Doordash.engineering

Why Burnout is Hard to Detect

WEBBurnout refers specifically to phenomena in the occupational context and should not be applied to describe experiences in other areas of life.”. Burnout is …

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URL: https://doordash.engineering/2021/09/02/why-burnout-is-hard-to-detect/

How to Handle Kubernetes Health Checks

WEBHere are our recommended steps to avoid similar issues: 1. Understand the different applications of the various Kubernetes probes. Ensure the entire department is …

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6 Best Practices to Manage Pull Request Creation and Feedback

WEBWrite descriptive and consistent names. Create a clear PR title and description. Keep PRs short (same applies to files and functions) Manage PR …

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6 Principles for Building a World Class TPM Team

WEBThe TPM team has a strong leadership position in engineering. TPM should be a centralized function reporting to the head of engineering. Although TPMs represent …

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How DoorDash is Scaling its Data Platform to Delight Customers …

WEBToday, many of the fastest growing, most successful companies are data-driven. While data often seems like the answer to many businesses’ problems, data’s …

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Scaling DoorDash’s Geospatial Innovation with a Location-Based …

WEBDoorDash’s Geo team built a delivery simulator to automate a formerly manual process of testing new location-based logic on our platform. This new tool, which …

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Using Active Probing to Detect Infrastructure Failures

WEBThe complexity of a microservice architecture requires fine-grained observability to spot impending service and infrastructure failures, and quickly mitigate …

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Optimizing OpenTelemetry’s Span Processor for High Throughput …

WEBOptimizing OpenTelemetry’s Span Processor for High Throughput and Low CPU Costs. Santosh Banda. When companies move to microservices, they need to …

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Speeding Up Redis with Compression

WEBOn average LZ4 had slightly higher compression ratio than Snappy i.e. while compressing our serialized payloads, on average LZ4 was 38.54% vs. 39.71% of …

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Addressing the Challenges of Sample Ratio Mismatch in A/B Testing

WEBOne of these challenges is sample ratio mismatch, or SRM. SRM represents one of the most egregious data quality issues in A/B tests because it fundamentally …

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Improving ETA Prediction Accuracy for Long-tail Events

WEBFigure 1: When the ETA time that customers see before making an order ends up being wrong, it hurts the customer experience and degrades trust in our …

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How DoorDash Defines Great Engineering Management

WEBEngineering Excellence encompasses three subcategories: Quality, Velocity, and Efficiency. Quality refers to the craft of engineering, delivering software …

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Failure Mitigation for Microservices: An Intro to Aperture

WEBCong Ma Matt Ranney. When dealing with failures in a microservice system, localized mitigation mechanisms like load shedding and circuit breakers have always …

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Tackling technical challenges to build a global logistics platform

WEBThere are a variety of novel challenges involved when a growing tech company wants to expand quickly and efficiently into new markets. This was very much …

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Switchback Tests and Randomized Experimentation Under …

WEBTo A/B or not to A/B, that is the question. Overview. On the Dispatch team at DoorDash, we use simulation, empirical observation, and experimentation to make …

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DoorDash's Lessons on Improving Performance on High-Traffic …

WEBConclusion. DoorDash’s web performance investigation generated many ideas and initiatives, most of which turned out to be dead ends. It’s challenging to apply …

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How DoorDash Manages Mobile Releases

WEBIn that spirit - and with a six-year background in the release processes for both the DoorDash and Caviar consumer apps - here is a high-level overview of …

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Improving Web Page Performance Server-Side Rendering with …

WEBResults. Migrating our pages to Next.js achieved +12% and +15% page load time improvements on Home and Store. LCP (one of Google’s core speed metrics) has …

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The 4 Principles to boost DoorDash's Experimentation by 1000%

WEBHow we scaled our experimentation 1000%. In order to scale our experiment capacity we focused on building an approach with the following four attributes: Operating …

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