Datadog - IT Press Tour February 2018

Transcript

1. Cloud-Scale Monitoring Monitoring that scales alongside your digital transformation
2. Real-time performance visualization What is Datadog A monitoring service for large – scale applications running on dynamic infrastructure Robust alerting Public Dashboarding and Collaboration Root Cause Correlation Historical Analysis Impossible d'afficher l'image. Votre ordinateur manque peut-être de mémoire pour ouvrir l'image ou l'image est endommagée. Redémarrez l'ordinateur, puis ouvrez à nouveau le fichier. Si le x rouge est toujours affiché, vous devrez peut-être supprimer l'image avant de la réinsérer.
3. Quick Facts •  Founded in 2010 by Olivier Pomel and Alexis Le-Quoc •  Headquartered in NYC with offices in Boston and Paris •  Over 500 employees •  Over 6,000 enterprise customers •  $147.9 Million in venture capital funding to date •  100% growth in ARR from 6/1/2016 – 5/31/2017
4. The new requirements of monitoring in the cloud age
5. Infrastructure Architecture Development Stack Participants Monitoring Centralized Monolithic Waterfall Standardized, using stable, on-premise vendor software Infra (Governance) Dev (Participants)) NEXT GEN Distributed Microservice Agile Diverse, using quickly-evolving OSS and SaaS components Multiple Infra and Dev teams LEGACY
6. Infrastructure-wide visibility Your Servers, Your Clouds, Yours Metrics, Your Apps, Your team. Together in one place. Compare and correlate metrics from multiple IT components Create custom KPIs and composite metrics Track events from the systems in your environment A B
7. Everything in One Place 200+ Vendor-Supported Turn Key Integrations
8. Love and trusted by thousands of enterprises
9. Scaling a unified monitoring platform through an AWS transition. Existing challenges •  AOL's systems were constantly failing due to increased load •  Ops and dev teams were missing key data contained in other team’s tools •  A patchwork of open source and custom-built monitoring tools made team collaboration challenging Compelling events •  AOL was transitioning to AWS company-wide •  The platform shift would also change processes and team structure •  Existing monitoring tools could not scale with the new dynamic platform and/or connect with data from AWS and other new support systems Solution •  Datadog provides unified infrastructure monitoring for AOL teams and their cloud environments, with data access for all teams that need it •  Product owners and corporate management receive high-level reporting and business metric visibility for all products monitored by Datadog Business impacts •  Engineers can correlate the monitoring data from upstream and downstream components to holistically troubleshoot issues in AOL's products •  The recurring time spent by AOL engineers from 45 different teams developing monitoring tools, are now applied to core AOL products
10. Full Stack Observability
11. Metrics Monitoring & Alerting -  Summarization of lots of data into Dashboards -  Long range storage & analysis -  Performance & efficient alert triggers
12. APM Application Performance Profiling & Tracing -  Measuring lots of performance points at the source code level -  Tracing transactions into source code and across remote services (Service map representation) -  Architecture runtime monitoring
13. Out-of-the-box Application Health and Performance
14. Distributed Tracing across Monoliths and Microservices
15. Metrics Monitoring & Alerting APM Profiling & Tracing Logs Troubleshooting, Debugging, Support & Auditing Troubleshoot Understand Identify trends Long range metrics New alerts See Func. calls See Service calls See operation details See error details Analyze Txns Analyze Services interactions Perf. Statistics New alerts Tech. & Services Integrations working hand-in-hand brings: -  Easy set-ups -  Same infrastructure tags -  Better default dashboards Well controlled data acquisition that unlocks all the potential (eg. deep linking, machine learning, etc.)
16. Logs Explorer Search bar: -Contains all filters -In sync with URL -Auto-complete Facets: -Filtering -Analytics Time range Filter "pills" Columns: -Log attributes -Infra. tags
18. Questions?