Naarad is an open-source performance analysis tool (https://github.com/linkedin/naarad) written in python and developed by the Performance team. Naarad analyzes various metrics (gc, sar, Jmeter etc), evaluates SLAs and generates a user friendly report to aid in performance analysis and investigations. In this talk, we will give an overview of Naarad, its usage, examples use-cases, its architecture and our future plans.

1. Naarad
A Performance Analysis Tool
Ritesh Maheshwari, Sharad Gandhi
Performance Team @ LinkedIn
github.com/linkedin/naarad

2. Agenda
1. Motivation
2. What is Naarad?
3. Architecture
4. Usage
5. Demo
6. Extending Naarad
7. Next Play
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3. 2

4. Environment
Setup
Monitoring
Test Kickoff
Metrics
Collection
Parse
Grade
Report
Analysis
Performance
Analysis
3

5. Environment
Setup
Monitoring
Test Kickoff
Metrics
Collection
Parse
Grade
Report
Analysis
4
NAARAD

6. What is Naarad?
• Naarad is a performance analysis tool
– Analyze various metrics
– Evaluate rules / SLAs
– Visualize Data (plot timeseries, CDF)
– Compare (diff)
– CLI / Python API
• Open Sourced
– http://github.com/linkedin/naarad
5

7. Fetch &
Parse
Run Command
Run Command
Diff
Report
NAARAD
6
Analysis
Visualization
config
GC Logs
System
Metrics
inGraphs
…
Workload Logs
Report
Pass
or
Fail

8. Fetch &
Parse
Run Command
Run Command
Diff
Report
NAARAD
7
Analysis
Visualization
config
Report
2
Report
1
Pass
or
Fail

9. Extensible Architecture
metric charting reporting
• Delimited files
• GC logs
• sar
• /proc metrics
• RUM logs
• Jmeter logs
• netstat
• cluster
• png (matplotlib)
• svg (pygal)
• js (dygraphs)
NAARAD
• Jinja2 templates
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10. Supports Proprietary Extensions
metric charting reporting
NAARAD
inGraphs HighCharts Custom templates
Proprietary
Open Source
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11. Usage
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NAARAD
Python API
API Clients
Continuous
Integration
CLI

12. Extensible Architecture
metric charting reporting
• Delimited files
• GC logs
• sar
• /proc metrics
• RUM logs
• Jmeter logs
• netstat
• cluster
• png (matplotlib)
• svg (pygal)
• js (dygraphs)
NAARAD
• analysis report
• diff report
• Jinja2 templates
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13. Adding New Metrics
metric
collect()
parse()
calc()
calculate_stats()
check_sla()
graph_data()
custom metric
parse()
Fetch Logs
Parse Logs
Derived metrics
Calculate Statistics
Validate SLAs
Plot timeseries, cdf charts
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14. $ sar –n DEV 1 3
SAR-dev.eth0.rxpck-per-s.csv SAR-dev.eth0.rxkB-per-s.csv
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15. Next Play
• Root Cause Analysis
– Anomaly Detection
– Metric Correlation
– Potential Culprits Stack Ranked
• Pip install
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