Data Protection Modernization: Meeting the Challenges of a Changing IT Landscape

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1 Data Protection Modernization: Meeting the Challenges of a Changing IT Landscape Tom Clark IBM Distinguished Engineer, Chief Architect Software 1

2 Data growth is continuing to explode Sensors & Devices IoT will connect 30 billion devices by 2020 Data Explosion 2.5 Billion gigabytes of data per day we are here Social Media 6.75 TBs of data will be created per person per day by % of data created in last two years Growth of data from different sources VoIP Enterprise Data SOURCE: *2014 IBM Institute for Business Value Study on Infrastructure Matters; Gartner IT Metrics 2

3 trends Continued dramatic growth in data driven by mobile, analytics, IoT, hybrid cloud, cognitive business and big data Transition of data types with new workloads, new applications New storage deployment models powered by software Transition to cloud models 60% of clients committed to SDS 23% interested 70% of clients deploying object storage or plan to within 24 months By 2018, storage-rich servers are expected to account for 50% of new capacity purchases IDC predicts that over 80% of enterprise IT organizations will commit to hybrid cloud architectures by Sources: ESG, IDC 3

4 Traditional and New Generation Applications Traditional application workloads New generation application workloads Traditional workloads require further optimization, leveraging features in applications, hypervisors and storage Optimize here Scale out infrastructure to support new workloads requires new approaches to management Extend here 4

5 Traditional Data Protection Approach Traditional Applications Hypervisors Purpose Recover from storage failure Disaster recovery Recover from application or operator error Recover from malware Archive or regulatory copy Systems Integration with APIs and CLIs Client or Proxy Data Mover Incremental forever or Periodic full + incremental copy Integration with backup server Deduplication/compression Tiered storage DR copy Long term retention Copyright IBM Corporation

6 Traditional Data Protection Challenges /restore are times too long for critical applications 6

7 Traditional Data Protection Challenges Scale out applications don t map well to traditional backup infrastructures 7

8 Traditional Data Protection Challenges Data protection for apps moving to cloud and cloud apps On Premises Cloud IaaS, PaaS, SaaS 8

9 Traditional Data Protection Challenges It s hard to reuse backup data for other purposes Dev-Ops Analytics 9

10 Traditional Data Protection Challenges Compliance with increasing regulations Forget about me 10

11 Traditional Data Protection Challenges Avoiding and recovering from ransomware Air Gap?: Periodic Connectivity Replication Air Gap?: Periodic Connectivity Replication Air Gap? Air Gap 11

12 Evolution of Data Protection: Snapshot Advantages: Fast backup, fast recovery Challenges: End to end orchestration Complexity The old way works (or used to) Snapshot Orchestration Optional Periodic 12

13 Evolution of Data Protection: Self-Protecting Advantages: Fast backup, fast recovery Challenges: End to end orchestration, reporting Data movement for large backups Snapshot or Differential Direct Copy to 13

14 Evolution of Data Protection: Scale-out Application Self-protecting Applications, Self-service Copy to Advantages: Operates at scale Challenges: End to end management, reporting Lack of capability in current applications App developer expertise Application Snapshot and Replication Scale-out Snapshot and Replication 14

15 Evolution of Data Protection: Data Protection in Clouds Advantages: Similar operations to on premises Challenges: Centralized hybrid management Lack of capability or APIs in cloud *aas Cloud On Premises Disk Traditional IaaS, PaaS, SaaS Snapshot or Application-driven 15

16 Evolution of Data Protection: Data Reuse DevOps and Analytics Advantages: Leverage collected data Immediate data availability Challenges: End to end orchestration Performance of mounted data Direct Mount Snapshot or Differential Replication 16

17 What We Need in Data Protection Data Sources Traditional Apps Hypervisors Scale-out Apps Key Capabilities Software-defined solutions Simplicity Orchestration Central catalog Central reporting Self-service Complete data functions Data Functions Data Sinks Systems Data Mover Integration App Instance IaaS, PaaS, SaaS Mount/Re-use Application or Replication Systems 17

18 Thank You! 18