Best Practice for Achieving High Availability in MariaDB
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This document discusses high availability and MariaDB replication. It defines high availability and outlines key components like data redundancy, failover solutions, and monitoring. It then describes MariaDB replication in detail, covering asynchronous and semi-synchronous replication as well as Galera cluster synchronous replication. MaxScale is introduced as a tool for load balancing, monitoring, and facilitating failovers in MariaDB replication topologies.
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Best Practice for Achieving High Availability in MariaDB
- 1. 2017 Roadshow 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. 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
- 6. 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. 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
- 9. 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
- 10. Data Redundancy HA for MariaDB
- 11. 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.
- 12. 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
- 13. 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
- 14. 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
- 15. 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
- 16. Async Replication Topologies Master and Slaves ReadOnly Slaves Master with Relay Slave Circular Replication
- 17. 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
- 18. 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)
- 19. 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
- 20. 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
- 21. 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
- 22. 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
- 23. 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
- 24. 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
- 25. MaxScale for HA
- 26. 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
- 27. MaxScale Use Case Master/Slaves Async Replication MaxScale monitors a MariaDB Topology Master/Slaves + R/W split routing Max Scale MariaDB
- 28. MaxScale Use Case Master/Slaves Async Replication Master/Slaves + R/W split routing Max Scale MariaDB 1 1 . Master failure
- 29. 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 Failover Script Monitor master_down event 2
- 30. 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 Failover Script Monitor master_down event 2 Promote as master3
- 31. 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 Failover Script Monitor master_down event 2 Promote as master3
- 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 4 . MaxScale monitor automatically detects new replication topology after the switch Master/Slaves + R/W split routing Max Scale MariaDB Monitor 2 4
- 33. 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
- 34. 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
- 35. Thank you Max Mether Field CTO max@mariadb.com