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Streamline and Scale Out Data Pipelines with Kubernetes, Telegraf, and InfluxDB

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RudderStack — the creators of the leading open source Customer Data Platform (CDP) — needed a scalable way to collect and store metrics related to customer events and processing times (down to the nanosecond). They provide their clients with data pipelines that simplify data collection from applications, websites, and SaaS platforms. RudderStack's solution enables clients to stream customer data in real time — they quickly deploy flexible data pipelines that send the data to the customer's entire stack without engineering headaches. Customers are able to stream data from any tool using their 16+ SDK's, and they are able to transform the data in-transit using JavaScript or Python. How does RudderStack use a time series platform to provide their customers with real-time analytics? Join this webinar as Ryan McCrary dives into: RudderStack's approach to streamlining data pipelines with their 180+ out-of-the-box integrations Their data architecture including Kapacitor for alerting and Grafana for customized dashboards Why using InfluxDB was crucial for them for fast data collection and providing single-sources of truths for their customers

Streamline and Scale Out Data Pipelines with Kubernetes, Telegraf, and InfluxDB

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Streamline and Scale Out Data
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What is RudderStack?
RudderStack architecture diagram
TRANSFORMATIONS
IDENTITY RESOLUTION
DATA GOVERNANCE
Rudderstack
Key Differences
4
WAREHOUSE FIRST
DEVELOPER FOCUSED
NO PERSISTENT DATA /
FUTURE-PROOF YOUR DATA STACK
4
Rudderstack
Key Differences
5
WAREHOUSE FIRST
DEVELOPER FOCUSED
NO PERSISTENT DATA /
FUTURE-PROOF YOUR DATA STACK
5
How do we use InfluxDB?
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Streamline and Scale Out Data Pipelines with Kubernetes, Telegraf, and InfluxDB

  • 1. Streamline and Scale Out Data Pipelines with Kubernetes, Telegraf, and InfluxDB
  • 4. Rudderstack Key Differences 4 WAREHOUSE FIRST DEVELOPER FOCUSED NO PERSISTENT DATA / FUTURE-PROOF YOUR DATA STACK 4
  • 5. Rudderstack Key Differences 5 WAREHOUSE FIRST DEVELOPER FOCUSED NO PERSISTENT DATA / FUTURE-PROOF YOUR DATA STACK 5
  • 6. How do we use InfluxDB?
  • 7. To change or remove footer go to View Tab > Master Kubernetes Deployment 7
  • 8. To change or remove footer go to View Tab > Master Kubernetes Deployment 8
  • 9. To change or remove footer go to View Tab > Master What do we need? ● Fast ● Reliable ● Gets out of the way Not our actual business (but very important to it) 9
  • 10. To change or remove footer go to View Tab > Master Why InfluxDB? We constantly evaluate the best tools for our customers In some deployments we run prometheus in parallel for comparison We knew we needed a fast, efficient time series database We have been using InfluxDB since we started storing metrics 10
  • 11. To change or remove footer go to View Tab > Master How do we use it? 11
  • 12. To change or remove footer go to View Tab > Master How do we use it? 12
  • 13. To change or remove footer go to View Tab > Master How do we use it? 13
  • 14. To change or remove footer go to View Tab > Master Metrics metrics everywhere 14
  • 15. To change or remove footer go to View Tab > Master Metrics metrics everywhere ● 100s of metrics ● High level ● Low level ● Counters, Timing, Guages ● Adding new metrics is fast and easy ● Primary monitoring/alerting 15
  • 16. To change or remove footer go to View Tab > Master What’s next? ● Determining long term storage of metrics ○ Sample? ○ Compress? ● Migration of metrics as deployment model changes ● Any change must be supported forever (open source) ● InfluxDB is limited to 200 tags ● Always evaluating more efficient options 16