Learn strategies to maintain your database's high availability even during peak use periods. MariaDB's Field CTO Max Mether offers best practices for high availability, disaster recovery and more.

1. MariaDB High
Availability
Max Mether
Field CTO

2. High
Availability
Defined
In information technology,
high availability refers to a
system or component that is
continuously operational for a
desirably long length of time.
Availability – Wikipedia
up time / total time

3. Uptime,
Downtime, 9s
• 90% -> 36.5 days/year or 72 hours/month
• 99% -> 3.65 days/year or 7.2 hours/month
• 99.9% -> 8.76 hours/year or 43.8 minutes/month
• 99.99% -> 52.56 minutes/year or 4.38 minutes/month
• 99.999% -> 5.26 minutes/year or 25.9 seconds/month
• 99.9999% -> 31.5 seconds/year or 2.59 seconds/month
Availability = uptime /
(uptime + downtime)
Availability and HIGH Availability
Source: http://en.wikipedia.org/wiki/High_availability

4. High Availability Background
• High Availability isn’t always equal to long Uptime
– A system is “up” but it might not be accessible
– A system that is “down” just once, but for a long time, is NOT highly available
• High Availability rather means
– Long Mean Time Between Failures (MTBF)
– Short Mean Time To Recover (MTTR)
• High availability is:
– a system design protocol and associated implementation that ensures a certain degree of
operational continuity during a given measurement period.

5. Approach to HA
Backup /
Restore
1
< 99.9%
Replication /
Automatic
failover
3
~ 99.99%
Simple
replication /
manual
failover
2
~ 99.9%
3 nodes Galera
Cluster
~ 99.999%
4 5
Other
Strategies for High Availability

6. An average of 80 percent of mission-critical application service
downtime is directly caused by people or process failures. The
other 20 percent is caused by technology failure, environmental
failure or a disaster
Gartner Research

7. High Availability Components
High availability is a system design protocol and associated implementation that
ensures a certain degree of operational continuity during a measurement period.
For stateful services, we
need to make sure that
data is made redundant.
It is not a replace for
backups!
Data Redundancy
Some mechanism to
redirect traffic from the
failed server or
Datacenter to a working
one
Failover or Switchover
Solution
Availability of the
services needs to be
monitored, to take
action when there is a
failure or even to
prevent them
Monitoring and
Management

8. HA Dictionary

9. General Terms
• Single Point of Failure (SPOF)
– An element is a SPOF when its failure results in a full stop of the service as no other element
can take over (storage, WAN connection, replication channel)
– It is important to evaluate the costs for eliminating the SPOF, the likelyhood that it fails, the
time required to bring it into service again
• Shared Storage Architecture
– Shared storage systems like SANs can provide built-in high availability, though this comes with
equally high costs
– Not really suitable for Disaster Recover scenario on multiple Data Center
• Shared Nothing Architecture
– Each node is independent and self-sufficient

10. General Terms
• Split-Brain
– When nodes in the cluster continue running but cannot communicate causing them to be
inconsistent
– To be avoided at all cost
• Switchover
– When a manual process is used to switch from one system to a redundant or standby system in
case of a failure
• Failover
– Automatic switchover, without human intervention
• Failback
– A (often-underestimated) task to handle the recovery of a failed system and how to fail-back to
this system after recovery

11. Data Redundancy
HA for MariaDB

12. MariaDB Replication
• Replication enables data from one MariaDB server (the master) to be replicated to one or
more MariaDB servers (the slaves).
• MariaDB Replication is:
– very easy to setup
– used to scale out read workloads
– provide a first level of high availability and geographic redundancy
– offload backups and analytic jobs.

13. The Binary Log
• Each MariaDB server has a binary log that should be enabled in most cases
• The server stores all changes that happen on the server in the binary log
• The binary log has three modes:
a. ROW: Row change events are stored in the binary log
b. STATEMENT: SQL Statements that change data are stored in the binary log
c. MIXED: Most events are replicated in STATEMENT based but some ROW based

14. Asynchronous Replication
• MariaDB Replication is asynchronous by default.
• Slave determines how much to read and from which point in the binary log
• Slave can be behind master in reading and applying changes
• If the master crashes, transactions might not have been transmitted to any slave
• Asynchronous replication is great for read scaling as adding more replicas does not
impact replication latency

15. Asynchronous Replication Phases
• 3 phases for each transaction:
1. The transaction is committed and written to the masters binary log
2. The slave reads the transaction and writes it to its relay log
3. The transaction is applied on the slave

16. Asynchronous Replication-Switch Over
1. The master server is taken down or we encounter a fault by our monitoring
2. The slave server is updated to the last position in the relay log
3. The clients point at the designated slave server
4. The designated slave server becomes the master server
5. All steps are manual
Master and Slaves
ReadOnly Slaves
Master and Slaves
ReadOnly Slaves

17. Async Replication Topologies
Master and Slaves
ReadOnly Slaves
Master with Relay Slave Circular Replication

18. Semi-synchronous Replication
• MariaDB supports semi-synchronous replication:
– the master does not confirm transactions to the client application until at least one slave has
copied the change to its relay log, and flushed it to disk.
– In semi-synchronous replication, only after the events have been written to the relay log and
flushed the slave does acknowledge receipt of a transaction's events
– Semi-synchronous is a practical solution for many cases where high availability and no data-loss
is important.
– When a commit returns successfully, it is known that the data exists in at least two places (on the
master and at least one slave).
– Semi- synchronous has a performance impact due to the additional round trip

