Hortonworks Hybrid Cloud - Putting you back in control of your data

1 © Hortonworks Inc. 2011–2018. All rights reserved
Putting You Back in Control of
Your Global Data Strategy
Scott Clinton
Vice President Product and Portfolio Marketing

Hortonworks, Capturing the Value of Cloud and Data Today
Get all data under management
Combat growing cloud data silos
Consistently secured and governed
Reduce operational costs (OPEX) and risk
Unique, proven data and hybrid cloud expertise
Successfully navigate the cloud data journey
Hybrid cloud data and workload agility
Reducing time to value and proliferation of shadow IT
30% of Hortonworks customers use cloud, across 4 major providers

Public Cloud Isn’t for All Workloads and Use Cases
IT Public Cloud Data Challenges
80% of surveyed IT decision-makers
have repatriated either
applications or data from public
cloud environments to private cloud
solutions in the last year.
Source: IDC’s 2018 Cloud and AI Adoption Survey

Navigating Cloud Service
Costs and Lock-in Can Be Difficult
CPU and RAM
$0.00001667 per
GB-second used
API requests
$3.50 per 1M
executions
Storage
$0.02-0.1
per GB
Network
$0.05-0.09 per
GB-out
Requests
$.02 per 1M
executions
Hidden costsVisible costs
DATA EGRESS
30TB
$3000-$6000+

Batch processing42%
Cost and performance optimizations – No hidden costs – All without cloud vendor lock-in
Real World Results with Hortonworks Cloud Optimized Platforms
Batch analytics50%
VS.
AWS EMR
+
AWS infrastructure
HDP
+
AWS infrastructure
HDP
+
AWS infrastructure
VS.
AWS EMR
+
AWS infrastructure
$
$
* Based on actual customer results

Hybrid by Design
MULTIPLE CLUSTERS AND SOURCES
MULTIHYBRID
Hortonworks
DataPlane
Service
MANAGE, SECURE,
GOVERN
DATA AT REST
Hortonworks
Data
Platform
DATA IN MOTION
Hortonworks
Data Flow
• Cloud native for Hadoop in the public
cloud with HDP & HDF
• Extend to the edge with HDF
• Common metadata, security and
governance across all deployments
• All platforms simultaneously support
a variety of workloads
• Reduce staff training requirements
across multiple clouds

Immediate Results: Real-time Analysis of IoT Data in the Cloud
Mitsubishi Fuso, a leading truck, bus, and industrial
engine manufacturer
Gather and analyze diagnostic data to provide an
accurate diagnosis of the vehicle’s real-time status
Professional Services expertise provided smooth
implementation and operation HDP on Microsoft Azure
Increased vehicle availability
Reduction in information management costs
Hortonworks is the largest contributor in the Hadoop community.with Hortonworks’ expertise, we can
see immediate results in our monthly improvements. HDP is most compatible with cloud.
“ ”⏤ Erik Spitzer, Manager, IT Process Design and Innovation, Mitsubishi Fuso

Cluster 2
(Unstructured)
Cluster 1
(Structured)
Cluster 2
(Unstructured)
Cluster 1
(Structured)
Cluster 3
(Structured)
Data Center Dublin
Cluster 2
(Unstructured)
Cluster 1
(Structured) Cluster 3 (Structured)
Cluster 4
(Unstructured)
Data Center Las Vegas
Cluster 2
(Unstructured)
Cluster 1
(Structured)
Cluster 3 (Structured)
Data Center Bangkok
Cluster 1
(Unstructured)
Cluster 2
(Structured)
Common Shared
Services
Application
Portability
Connectivity
All Data Under Management
Uniform data fabric
Multi-cloud data silos
Edge to enterprise
Single point of access
Derive insight from
wherever the data
may live

