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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 347
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Using SLOs to become the optimization athlete with Dynatrace

Dynatrace

For example, an athlete must be in tune with their body to know when something isn’t operating right which could impact their future performance. In our exercise: Metric 1 (Number of requests with a response time > 1 second): requires the creation of a calculated metric with the right filter. Ability to define automatic baselining.

Metrics 242
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Pushy to the Limit: Evolving Netflix’s WebSocket proxy for the future

The Netflix TechBlog

Where aws ends and the internet begins is an exercise left to the reader. KeyValue is an abstraction over the storage engine itself, which allows us to choose the best storage engine that meets our SLO needs. This delicate balance led to us doing a deep evaluation of many instance types and performance tuning options.

Latency 234
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A Decade of Dynamo: Powering the next wave of high-performance, internet-scale applications

All Things Distributed

Manageable – DynamoDB eliminates the need for manual capacity planning, provisioning, monitoring of servers, software upgrades, applying security patches, scaling infrastructure, monitoring, performance tuning, replication across distributed datacenters for high availability, and replication across new nodes for data durability.

Internet 111
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How to Assess MySQL Performance

HammerDB

Instead, focus on understanding what the workloads exercise to help us determine how to best use them to aid our performance assessment. As database performance is heavily influenced by the performance of storage, network, memory, and processors, we must understand the upper limit of these key components. Operating System: Ubuntu 22.04

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Evaluating the Evaluation: A Benchmarking Checklist

Brendan Gregg

A co-worker introduced me to Craig Hanson and Pat Crain's performance mantras, which neatly summarize much of what we do in performance analysis and tuning. sounds like a homework exercise of purely academic value. They are: **Performance mantras**. Don't do it. Do it, but don't do it again. Do it less. Do it later. Do it concurrently.

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Evaluating the Evaluation: A Benchmarking Checklist

Brendan Gregg

A co-worker introduced me to Craig Hanson and Pat Crain's performance mantras, which neatly summarize much of what we do in performance analysis and tuning. sounds like a homework exercise of purely academic value. They are: **Performance mantras**. Don't do it. Do it, but don't do it again. Do it less. Do it later. Do it concurrently.