In this fireside chat, Balaji and Brian discuss the evolution of the monitoring and observability industry, the role that InfluxDB plays and a look at how one customer is using InfluxDB in their solution.

2. Use Case: Monitoring /
Observability
Balaji Palani - Sr. Director of Product Management,
InfluxData
Brian Gilmore - Director of IoT and Emerging
Technologies, InfluxData

3. Connect Learn Build
Hear from and meet developers
from the InfluxDB Community
Be inspired by use cases from
our partners and InfluxDB engineers
Learn best practices that will
help you build great experiences
for your projects

4. In this fireside chat, Balaji and Brian discuss the
evolution of the monitoring and observability industry,
the role that InfluxDB plays and a look at how one
customer is using InfluxDB in their solution.
Balaji Palani
Sr. Director of Product
Management, InfluxData
Balaji Palani is the Senior
Director of Product
Management focused on
InfluxDB Cloud. He is
passionate about building
powerful cloud products
that help Developers
achieve the fastest time to
awesome.
Use Case: Monitoring /
Observability
Brian Gilmore
Director of IoT and Emerging
Technologies, InfluxData
Brian Gilmore is Director
of IoT and Emerging
Technology at InfluxData.
He has worked with
organizations to drive the
unification of industrial
and enterprise IoT with
machine learning, cloud,
and other technologies

5. Agenda
1. Evolution of monitoring
2. How customers are using InfluxDB for monitoring
3. Customer implementations

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

7. Metrics, Events, and Traces
Usually derived through sampling, usually numeric, and
typically regular in period.
Usually emitted, on-event or on-exception. Can be either
numeric or strings. Irregular period by nature.
Bundled and uniquely labeled collections of related
metrics and events related to a specific transaction or
interaction. Irregular period and explicit duration.
Metrics
Events
Traces

8. How They Relate
Metrics (one/sec):
Events (varied):
Traces (bundled):
12s
3s
8.26s
Condition 1
Condition 2
Condition 3
Condition 4
Trace ID: 86ef2836-58fe-4a2e-ba69-3de4596072fd
duration 37 seconds
6s

9. InfluxData Reference Architecture
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
14+ Languages
…
Native Ecosystems
JMeter
NiFi
AWS Kinesis
Azure Event Hubs
GCP PubSub
Java
.NET/C#
PHP
Ruby
Vector
Fluentd
Scrapers
Native Collectors

10. Reference Architecture Detail
DevOps Monitoring with InfluxData
Data Sources Integrations
Applications/Services
• Web Application Infrastructure
• Containers
• Message Brokers
• Databases
• K8S
• Custom microservices
• Network Instrumentation
• Customer facing web applications
• Customer facing mobile apps
Devices/Infrastructure
• Mobile Apps
• Web Apps
• APIs
• Message Queues
• Ecosystem Devices
(Connectivity, coordination
ie Alexa)
Telegraf
• AMQP
• Active MQ
• Amazon Cloudwatch
• Amazon Kinesis
• Kafka
• Docker
• Azure Event Hub
• ExecD
• GCP Pub/Sub
• HTTP
• Jenkins
• Kernel
• Kubernetes
• MQTT Consumer
• NATS Consumer
• NGINX
• OpenTelemetry
• Redis
Client Libraries
• Java
• .NET/C#
14+ Languages
300+ Plugins
• Product quality
• Process optimization
• Code integration
• Testing and load balancing
• Deployment optimization
• Error handling
• Monitoring Analytics
• Alerting Frameworks
• Go
• JavaScript
Applications & Use Cases
InfluxDB
Purpose-Built Time Series Database
Visualization, Query & Task Engine
Collect
Transform
Downsample
Trigger Workflows
Alert

12. SLO PLATFORM
Translate Observability Data into Clear Action
Roadmap Decisions
Justifying Tech Investments
& Cloud Spend
On Call Alerts &
Interruptions
OBSERVABILITY
DATA SOURCES
Normalized Service Level
Objectives (SLOs) across
multiple data sources:
● Quantified Customer
Expectations
● Tech Debt & Service
Delivery Risks
● Define Clear Trade-offs in
Service Management

13. Deployment
Optimization
Reference Architecture
DevOps Monitoring with InfluxData
Error
Handling
Sources
CI/CD Pipelines
Cloud Services
Containers
Kubernetes (K8S)
Mobile apps
Web apps
Networking
System Stats (CPU,
Memory)
Microservices
InfluxDB
Purpose-Built Time Series Database
Visualization, Query & Task Engine
Telegraf
Client Libraries
• HTTP
• Syslog
• Kubernetes
• Apache Kafka
• AWS Kinesis
• Azure Event Hubs
• GCP PubSub
300+ Plugins
• Java
• Go
• .NET/C#
• JavaScript
• Node.js
• Python
• Arduino
• PHP
• Ruby
12+ Languages
Data Types
APIs
Application
performance
Metrics
Infrastructure
metrics
Business
transaction metrics
Service adoption
metrics
Collect
Transform
Downsample
Trigger Workflows
Alert
• Product quality
• Process optimization
• Code integration
• Testing and load
balancing
• Deployment
optimization
• Error handling
• Monitoring Analytics
• Alerting Frameworks
Applications &
Use Cases

15. Nobl9 Architecture - Black Box View
Error
Budgets
Web App
API
InfluxDB
PM & Business
Stakeholders
YAML
GUI
A
l
e
r
t
P
r
i
o
r
i
t
i
z
e
Raw SLIs
SLO Config
Ops/SREs &
Application Leads
Govern
Align
New Relic Prometheus
Datadog
Calculations
Customer Platforms and Services
App
CI/CD Web Services
Data
GitOps
SLO Based
Events &
Alerts
Graphs
Reports
Review &
Align
Review &
Align

16. Calculation of SLO time series
Nobl9 Calculation Architecture
● Rearchitected into custom code and Kafka
○ FIFO calculation approach
○ Maintains state, uses object storage as a
backing store
○ Scales horizontally
Processing of telemetry data (SLIs) and math

17. API Tier
Catalog
Ingestor
Kafka
Ingestor
Ingester
Querier
Querier
Querier (SQL)
Compacter
Compacter
Compacter
Object Store
InfluxQL
Flux
Queries
Writes
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18. T H A N K Y O U