NICTA, Disaster Recovery Using OpenStack
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Building a Disaster Recovery Solution using OpenStack
Jorke Odolphi
Principal Research Engineer
NICTA
@jorke
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http://bionicvision.org.au/eye
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The Team
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Yuru – ‘cloud’, Gamilaraay People NSW
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Problem
The cloud can fail.
Online businesses that rely and benefit most from the cloud don’t have the skills
to handle failure.
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Disaster Recovery
process, policies and procedures related to preparing for recovery or continuation of
technology infrastructure critical to an organisation after a natural or human-induced
disaster *
*according to wikipedia..
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RPO
Recovery Point Objective
“maximum tolerable period in which data might be lost from an IT Service due to a Major
incident…” *
*according to wikipedia..
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RTO
Recovery Time Objective
“duration of time and a service level within which a business process must be restored after
a disaster…” *
*according to wikipedia..
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Recovery Time Objective0 downtime Sometime...
Realtime recovery/
failover
Recovery Point
Objective
Somewhere..
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Without re-architecting your application;
Provide a configurable warm standby solution,
with a known consistent RPO,
reducing RTO,
minimising business impact.
Our Goal
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Goals and Challenges
Replicate application over to OpenStack in case of a disaster
–Preserve the running environment of the application, this includes:
• Compute instances
• Networks
• DNS
Minimise RTO and RPO AND cost!
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mypizzashop.com.auPublic IP / Load Balanced
Web front endApache/Nginx/IIS
app.mypizzashop.com.auPrivate IP
ApplicationProcessing/memcache
db.mypizzashop.com.auPrivate IPDatabase
MySQL/PostgreSQL/MSSQL
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Architecting for DR in Cloud
Virtualise your servers
– snapshotting support in hypervisor primarily at the disk
Use Dynamic DNS solutions
– E.g. Route 53, Anycast DNS
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Compatibility across IaaS Clouds
Cloud Provider
Framework Compute Instance
Object Store
Block Storage
Network Security Group
AWS Custom ✓ ✓ ✓ DHCP ✓
Rackspace Custom ✓ ✓ ✗ STATIC ✗
Ninefold CloudStack ✓ ✓ ✓ DHCP ✓
TryStack OpenStack ✓ ✓ ✓ DHCP ✓
HP Cloud OpenStack ✓ ✓ ✗ DHCP ✓
• Replication from one cloud to another is NOT always possible • Some clouds do not have all the technology pieces (e.g., Block Storage)
• Minimum requirements for replicating application servers: • compute instance and persistent storage, such as object store or block storage • Snapshot service (to ensure point-in-time consistency) • Hypervisor support (e.g., PVGrub)
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Overview of DR Process
AWSTake snapshot Create volume
Partition
Send to storageDownload from storage
OpenStackMount new
instance
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Building DR using OpenStack
Progress: – Deploying OpenStack in our NICTA lab – Successfully replicated AWS compute instances to
OpenStack • In Rackspace OpenStack public cloud (private beta) • Instances created from standard 64-bit EXT3 AWS OpenSuse
image
Requirements: – Xen support for PVGrub – Write access to partition table – Network support
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Problems
Latency Point in Time Log and replay / transactional How do modern databases handle broken transactions / problem disks? Rollback
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Optimisations: Incremental Backup
Typical AWS system volume is around 10GB
Replication is tricky for large data volumes
– Initial backup:
• Send the whole data volume (unavoidable!)
• Optimise by compression and skipping empty space (0’s)
– Subsequent backups:
• Incremental – partition a volume into chunks and resend only the difference (the ‘delta’)
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Large Data Transfer Across Cloud Datacenters Why so slow?
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Optimisations: Large Data Transfer Across Cloud Datacenters for DR
Problem: Transferring large data volumes is slow
– Where is the bottleneck?
• Reading from the source volume? YES!!
• Transferring across LAN/WAN?
• Writing to destination volume?
• Our solution
Rapidly Cloning data volumes from snapshots
– Parallel transfers
50 40
190
140
Volume Scan (MB/s) End-to-end Transfer(MB/s)
Data Transfer Evaluations
1 Clone 4 Clones
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Reversing..
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Point us to your instances
Replicate to new cloud/region
Automatically sync changes every hour
If the worst happens: failover
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