2. Network Monitoring
with InfluxDB
Charles Mahler –
Technical Writer, InfluxData

3. This session looks at the Network Monitoring use case
and how InfluxDB enables these types of solutions.
Charles Mahler
Technical Writer, InfluxData
Charles Mahler is a Technical Writer at InfluxData where
he creates content to help educate users on the
InfluxData and time series data ecosystem. Charles’
background includes working in digital marketing and
full-stack software development.
Network Monitoring with InfluxDB

4. Agenda
1. Challenges of Network Monitoring
2. How InfluxDB helps solve those challenges
3. InfluxDB Network Monitoring use cases

5. Use Case Categories
5
IoT Monitoring Developer Tools Real-time Analytics
Industrial
Enterprise
Consumer
DevOps
Networks
Security
Cloud
Applications
APIs
Gaming
Renewable
Energy
FinTech
Crypto

6. Challenges of Network Monitoring
Collecting Data
• Legacy hardware
• Proprietary protocols
• Most important part
Storing Data
• Cost
• Complexity
Analyzing Data
• Query data efficiently
• Allow non-experts to
generate value from data
• Take action on data

7. How the InfluxDB Ecosystem can
help solve these challenges

8. Data Sources
Application
Workflows
Infrastructure
Insights
Telegraf
Client Libraries
HTTP
Syslog
Kubernetes
Apache Kafka
Python
Arduino
Node.js
JavaScript
Go
Data Systems
Mobile apps
Web apps
Cloud Services
Devices
Sensors
Databases
Networks
Message Queues
APIs
IoT Platforms
CRMs
InfluxDB Platform
IoT
Actions
InfluxDB
Purpose-Built Time Series Database
Visualization, Query & Task Engine
Collect
Downsample
Trigger
Alert
Transform
…
300+ Plugins
12 Languages
…
Native Ecosystems
JMeter
NiFi
AWS Kinesis
Azure Event Hubs
GCP PubSub
Java
.NET/C#
PHP
Ruby
Vector
Fluentd
Scrapers
Native Collectors

9. Telegraf
• Easy to deploy
• 300+ plugins
Ecosystem Integrations
• FluentD
• Apache NiFi
• Vector
• Line Protocol support
Client Libraries
• 12+ Languages
• Best practices out of the
box
Data Collection

10. Telegraf Deployment patterns
● Per device sidecar pattern
● single Telegraf instance for multiple devices

11. Telegraf processors for Network Monitoring
● Normalizing data
● Enriching data
● Filtering and rate limiting

12. Data Storage
Storage Costs
• Compression
• Data Management features
Management Complexity
• Scaling
• Integrating with other tools
• Deployment flexibility

13. Edge data architecture
Edge
Data
Replication
Local UI
and Alerts
Gateway
Device Metrics
Aggregated UI
and Alerts
InfluxDB
Bucket
InfluxDB
Bucket
InfluxDB
Bucket
InfluxDB
Bucket
InfluxDB
Bucket
InfluxDB
Bucket
Edges
External
Databases
Cloud Data
Sources

14. • Query performance
• Allowing non-experts to gain value from data
• Acting on data
Analyzing Data

15. Network Monitoring Use cases
Security Monitoring
• Behavior modeling
• Intrusion detection
Performance Monitoring
• Faster incident resolution
• Reduce toil
• Improve resource efficiency
Forecasting
• Hardware capacity estimates
• Predictive maintenance

16. InfluxDB Security Use Cases

17. InfluxDB Performance Monitoring Use Cases
● Cisco
○ Use InfluxDB for E-commerce platform performance monitoring and
Cisco Live network monitoring
○ 2300 wireless access points
○ 650 switches
○ 76TB of network data over 5 days
● Red Hat
○ Use InfluxDB for internal network monitoring
○ 60+ locations
○ 1600 network devices
○ 14000 network interfaces

18. InfluxDB Forecasting Use Cases
• Hardware capacity planning
• Renewable energy and power grid optimization
• Predictive maintenance

19. T H A N K Y O U