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Migrating Critical Traffic At Scale with No Downtime?—?Part 1

The Netflix TechBlog

Migrating Critical Traffic At Scale with No Downtime — Part 1 Shyam Gala , Javier Fernandez-Ivern , Anup Rokkam Pratap , Devang Shah Hundreds of millions of customers tune into Netflix every day, expecting an uninterrupted and immersive streaming experience. This approach has a handful of benefits.

Traffic 339
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Migrating Critical Traffic At Scale with No Downtime?—?Part 2

The Netflix TechBlog

Migrating Critical Traffic At Scale with No Downtime — Part 2 Shyam Gala , Javier Fernandez-Ivern , Anup Rokkam Pratap , Devang Shah Picture yourself enthralled by the latest episode of your beloved Netflix series, delighting in an uninterrupted, high-definition streaming experience. This is where large-scale system migrations come into play.

Traffic 279
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Efficient SLO event integration powers successful AIOps

Dynatrace

For instance, consider how fine-tuned failure rate detection can provide insights for comprehensive understanding. Please refer to How to fine-tune failure detection (dynatrace.com) for further information. SLOs must be evaluated at 100%, even when there is currently no traffic. What characterizes a weak SLO?

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Rapid Event Notification System at Netflix

The Netflix TechBlog

Motivation With the rapid growth in Netflix member base and the increasing complexity of our systems, our architecture has evolved into an asynchronous one that enables both online and offline computation. This helps limit the outgoing traffic footprint considerably.

Systems 334
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Unlock end-to-end observability insights with Dynatrace PurePath 4 seamless integration of OpenTracing for Java

Dynatrace

Cloud-native technologies and microservice architectures have shifted technical complexity from the source code of services to the interconnections between services. Heterogeneous cloud-native microservice architectures can lead to visibility gaps in distributed traces. Dynatrace news. What’s next?

Java 239
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Data lakehouse innovations advance the three pillars of observability for more collaborative analytics

Dynatrace

The short answer: The three pillars of observability—logs, metrics, and traces—converging on a data lakehouse. You’re getting all the architectural benefits of Grail—the petabytes, the cardinality—with this implementation,” including the three pillars of observability: logs, metrics, and traces in context.

Analytics 191
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Telltale: Netflix Application Monitoring Simplified

The Netflix TechBlog

A metric crossed a threshold. You’re half awake and wondering, “Is there really a problem or is this just an alert that needs tuning? Telltale learns what constitutes typical health for an application, no alert tuning required. Metrics are a key part of understanding application health. Regional traffic evacuations.