Modern day applications are data driven and data rich. The infrastructure your backends run on are a critical aspect of your environment, and require unique monitoring tools and techniques. In this webinar learn about what DataOps is, and how critical good data ops is to the integrity of your application. Intelligent APM for your data is critical to the success of modern applications. In this webinar you will learn: The power of APM tailored for Data Operations The importance of visibility into your data infrastructure How AIOps makes data ops actionable

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Learn More About Unravel
info@unraveldata.com

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July 16, 2019
George Demarest
Senior Director of Product Marketing
Understanding DataOps
and its Impact on
Application Quality

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Data Applications: The Perfect Storm of Human Error
Swiss Cheese Model of Human Error
Latent failures
Organizational
Challenges
Latent failures
Immature Supervision
Preconditions for
unsafe acts
Latent failures
Unsafe acts
Active failures
Incident!

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Data Applications: The Perfect Storm of Human Error
Swiss Cheese Model of Human Error in Data Applications
Latent failures
Organizational
Challenges
Latent failures
Immature Supervision
Preconditions for
unsafe acts
Latent failures
Unsafe acts
Active failures
OOM
Incident!
“We don’t need a CDO/CAO”
“Developers will allocate their own cluster resources”
“Big Data is experimental. Data team: govern thyself”
“I need max memory for all of my jobs”

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DataOps is a Thing

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DataOps is a Thing
https://www.dataopsmanifesto.org/

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Gartner Definition of DataOps
DataOps is a collaborative data management practice focused on
improving the communication, integration and automation of data flows
between data managers and consumers across an organization.
The goal of DataOps is to create predictable delivery and change
management of data, data models and related artifacts.
DataOps uses technology to automate data delivery with the appropriate
levels of security, quality and metadata to improve the use and value of
data in a dynamic environment.

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Are We Losing the Battle of Complexity?
Multiple layers of
complexity make data
applications difficult to
tune, troubleshoot,
operationalize, and scale.
Only intelligent automation
can win this fight.

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Managing distributed apps is hard and expensive
Hard to identify root cause Large “attack surface”

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Without AI, DataOps is a manual, logistical challenge
One complete correlated view
with intelligent automation.
Multiple tools, no complete
view, no intelligence.
DataOps Without AI AI-Powered DataOps

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Unravel is AI Powered Automation for DataOps
Without Unravel With Unravel
• One full-stack, cross platform console
• One complete correlated view
• Automatic, lightweight data/log collection
• Built-in AI/ML powered recommendations,
insights, remediation
• Chargeback/showback reporting
• Multiple tools
• Manual data/log collection
• Fragmented view, multiple consoles
• Minimal intelligence; manual tuning
and troubleshooting
• Manual cost analysis

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Where is the value for DataOps created?
Business Value Accelerate business decisions though timely data driven insights
Performance Guarantee modern data application SLAs
Throughput Optimize cluster performance and job completion times
Quality Minimize failed jobs
Efficiency Minimize big data cluster and resource contention
Productivity Autonomous remediation scales Ops teams

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Essential Elements of an AI-Powered DataOps
• Data Collection and Correlation
- Observe and collect all relevant data
- Correlate collected data and derived metadata
• Operational Data Model
- Monitoring, troubleshooting, tuning, and managing
requires an operational data model
- Richer, more powerful than a CMDB
• Analytics
- Basic and advanced statistical analysis – correlate,
classify, extrapolate from operational metadata
- Predictive analytics and forecasting for capacity and
growth
- Pattern and anomaly detection, root-cause analysis
- Prescriptive analytics and recommendations
- Context, topology and coded expertise
• Automation
- Auto-tuning of applications
- Autonomous resource allocation and optimization
- Cluster load balancing and job scheduling
- Automatic response to alerts and recovery from failures

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Our Solution – Extensible Data Operations Platform

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Automated DataOps Use Cases for Unravel
Automated Cloud Cost Management
• Optimize cost by right-sizing cloud images
• Optimize cost by choosing the optimal
price plan
Automated Workload Management
• Eliminate CPU, Memory, Network I/O and
Disk I/O contention
• Correctly size VM’s and Cloud Images
• Place VM’s in the best Hosts and Clusters
Automated Root Cause Analysis
• Intelligent analysis of application
failures
• Use Unravel data model and learned
app behaviors to automate RCA
Automated Performance Optimization
• Automatically learn the performance
characteristics apps and supporting stack
• Automatically optimize for a chosen KPI
(performance, efficiency)

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Example: Root Cause Analysis of App Failures
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Challenge
• Many levels of correlated stack traces
• Identifying the root cause is hard and time consuming

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Resolution
• Reduce troubleshooting time from days to seconds
• Improve productivity of data scientists and analysts
Automated Root Cause Analysis of Failures

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Error
Template
Extraction
Feature
vectors
Learning
Algorithm
for
Predictive
Model
Container
Logs
Predictive
Model
Root causes
Automated Root Cause Analysis of Failures

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Unravel insights and
recommendations for
spark application tuning

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Unravel is AI Powered Automation for DataOps
Without Unravel With Unravel
• One full-stack, cross platform console
• One complete correlated view
• Automatic, lightweight data/log collection
• Built-in AI/ML powered recommendations,
insights, remediation
• Chargeback/showback reporting
• Multiple tools
• Manual data/log collection
• Fragmented view, multiple consoles
• Minimal intelligence; manual tuning
and troubleshooting
• Manual cost analysis

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Unravel – What makes us different
FULL-STACK
COVERAGE
Only Unravel works across your
entire ecosystem to demystify and
simplify operations.
AI-DRIVEN
RECOMMENDATIONS
Unravel does more than monitor – it
shows you how to make things
better.
AUTOMATED TUNING AND
REMEDIATION
Unravel operationalizes big data by
automating it.
FULLY-EXTENSIBLE
FOR CLOUD ADOPTION
Only Unravel works future-proofs
your cloud adoption choices

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Learn More About Unravel
info@unraveldata.com