19. MariaDB Enhanced Semi-synchronous Replication
• One or more slaves can be defined as working semi-synchronously.
• For these slaves, the master waits until the I/O thread on one or more of the semi-synch slaves
has flushed the transaction to disk.
• This ensures that all committed transactions are at least stored in the relay log of the slave.
• Standard semi-synchronous replication would commit the transaction before it gets the
acknowledge of the binlog event from a slave (AFTER_COMMIT or AFTER_SYNC)

20. Semi-synchronous Replication – Switch Over
• The steps for a failover are the same as when using the standard replication
• but in Step 2, a slave should be chosen among those (if many) that are be semi- synched
with the master
Master and Slaves
Semi-Sync
Slave
Async Slaves
Master and Slaves
Async Slaves

21. Semi-Sync Replication Topologies
• Semi- synchronous replication is used between master
and backup master
• Semi- sync replication has a performance impact, but the
risk for data loss is minimized.
• This topology works well when performing master
failover
– The backup master acts as a warm-standby server
– it has the highest probability of having up-to-date data if
compared to other slaves.
Semi_sync
Asynchronous
ReadOnly/
Backup Master
ReadOnly

22. MariaDB Multi-Source Replication
• It enables a slave to receive transactions from
multiple sources simultaneously.
• It can be used to backup multiple servers to a
single server, to merge table shards, and
consolidate data from multiple servers to a single
server.
Master 2Master 1 Master 3
Slave

23. Synchronous Replication
MariaDB Galera Cluster
• Galera Replication is a synchronous multi-master
replication feature enables a true master-master
setup for InnoDB.
• Every node is a share nothing server
• All nodes are masters and applications can read and
write from any node
• A minimal Galera cluster consists of 3 nodes:
– A proper cluster needs to reach a quorum (i.e. the
majority of the nodes of the cluster)
• Transactions are synchronously committed on all
nodes.
MariaDB
MariaDB
MariaDB

24. How it works
• A transaction is started by connecting to one of the
nodes
• Everything (locks, modifications etc) is local until
the transaction is committed
• Upon commit, the writeset is sent out to the other
nodes for certificaton
• The other nodes verify that the transaction doesn't
conflict with any open transactions local to them and
at the same time store the writeset
• If certified the transaction is committed on all nodes
• If the certification fails (due to a conflict) the
transaction is aborted
MariaDB
MariaDB
MariaDB

25. MariaDB Cluster Pros
• PROS
– A high availability solution with synchronous
replication, failover and resynchronization
– No loss of data
– All servers have up-to-date data (no slave lag)
– Read scalability
– 'Pretty good' write scalability
– High availability across data centers
MariaDB
MariaDB
MariaDB

26. MariaDB Cluster Cons
• CONS
– It only supports InnoDB
– The transaction rollback rate and hence the
transaction latency, can increase with the number of
the cluster nodes
– The cluster performs as its less performing note: an
overloaded master affects the performance of the
Galera cluster
MariaDB
MariaDB
MariaDB

27. MaxScale for HA

28. MDBE
Cluster Failover
Clustered nodes cooperate
to remain in sync
With multiple master nodes,
reads and updates both scale*
Synchronous replication with
optimistic locking delivers high
availability with little overhead
Fast failover because all
nodes remains synchronizedMariaDB
MariaDB
MariaDB
Load Balancing
and Failover
Application /
App Server

29. MaxScale Use Case
Master/Slaves Async
Replication
MaxScale monitors a MariaDB Topology
Master/Slaves + R/W split routing
Max
Scale
MariaDB

30. MaxScale Use Case
Master/Slaves Async
Replication
Master/Slaves + R/W split routing
Max
Scale
MariaDB
1
1 . Master failure

31. MaxScale Use Case
Master/Slaves Async
Replication
1 . Master failure
2 . MaxScale Monitor detects the master_down
event
Master/Slaves + R/W split routing
Max
Scale
MariaDB
script
Failover Script
Monitor
master_down event
2

32. MaxScale Use Case
Master/Slaves Async
Replication
1 . Master failure
2 . MaxScale Monitor detects the master_down
event
3 . In case it is configured, MaxScale launches a
Failover Script that promotes a slave as a new
Master
Master/Slaves + R/W split routing
Max
Scale
MariaDB
script
Failover Script
Monitor
master_down event
2
Promote as master3

33. MaxScale Use Case
Master/Slaves Async
Replication
1 . Master failure
2 . MaxScale Monitor detects the master_down
event
3 . In case it is configured, MaxScale launches a
Failover Script that promotes a slave as a new
Master
Master/Slaves + R/W split routing
Max
Scale
MariaDB
script
Failover Script
Monitor
master_down event
2
Promote as master3

34. MaxScale Use Case
Master/Slaves Async
Replication
1 . Master failure
2 . MaxScale Monitor detects the master_down
event
3 . In case it is configured, MaxScale launches a
Failover Script that promotes a slave as a new
Master
4 . MaxScale monitor automatically detects new
replication topology after the switch
Master/Slaves + R/W split routing
Max
Scale
MariaDB
Monitor 2
4

35. MaxScale Use Case
MDBE Cluster
Synchronous Replication
Each application server
uses only 1 connection
MaxScale selects one node
as “master” and the other
nodes as “slaves”
If the “master” node fails,
a new one can be elected
immediately
Galera Cluster + R/W split routing
Max
Scale

36. MariaDB HA: MaxScale
• Re-route traffic between
master and slave(s)
• Does not manage servers
• Failover / slave promotion
is an external process
• Implemented for Booking.com
• Part of MaxScale release
• All slaves are in sync,
easy to promote any slave
Read / Write Splitter
Detects Active Master
Binary Log
Server

37. Thank you
Max Mether
Field CTO
max@mariadb.com