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

The Netflix TechBlog

The second phase involves migrating the traffic over to the new systems in a manner that mitigates the risk of incidents while continually monitoring and confirming that we are meeting crucial metrics tracked at multiple levels. It provides a good read on the availability and latency ranges under different production conditions.

Traffic 339
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Service level objectives: 5 SLOs to get started

Dynatrace

Certain SLOs can help organizations get started on measuring and delivering metrics that matter. Fitness app : The fitness app should offer a response time of less than 500 milliseconds for exercise tracking and data recording. This SLO enables a smooth and uninterrupted exercise-tracking experience.

Latency 179
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Service level objective examples: 5 SLO examples for faster, more reliable apps

Dynatrace

Certain service-level objective examples can help organizations get started on measuring and delivering metrics that matter. Fitness app : The fitness app should offer a response time of less than 500 milliseconds for exercise tracking and data recording. This SLO enables a smooth and uninterrupted exercise-tracking experience.

Traffic 173
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Failure Modes and Continuous Resilience

Adrian Cockcroft

There are many possible failure modes, and each exercises a different aspect of resilience. Collecting some critical metrics at one second intervals, with a total observability latency of ten seconds or less matches the human attention span much better. Try to measure your mean time to respond (MTTR) for incidents.

Latency 52
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Failure Modes and Continuous Resilience

Adrian Cockcroft

There are many possible failure modes, and each exercises a different aspect of resilience. Collecting some critical metrics at one second intervals, with a total observability latency of ten seconds or less matches the human attention span much better. Try to measure your mean time to respond (MTTR) for incidents.

Latency 53
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MezzFS?—?Mounting object storage in Netflix’s media processing platform

The Netflix TechBlog

Mounting object storage in Netflix’s media processing platform By Barak Alon (on behalf of Netflix’s Media Cloud Engineering team) MezzFS (short for “Mezzanine File System”) is a tool we’ve developed at Netflix that mounts cloud objects as local files via FUSE. Our object storage service splits objects into many parts and stores them in S3.

Media 214