SCHEMA
WHAT
Hive schema
(tables, views, etc.).
WHY
If you have 2+ workloads
accessing the same schema,
need to share this across
workloads.
HOW
Share Hive Metastore for
schema definition.
POLICY & AUDIT
WHAT
Defines security policies
around Hive schema.
Audit user access.
WHY
If you have 2+ users
accessing the same data,
need policies to be
consistently available and
applied.
HOW
Share Apache Ranger across
workloads and store policies
externally.
CATALOG & LINEAGE
WHAT
Track data provenance,
lineage, and chain of custody
end-to-end.
WHY
Guarantee the integrity and
reliability of your data.
Capture data access activity.
HOW
Share Apache Atlas across
workloads, leverage cloud
storage for lineage & audit
data.
GATEWAY
WHAT
Provide single endpoint that
can be protected with SSL
and enabled for
authentication to access to
cluster resources.
WHY
Avoid opening many ports,
some potentially without
authentication or SSL
protection.
HOW
Deploy a centralized
Apache Knox gateway.
Common Shared Services

Open source tools and technologies
Standardized SQL with Hive
Across any file system in the cloud or on-premises
Seamless architecture extending applications to the edge
Reducing Costs — Protecting Investments
Ensuring Application Portability

DataPlane: Single Point of Access, Pluggable Applications
* Not available as a DPS
module yet
Hortonworks DataPlane Service
• DLM - Data LifeCycle Manager
• DSS – Data Steward Studio
• DAS – Data Analytics Studio
• SMM – Streams Messaging Manager
DATA
SOURCES
DATA CENTER
Exception
Monitoring
360 View of
Operations
Cyber Security
CLOUD
Telemetry –
Connected
Devices
Time Series
EDGE
Sensors,
Control
Systems
DATAPLANE SERVICE (DPS)
MANAGE, GOVERN, SECURE
DATA
LIFECYCLE
MANAGER
DATA
STEWARD
STUDIO
EXTENSIBLE SERVICES
DATA
ANALYTICS
STUDIO
STREAMS
MESSAGING
MANAGER

MULTIPLE CLUSTERS AND SOURCES
MULTIHYBRID
Hortonwork
s
DataPlane
Service
MANAGE, SECURE,
GOVERN
DATA AT REST
Hortonworks
Data Platform
DATA IN MOTION
Hortonworks
Data Flow
Hortonworks
DataPlane
Service
MANAGE, SECURE,
GOVERN
ROI/Return StatementReduce security risk and
operational costs
Common metadata
Operational efficiency
Single set of policies
Ensure compliance
Policy
Policy
Policy
Policy
Policy
Consistently Secured and Governed
Policy

Cloud Data Stewardship Is Complex and Essential
Data must be made known, available, trusted and compliant
Increasing
Cloud Data Silos
Are Hampering
Value Creation Cloud-native analytics are rapidly creating new data silos
Data can be stored anywhere, in any format
IoT accelerating type, volume and distribution of data
Compliance mandates and fines are increasing pressure
$ 3.2M average per data breach
68% of IT organizations world-wide will be impacted by GDPR

Ensure consistent security and governance
for data assets across tiers
• Curate, discover and organize data assets
based on business classifications, purpose, protections, relevance, etc.
• Govern proper usage and lineage of data assets
to identify schema, classification and view lineage/data supply chain
• Understand and audit data asset security and use
for anomaly detection, forensic audit/compliance & proper control
mechanisms
…all across multiple types and tiers of data
Manage Data Governance and Security Policies Data Steward Studio

Dynamic Attribute-Based Security Policies
via Apache Atlas and Ranger Integration
Classification-
based Policy
A data asset such as a
table or column can
be marked with the
metadata tag such as
"PCI". This tag is then
used to assign
permission to a user
group.
Location-
based Policy
Administrators can
customize
entitlements based on
geography. A user
trying to access the
same data from
different locations
would trigger access
based on different set
of privacy rules.
Data Expiry-
based Policy
Apache Atlas can
assign expiration dates
to a data tag. Apache
Ranger would inherit
the expiration date
and automatically
deny users access to
the tagged data after
the expiration date.
Prohibition-
based Policy
It is now possible to
define a security
policy that restricts
combining two data
sets. Administrators
can now apply a
metadata tag to both
data sets to prevent
them from being
combined, helping
avoid privacy
violations.
Key Benefits
• New flexible
metadata based
security paradigm
• Dynamic, real-time
policy
• Active protection
— fast updates to
changes
• Centralized and
simple to manage
policy

