Dash 2019
| title | author | length |
|---|---|---|
| Datadog DASH 2019 Keynote | Alexis Lê-Quôc, Aparna Sinha, Michael Gerstenhaber, Calvin French-Owen, Miranda Kapin, Brent Montague, Celene Chang, Vishesh Sharma, Renaud Boutet, Kartik Garg, Amit Agarwal, Priyanshi Gupta, Andrew Southard, Justin Wright, Gabriel-James Safar, Hugo Kaczmarek | 01h 41m |
Announcements show concrete capabilities and scale: Datadog ingests everything and lets teams keep what matters with Metrics Without Limits (ingest-first, pay… | ||
| Stress Testing in Production: The New York Times Engineering Survival Guide | Shesh Patel | 28m |
Describes a production stress test using JMeter + BlazeMeter against a production‑mirror environment that simulates newsroom writes and user reads; test… | ||
| Transforming Hulu’s Application Platform | David Lindquist | 38m |
Hulu runs Donki, a Heroku-style Docker-native platform that scales from hundreds of requests per second to handling “hundreds of billions of requests per day”… | ||
| Strengthening the Foundation: Airbnb's Platform Transformation | Victor Chen | 39m |
Airbnb builds a shared platform during its 2016 SOA migration that standardizes service construction and ops: an in-house Java library PowerGrid runs… | ||
| Operational Controls | Ross Wilson | 35m |
BBC runs over 4,000 services and deploys immutable AMIs with HashiCorp Packer, rolling updates and CloudWatch-driven automatic rollbacks. Production uses… | ||
| A Tale of Two System Crashes: Innovation and Accidental Chaos | Bonnie Rhee | 33m |
Flatiron Health builds an internal Flask job runner called Crane and adds AWS Auto Scaling to create AutoCrane, which turns a static 20‑worker EC2 fleet into a… | ||
| Building & Scaling Distributed Teams | Jason Hiltz-Laforge | 37m |
Experience grows three distributed teams into about two dozen people across 10 cities, three countries, six time zones and four offices, showing concrete… | ||
| Safer Deploys with Test-Driven Infrastructure | Jess Males | 31m |
Advocates writing monitoring checks before infrastructure and shipping them alongside service code so deployments carry their own health tests. Demonstrations… | ||
| When Bad Architectures Happen To Good People: Migrating Legacy Systems To Serverless | Forrest Brazeal | 31m |
Argues a practical migration path: create an on‑prem agent to stream legacy DB changes into AWS EventBridge/Kinesis/SNS, consume with Lambda and build read… | ||
| The Path to SRE | Damian Schenkelman | 30m |
Auth0 starts an SRE program mid‑2018 with a small 5–6 person core, focuses on consultancy and short‑term embedding with explicit “what we do / don’t do” rules… | ||
| The Anatomy of a Cascading Failure | Rareș Mușină | 31m |
Shows how a rollout bug triggered a RDS Postgres spike of unexpected writes, how AWS burst limits throttled the database, and how a cron job every 15 minutes… | ||
| Subverting the Monolith with Principles and Tooling | Sophia Russell | 35m |
Betterment builds a principled platform that migrates legacy monoliths to Kubernetes by enforcing explicit project contracts, generating config code, and… | ||
| Lead Lead and Not Lead Follow | Blake Scrivner | 27m |
Zendesk scales SRE from scratch across 700 engineers supporting 145,000 customers and shows concrete practices: team built an upload/installation tool to let… | ||
| Scaling AI Infrastructure | Eric Sigler | 28m |
OpenAI describes concrete scaling wins and failure modes: reinforcement agents for Dota run across custom Rapid clusters with rollout, optimizer and evaluation… | ||
| Migrating Data Quickly and Safely | Aaron Webber | 29m |
Nextdoor deploys 10–15 times per day and solves long blocking DDLs by keeping Django migrations but adding safety checks that query Postgres’… | ||
| Building Place Exchange: Handling Over Ten Thousand Digital Street-Side Screens | Taq Karim | 41m |
Place Exchange runs programmatic ads to over ten thousand street‑side screens using serverless on AWS: API Gateway frontends, hundreds of Lambda functions… | ||
| Building a Real Time Metrics Database | Joel Barciauskas | 35m |
Datadog processes trillions of metrics per day and is architecting for a quadrillion, combining Cassandra, Kafka, PostgreSQL with in‑house in‑memory stores to… | ||
| A Journey to Automated Infrastructure | Curtis Wellborn, Steve Mastrorocco | 23m |
eVestment migrates to AWS and automates everything in 6 months migration, replacing VMs with Docker on ECS, moving .NET Framework to .NET Core, and enforcing… | ||
| Serverless from Scratch | Reza Javidi | 37m |
Openfit runs a 100% serverless stack on AWS using Lambda, API Gateway (26 endpoints), Cognito, DynamoDB, S3 + CloudFront and Lambda@Edge, with monitoring in… | ||
| How Small Changes Can Make Huge Waves | Zach McCormick | 37m |
Braze runs at massive scale—11 billion user profiles, 8 billion Sidekiq jobs/day and 6 billion API calls/day—and uses feature flippers to roll changes from 1%… | ||
| Adventures in Running a Private Cloud | Rob Jefferson | 36m |
Comcast runs an OpenStack private cloud across 11 regions with about 37,000 VMs on roughly 2,500 hypervisors and builds tooling to manage capacity, quotas and… | ||
| Running Services at Google Scale | Aparna Sinha | 16m |
Google claims its stack lets services scale from zero to billions without rewrites, running 4 billion containers/week on Borg-inspired orchestration and GKE… | ||
| Metrics Without Limits | Michael Gerstenhaber | 14m |
Product announces a new model that ingests all metric streams but charges only for what you keep and query, with 10¢ per 100 metrics ingest pricing, 15 months… | ||
| Network Performance Monitoring | Miranda Kapin | 08m |
Datadog launches Network Performance Monitoring that collects network metrics without instrumentation and surfaces a thousand‑foot view in 30 seconds. It… | ||
| Correlations and Watchdog for Infrastructure | Celene Chang | 06m |
Datadog’s Watchdog automatically models weeks of service metrics, sets bounds of normal, and flags anomalies with no configuration, now extending from APM to… | ||
| Log Rehydration and Logs to Metrics | Renaud Boutet | 16m |
Datadog decouples ingest from indexing so teams ingest hundreds of terabytes a day while indexing a small sample (example uses 5%) and still archive everything… | ||
| End User Experience Monitoring | Gabriel-James Safar | 07m |
Datadog presents concrete features for measuring user-facing performance: study-backed goals like 15% more signups from 40% faster perceived load and the BBC’s… | ||
| Mobile Real User Monitoring | Hugo Kaczmarek | 02m |
Announces a lightweight mobile RUM SDK that auto-sends logs, metrics and traces and correlates them with server data in a single dashboard, supporting Java and… | ||
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