How To Understand And Understand The Risks Of Configuration Drift

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Transcription:

How to: Eliminate Configuration Drift Risk Gil Hecht, CEO Continuity Software

SNIA Legal Notice The material contained in this tutorial is copyrighted by the SNIA. Member companies and individual members may use this material in presentations and literature under the following conditions: Any slide or slides used must be reproduced in their entirety without modification The SNIA must be acknowledged as the source of any material used in the body of any document containing material from these presentations. This presentation is a project of the SNIA Education Committee. Neither the author nor the presenter is an attorney and nothing in this presentation is intended to be, or should be construed as legal advice or an opinion of counsel. If you need legal advice or a legal opinion please contact your attorney. The information presented herein represents the author's personal opinion and current understanding of the relevant issues involved. The author, the presenter, and the SNIA do not assume any responsibility or liability for damages arising out of any reliance on or use of this information. NO WARRANTIES, EXPRESS OR IMPLIED. USE AT YOUR OWN RISK. 2

Abstract This session will appeal to: Chief Information Officers IT Management: System(Unix/Win/Cluster/VM) & Storage Managers Business Continuity Managers Those seeking a fundamental understanding of HA/DR Risks Topics covered Downtime & Data Loss Major Business Risk Configuration Drift Leading Cause of Downtime & Data Loss Understanding Configuration Drift Eliminating Configuration Drift with HA/DR Configuration Analytics HA/DR Configuration Analytics How it works 3

IT s greatest nightmares Critical data loss Unplanned (& prolonged ) downtime 4

Having the right infrastructure Redundant datacenters Data replication Manual failover configuration / Local and Geo-Cluster 5

Is simply not enough The problem: configuration drift Standby systems get out of sync Production environment constantly changes Changes manually applied to HA and DR systems Some changes slip through Existing mitigation approach fails Annual manual & expensive DR & HA tests Testing results: 75% failure rate as recovery configurations are out of sync with their production configurations (*) 6

Solution: Configuration Analytics Automatic Detection & Alerting: HA / Cloud / DR Vulnerabilities & Inefficiencies Cross Vendor Best Practice Violations Benefit: Reduced Risks, Effort & Costs 7

Sample Gap Partial Replication Result: Data Loss 8

Sample Gap - Sync Replication RDF Group Replication Inconsistency Result: Data loss, increased time to recover 9

Sample Gap - Tampering Risk Result: DR failure and data corruption 10

Sample Gap - Local Replication with BCVs Replication Age Inconsistency Result: Data corruption 11

Config Drift: Production DR/HA Hardware 8 x CPU 2.2Ghz 32 GB RAM 2 x HBA 2 x NIC Software OS: HP-UX 11.31 WebSphere Java 1.5 EMC PowerPath 4.4 Kernel Parameters Max up processes: 8192 Max # of semaphores: 600 Hardware 2 x CPU 2.2Ghz 8 GB RAM 1 x HBA 1 x NIC Software OS: HP-UX 11.23 NO WebSphere Java 1.4.2 EMC PowerPath 3.0.5 Kernel Parameters Max up processes: 1024 Max # of semaphores: 128 More differences in the areas of DNS, NTP, Page files, Internet services, patches, etc Result: Increased time to recover 12

Config Drift 2: Production DR/HA Hardware 2 x HBA Software Microsoft.NET 2.0 SP 2 Windows x64 SP 1 Oracle MTS Recovery Service DNS Configurartion 192.168.68.50 192.168.68.51 192.168.2.50 Page Files 1 x 1 GB (c:\) 1 x 4 GB (d:\) Kernel Parameters Number of open files: 32767 Hardware 1 x HBA Software Microsoft.NET 2.0 SP 1 Windows x64 SP 1 Oracle MTS Recovery Service DNS Configurartion 192.168.68.51 Page Files 1 x 1 GB (c:\) 1 x 4 GB (d:\) Kernel Parameters Number of open files: 8192 Result: Downtime, manual intervention needed to recover 13

Suspended Replication Result: Reduced MTBF, Downtime, Sub-optimal performance 14

Config Drift is Not for Humans Numerous interconnected systems in the Datacenter X Practically unlimited configuration options for each X ( Daily growth, changes, patches, upgrades + Inability to instantly validate configuration ) = Failure = Downtime & Data Loss 15

Solution: Configuration Analytics Automatic Detection & Alerting: HA / Cloud / DR Vulnerabilities & Inefficiencies Cross Vendor Best Practice Violations Benefit: Reduced Risks, Effort & Costs 16

What s required Discovery Import of IT elements from CMDB / Other Systems Optional: Automatic discovery Scanning of entire IT for configuration data: Database-Cluster-Virtualization-Server-Storage-Replication Optional: Use existing CMDB data Recommended: Agent-less, Read-only, Non-intrusive Configuration Analytics to discover Risks & Inefficiencies Recommended: Updatable Risks & Inefficiencies databases Community driven risk database 17

How It Works Storage arrays Scanning Storage Arrays via Vendor API for maximum accuracy System Server Hosts Database SSH / WMI using valid user credentials Web browser Databases JDBC using valid user credentials 18

How to get started? If you want to Get a one time accurate assessment of your Downtime & Data Loss Risks If you want to Continuously monitor for Downtime & Data Loss Risks Start with technology pilot & ask for free vulnerability scan Start by deploying HA/DR Configuration Analytics 19

Starting with Technology Pilot Demand the free HA/DR Vulnerability Detection Report from your leading IT Provider / Vendor. Report should cover Risks & Improvement opportunities for: Databases, Clusters, Private Cloud / Virtual Machines, Operating Systems, Servers, Storage Arrays, Replication Mechanisms, Etc Typically takes < 3 days from install to report 20

Starting with Full Deployment Key factor for choosing the right system: Breadth & depth of Risk (Signatures) Database Impact on production systems (Should be minimal) Deployment effort (Should be <5 days for large datacenter) Expected benefits / results Dramatic reduction in downtime & data loss events HA/DR Testing Results Improvement & reduced effort New Risks expected to be discovered daily for med-large datacenters 21

Q&A / Feedback Please send any questions or comments on this presentation to SNIA: trackstoragemgmt@snia.org Gil Hecht Many thanks to the following individuals for their contributions to this tutorial. - SNIA Education Committee 22