iguazio © 2016
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https://nuclio.io

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2 Years to Production
Moving Target, Skill Gaps
High CapEx & OpEx
Not Enterprise Grade
Businesses Rely on Modern Services
But DIY is Complex and Failing
2

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High-Level Abstractions and Serverless Solve the Complexity
Enabling faster business transformation

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iguazio Data Platform: Simple, Fast, and Secure
SERVERLESS FUNCTIONS MICRO-SERVICESSTATELESS DATA APIs
NoSQL API Stream API Object API File API
Security Queries & Functions Unified Data Data Lifecycle
High-performance unified data fabric
S3
Kinesis
DynamoDB
SQL (Presto)
Managed data services and
serverless like in the cloud, just:
• Unified
• Up to 100x Faster
• Deployed ANYWHERE
• 1/3rd the COST
Unified Data Platform
Productivity with Performance

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What is Serverless?
“No need to spend time and resources on server provisioning, maintenance,
updates, scaling, and capacity planning. Instead, all of these tasks and capabilities
are handled by a serverless platform and are completely abstracted away from the
developers and IT/operations teams” - CNCF Serverless Paper
Event
Sources
Function
Instance
invoker
Function
Instance
invoker
Function
Instance
invoker
Event
Sources
Event
Sources
Synchronous or
Asynchronous Invocation
FaaS Controller
Platform Services (Identity, Data, etc.)

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Serverless Application Examples
APIS, UI,
DASHBOARDS
DATA / EVENT
SOURCES
DATA
SERVICES
DATA
SERVICES
DATA
SOURCE
DESTINATION
IOT DEVICE /
GATEWAY
CENTRAL /
EDGE CLOUD
Real-time Analytics & AI Data Transformation & Movement
IoTAPIs, UI, Bots
APP
SERVICES
APP
SERVICES
SENSORS

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Serverless Pros and Cons
• Serverless:
Easy to deploy functions, no scripts, Dockerfiles, build, etc.
Auto-scaling and event triggers are built-in
Use any language
• What’s missing in current implementations?
Slow performance, lack of concurrency, no stream partitioning
Limited number of event sources (mostly HTTP, some Kafka)
Hard to debug and diagnose
Hard to manage complex functions and dependencies

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nuclio: A New Real-Time Serverless Platform
Comprehensive, Open, Super Fast and Runs ANYWHERE
Variety of event
sources, single API
8
400K Events/sec per Process
Maximum
performance
Dev, test, and run
ANYWHERE
Simple, fast and
secure data integration
https://github.com/nuclio/nuclio
http://nuclio.io
Platform
Controller
Local or shared
image repository
Event
Listeners
Real-Time, Auto-scaling Function OS
Language Runtime
Function
Workers
Data
Bindings
Pluggable
Data Services
Pluggable
Event Sources
Platform API: config, log, monitor, security
HTTP, AMQP, MQTT, Kafka,
Kinesis, NATS, Files/DB
CLI
& UI

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nuclio Perf Results: Single Process, Basic Echo Functions
Lang Threads HTTP Req/sec Avg Latency
1 40,281 24 us
100 372,496 2.03 ms
1 30,156 38us
100 66,681 3.41 ms
Setup: a single AWS C5.9Xlarge instance
Other Serverless/FaaS platforms processed only
1-5K events/sec at magnitudes higher latency !
Up to 100X Faster
Py
Go

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Data Bindings
$ nuctl deploy <name> <source> [options]
Enabling Simple and Continuous Dev and Ops (CI/CD)
One click to test, deploy, upgrade or rollback code
Runs ANYWHERE, Self-healing and auto-Scaling
LOCAL or CLOUD

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nuclio Playground – Online Dev, Config, and Test Environment
Edit, Deploy, Run, Test
Configure

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nuclio
Function Spec
Support Kubernetes CRD:
Functions can be created and
deleted using kubectl
tags/labels used for search and
event sources (Label Selectors)
Control Min/Max Replicas
for controlled auto-scale
Pass text or secret
environment variables
(k8s convention)
Flex resource allocation,
GPUs are coming
Pluggable Data
Sources
Various src code options*: inline code, path
(local/http/git), or local/remote pre-built image
namespaced
For the full spec see: https://github.com/nuclio/nuclio/blob/master/docs/configuring-a-function.md

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Function Example – Sentiment Analysis
Dependencies
(in YAML, UI or Code comments)
Call API
(Trigger independent)
Structured
Logging
Structured or Unstructured Response

DEMO
Type the following command and browse to <host-ip>:8070
docker run -p 8070:8070 -v /var/run/docker.sock:/var/run/docker.sock
-v /tmp:/tmp nuclio/playground:0.2.1-amd64

