data science for effective network operations - cisco.com · data science for effective network ......

Cisco Knowledge Series

Sept 6th, 2017

Data Science for Effective Network Operations

© 2017 Cisco and/or its affiliates. All rights reserved. Cisco Confidential

Fully Aware• Get more insight into your network and data out of your network

Open Intelligence• Constantly learn, develop and deploy solutions faster and more efficiently

Predictive Control• Make things happen rather than waiting for things to happen

Cisco AutomationYour Competitiveness

Speakers / Panelists

Kiran InampudiSolutions Leader- Cisco, GSP Services

Shelly CadoraPrincipal Engineer- Cisco, GSP Engineering

Patrick LinVP Product & Partnerships, SignalFx

Agenda

Relevance of Data Science for Network Ops

Cloud Scale Networking / Model Driven Telemetry

Modern Monitoring Approaches / SignalFx

Demo & Customer Use case

Q&A

What is Data Science ?

Data science involves using automated methods to analyze massive amounts

of data and to extract knowledge from them.

Data science is a broad discipline that includes

• Statistics

• Computer science

• Applied mathematics

• Machine learning/AI

• Visualization

Data Science is a methodology, not a feature!

Data Science for SP Network Operations

Advanced Security

Optimization

Predictive Maintenance

Forecasting

Reduce Alerts

Cloud Scale Networking

NFV/SDN

Real-time

Telemetry Cloud

Raw

Data

Cleaned

Data

Standard

Reports

Data Exploration &

Metrics Reporting

Predictive

Analytics

Prescriptive

Analytics

Big Data & Advanced Analytics

Why did it happen

What w ill happen

What is the best

w ay to do this

Statistics & Data

Visualization

What happened

Sense & Respond Predict &

Act

Co

mp

etitive

Ad

va

nta

ge

Business Intelligence Advanced Analytics

Cognitive

Analytics

Machine tells humans

w hat to do!

Source : SAP

What skills are required to succeed?

SP Operations

Transformation

SP Domain

Expertise

Software

Automation

Data

Science

Expertise

Math & Software

Background

SP Ops Workflow

Algorithms & Models

Software Dev

Expertise

Open Source Tools

Identify use cases

Poll Question

Agenda





Q&A

Current State of Network Operations

Troubleshooting

complexity

Network

outages

Network

planningPain points

Caused by

Leading to

Increasingly

dynamic and diverse traffic

patterns

Manual

operations

Coarse visibility

into networks

Over-

provisioned networks

Poor customer

experienceOpEx increase

Network Operations Must Evolve to Cloud Scale

Cloud Scale

Network Operations

SW

Modularity &

Extensibility

Automation

Visibility &

Control

Day 1

CONFIGURE

Day 2

MANAGE

& OPTIMIZE

Day 0

INSTALL

Traditional Network

Operations

Inflexible

SW

Manual

Provisioning

Fragmented

Topology View and

Complex

Routing

DevOps

• Automated services

• Agile, Simple to scale

• Data Driven, Real-time

SNMP

storage & analysis

sensing &

measurement

Network data is bottlenecked

Where Data Is Created Where Data Is Useful

CLI

Syslog

SNMP Server

Syslog Collector

Scripts

Non real

time

Strong burden on back-end

Must normalize different encodings, transports, data

models, timestamps

The New Paradigm – Free the Data

sensing &

measurement

Where Data Is Created Where Data Is Useful

T

T

T

Real

time

As Much Data

As Fast

As Useful

As Easy

As Possible

Storage & analysis

Kafka

Different Ways to Store and Analyze

Logstash

ElasticSearch

Kibana

Panda

BYO

Black

Box

S

S

T

Custom Open Source

SignalFx

SaaS

Prometheus

Grafana

Poll Question

Agenda





Q&A

@signalfx | www.signalfx.com23

SUMMARY TREND SOLUTION CRITERIA TECH REQUIREMENTS

1. Scale-out open source software

and microservices architectures

Monitor service-wide aggregate metrics

vs. element-specific metrics

Streaming aggregation, composite

metrics

2. Dynamic or ephemeral

infrastructure, e.g. containers

and serverless

Instant discovery with real-time

monitoring

Streaming high-resolution metrics

with zero-lag discovery

3. Developer choice, decentralized

teams

Shared context across distributed

teams and instant visibility into any

changes in environment

Centralized, self-service, real-time

operational intelligence solution

4. High-velocity release cycles Predictive analytics and proactive

alerting to identify emerging trends

Real-time streaming analytics,

alerts, anomaly detection, outlier

detection

5. Troubleshooting across

distributed teams

Advanced real-time correlation and

dimensional analysis.

Interactive, high-cardinality queries

and alerts

CLOUD NATIVE MONITORING REQUIREMENTS


DISCOVER & COLLECTOpen-source based collection and instrumentation that’s future proof for microservice environments

No agent lock-in, ever

100+ supported integrations and counting

New instances visible in SignalFx with minimal lag


MASSIVELY SCALABLEREAL-TIME ARCHITECTURE Built from the the ground up for containers, functions and frequent releases

Architected for real-time monitoring of dynamic and ephemeral environments

Powerful streaming analytics engine enables predictive monitoring and preventative operations

Highly secure, SOC 2 Type II compliance

Highly available (99.9%), 24/7 oncallservice operations Sam Eaton

Director of Engineering Operations

“For the vast amount of metrics we produced, SignalFx was the only

solution that didn’t fall over. You guys clearly know what

you are doing.”

EXPLORE AND VISUALIZE

Built-in dashboards and Navigator to get started

Explore and gain insights from metrics data using interactive, streaming UI

Customize and annotate metrics dashboard to ensure shared understanding and interpretation

DETECT AND ALERT

Built-in detectors and alert conditions to get started

Configure or customize to detect exactly the pattern, trend or outlier you need to know

Confirm selected alert condition works as intended with preview

Notify via email, Slack, PagerDuty, etc.

CORRELATE AND TRIAGE Shared visibility into apps and infra (and how they

are related)

Use SignalFx's interactive analytics capabilities to further correlate and troubleshoot

Collaborate with team, share work-in-progress

Create new detectors and dashboards (or edit existing ones) as part of post-mortem

ENTERPRISE ADMIN

Centralize, simplify subscription management

Enforce change control over custom content

Organize dashboards and alerts by team

Solution Overview- Cisco Telemetry + Signal FX

SignalFxTM

Streaming & HistoricalAnalytics

Visibility

Timely Alerts

Analytics

Advanced

Troubleshooting

Real time streaming

Temperature Power

Fan Speed CPU

Process

UptimeMemory

Metrics

Platform Stability- Metrics

Route FlapNeighbor

Counts

Convergence

TimeRoute Memory

VRF State Errors

Metrics

Routing Stability- Metrics

Agenda





Q&A

Topology/Setup

Cisco Pipeline

NSO

SignalFX(SaaS)

VisibilityAnalytics

Timely Alerts

Real time / Intelligent Alerting

Real time detection of problem

Summary

Data Science is a Methodology, Not a feature!

SDN/NFV & Data Science is a powerful new approach for making networks more reliable and secure

Data science capabilities should synergize, empower network Operations teams

Recommended Approach- Crawl, Walk & Run

data science for effective network operations - cisco.com · data science for effective network ......

Documents