Hortonworks
DataPlane
Service
MANAGE, SECURE,
GOVERN
IT Organization
Regional
Business Partner
Business Analyst
Partners
Data and Workload Agility
Support any cloud
Slow shadow IT growth
Reduce app rewrites
Move apps and data
Up to 37% reduction in
operational costs

Cloudbreak: Deploy Workloads Blueprints to any Cloud
• Declarative workload provisioning
across multiple cloud providers
• Flexible topologies and security
configuration options
• Easy setup and simple to
automate
• Built-in elasticity and auto-scaling
• Prescriptive integration with cloud
services
AWS
Cloudbreak
HDP + HDF
AWS
HDP + HDF

• Manage the data lifecycle:
– Replication/failback to another
cloud/on-prem site for disaster recovery
– Auto tiering of hot/warm/cold data to
cloud object storage/on-prem for TCO
reduction
– Backup & recover critical business data
• Maintain common security and governance
policies across multi data sources/
environments
Manage Data Movement and Protection with Data Lifecycle Manager
REPLICATION &
DISASTER
RECOVERY
Cluster Cluster ClusterMOVE MOVE
AUTO TIERING
BACKUP &
RESTORE
P(use): high
cost: $$$
P(use): medium
cost: $$
P(use): low
cost: $
Full
bacup
day 1 day 2 day 3
Cumulative
incremental
backups
Accident
delete
X
FAILBACK
REPLICATION
RESTORE
Prod
Cluster
Backup
Cluster
Generally available
Coming soon
Coming soon

Unique Data and Hybrid Cloud Expertise
Project Initiation, Management & Governance
• System Requirements
Gathering
• Technical Flows
Modelling
• Unit Testing
• System Testing
• Business case
development
• Business value
planning / realization
Implementation and
Optimization
Hybrid Architecture
• Hybrid Cloud Design
• Business Architecture
• Solution Architecture
• Data Architecture
• Standard Practices
• Practitioner
Knowledge &
Experience for Data &
Dev Teams
Data Engineering
• Data Ingestion
• Batch / Real-time
Processing
• ETL/ELT
• Data Management
• API development for
data consumption
Data Science
• Data Analysis
• Statistics
• Machine Learning
• Data Mining
• Statistical Modelling
• Research
• Algorithms
• Advanced Analytics
Comprehensive Professional Services Offerings 1000+ projects
Implementation risk
Manage entire lifecycle
Innovate faster
Reduce time to value by
as much as 42%

Delivering a Modern Hybrid Data Architecture Today
Cloud-native data architecture
Extend to the edge
Seamless architecture
Consistent security and governance
Hortonworks Data Platform
Hortonworks Dataflow
Hortonworks DataPlane
Open Hybrid Architecture Initiative
Requirements

The Open Hybrid Architecture Community Initiative
Seamless cloud and on-premises architecture
Containerization of workloads and applications
Separation of compute and storage
Foster community innovation
Hortonworks, IBM, Red Hat collaborate to help accelerate containerize big data
workloads for hybrid architectures – Sept 10, 2018Gold Member
The Next-Generation
Hybrid Cloud Platform
for Big Data Workloads

Thank You!

Hortonworks Hybrid Cloud - Putting you back in control of your data

Recommended

Recommended

More Related Content

What's hot

What's hot (20)

Similar to Hortonworks Hybrid Cloud - Putting you back in control of your data

Similar to Hortonworks Hybrid Cloud - Putting you back in control of your data (20)

More from Scott Clinton

More from Scott Clinton (6)

Recently uploaded

Recently uploaded (20)

Hortonworks Hybrid Cloud - Putting you back in control of your data