when 2 cores reading from / writing to unrelated variables that happen to share the same L1 cache line. Cache line is a concept similar to memory page?—? Thread 0’s cache in this example.

Hardware 363