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Serverless Invocation Modes
Function
Instance
invoker
Message
Function
Instance
invoker
Function
Instance
invoker
Exchange
Message Queue
(e.g. RabbitMQ)
HTTP
API GW
Function
Instance
invoker
Function
Instance
invoker
Function
Instance
invoker
Req
Function
Instance
invoker
Function
Instance
invoker
Function
Instance
invokerPartition 1
Messages
Synchronous Req/Rep
Message Stream
Async Message Queue
Kafka,
Kinesis, etc.
Function
Instance
invoker
Function
Instance
invoker
Function
Instance
invoker
Job
Job (Master/Worker)
Priority
Queue
Master
(dealer)
Dealer
Partition 2
Partition 3
Partition 4

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Serverless is Enabling Intelligent and Continuous Applications
ACTIONS, INTERACTIVE
UI & DASHBOARDS
EXTERNAL
SOURCES
OPERATIONAL
DATA
CONTAINERIZED AI & ANALYTICS TOOLS
EXTERNAL DATA
SOURCES / LAKES
DATA SERVICES
Productivity | Faster Insights | Invisible Infrastructure | Lower TCO
SyncIngest / Alert
APIs &
Triggers
Analyze

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Real-time Maps
& Dashboards
Extract Metadata:
Geo location, time,
device, thumbnail
Deep Learning:
Detect people,
gender, age, etc.
Queries:
Find people in
places, relations
Missing person
notification
Trigger
Update
SMS
Query/Scan
Trigger
Update
Trigger
• Pictures + Metadata
• People DB, Locations
and relations
Ingest
DATA SERVICES
Real-Time Surveillance Example

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Streaming vehicle
data via web APIs
Real-Time Analytics for Alerts and Proactive Maintenance
Real-time enrichment with
weather & road data
Finds correlations
between weather
conditions and vehicle
components
Weather
Microservice for
data ingestion
Customer use case #1
Road info
Real-time alerts
Real-time
Dashboard
DATA SERVICES

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Real-Time Fleet Management Dashboard
Real-time
enriched data
Fuel consumption
and weather
correlation
Vehicle location
heatmap
Filter by bad
weather alerts
Customer use case #1

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Real Example: Event-Driven Analytics for Connected Cars
Geo Data
Weather/Road info
Vehicles Data
State
Changed?
Identify
Violation?
Drivers
Violations
Stream
State
Changes
Geo
Aggregate
Map
Process
Alerts
Process
Violations
External Sources
Import
service
Enriched
Events
Parallel
Enrichment
ML Processing
Complex Events + Data processed in real-time without the infrastructure hassle
real-time, auto-Scaling
serverless functions
Model Update
Stats
Update
* See code in the
UI/Playground slide

Thank You
nuclio is easy: try it and give it a
https://github.com/nuclio
Sign up for our online hackathon and build the greatest serverless
application on nuclio. You just might win a Phantom 4 drone…

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CLI (Run Command Example)
$ nuctl run --help
Build, deploy and run a function
Usage:
nuctl deploy function-name [flags]
Flags:
--base-image string Name of base image. If empty, per-runtime default is used
--build-command String Commands to run on build of processor image
--data-bindings string JSON encoded data bindings for the function (default "{}")
--desc string Function description
-d, --disabled Start function disabled (don't run yet)
-e, --env string Environment variables (name1=val1,name2=val2..)
-f, --file string Function configuration file
--handler string Name of handler
-h, --help help for deploy
-i, --image string Docker image name, will use function name if not specified
-l, --labels string Additional function labels (lbl1=val1,lbl2=val2..)
--max-replicas int Maximum number of function replicas
--min-replicas int Minimum number of function replicas
--no-pull Don't pull base images - use local versions
--nuclio-src-dir string Local directory with nuclio sources (avoid cloning)
--nuclio-src-url string nuclio sources url for git clone (default "https://github.com/nuclio/nuclio.git")
-o, --output string Build output type - docker|binary (default "docker")
-p, --path string Function source code path
--port int Public HTTP port (node port)
--publish Publish the function
-r, --registry string URL of container registry (env: NUCTL_REGISTRY)
--replicas int If set, number of replicas is static (default 1)
--run-image string If specified, this is the image that the deploy will use, rather than try to build one
--run-registry string The registry URL to pull the image from, if differs from -r (env: NUCTL_RUN_REGISTRY)
--runtime string Runtime (e.g. golang, golang:1.8, python:2.7)
--triggers string JSON encoded triggers for the function (default "{}")
--version string Docker image version (default "latest")
Global Flags:
-k, --kubeconfig string Path to Kubernetes config (admin.conf)
-n, --namespace string Kubernetes namespace (default "default")
--platform string One of kube/local/auto (default "auto")
-v, --verbose verbose output
See more in: https://github.com/nuclio/nuclio/blob/master/docs/nuctl/nuctl.md