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What is RTO, RPO, WRT, MTD ?

When it comes to Disaster Recovery & High Availability Techniques, these Acronyms are a must. So will discuss a bit in further.

1. Business as usual

hadr1

At this stage all systems are running production and working correctly.

2. Disaster occurs

hadr2

On a given point in time, disaster occurs and systems needs to be recovered. At this point the Recovery Point Objective (RPO) determines the maximum acceptable amount of data loss measured in time.

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3. Recovery

hadr3

At this stage the system are recovered and back online but not ready for production yet. The Recovery Time Objective (RTO) determines the maximum tolerable amount of time needed to bring all critical systems back online.

4. Resume Production

hadr4

At this stage all systems are recovered, integrity of the system or data is verified and all critical systems can resume normal operations. The Work Recovery Time (WRT) determines the maximum tolerable amount of time that is needed to verify the system and/or data integrity. This could be, for example, checking the databases and logs, making sure the applications or services are running and are available.

5. Resume Production – Scenario

hadr5

The sum of RTO and WRT is defined as the Maximum Tolerable Downtime (MTD) which defines the total amount of time that a business process can be disrupted without causing any unacceptable consequences.

How to Enable JAVA application High Availability

HA-JDBC is a JDBC proxy that enables a Java application to transparently access a cluster of identical databases through the JDBC API.

ha-jdbc

HA-JDBC has the following advantages over normal JDBC:

  • High-Availability

The database cluster is available to service requests so long as at least one database node is active.

  • Fault Tolerance

Because HA-JDBC operates via the JDBC API, it is transaction-aware and can survive a database node failure without failing or corrupting current transactions.

  • Scalability

By balancing read requests across databases, HA-JDBC can meet increasing load by scaling horizontally (i.e. adding database nodes).

(source & for more info: http://ha-jdbc.github.io/doc.html)