A system design approach in cloud databases known as ‘high availability’ ensures maximum performance for operational activities. Much planning part is needed for gaining high availability around data storage and backup systems.
A well designed and thoroughly tested database design prevents any failure in the data processing. To achieve high availability/fault tolerance (low latency, zero downtime) on Cloud database systems and to avoid failures, following measures should to be adapted:
1. Numerous Zones:
In Cloud computing, the resources are physically separated from one, thus creating multiple zones. Each zone provides cloud computing facilities for application deployment and several other zones share the service.
Having multiple zones provides an effective design for fault tolerance. For example, a failure in a given location can be overcome by distributing services to the remaining zones. Consumers in failure zone can access services by fail-over process technique where they get access to same services hosted in other zone/geography.
To achieve high availability for cloud computing database systems, it’s one of the necessary conditions that need to be satisfied.
2. Scattered Platforms:
Also known as distributed data management platform, scattered platform is a highly scalable, replicated data & low latency system. The inclusion of in-memory database technology offer features such as, auto sharing and global data replication. Distributed platforms are highly scalable in the cloud-based architecture and offer great flexibility.
3. Query Registration:
Event driven applications are often used in the internet for delivering notifications to many individual users. To post scheduled updates, server involves a process of polling resources. Constantly responding to an individual even if there is no update on the network is a resource-centric approach.
To overcome this problem, the client can have a query registered through a robust registration mechanism and must not be responded to by the server until there appears any update on the network. A load on the server can be reduced to a great extent by adapting a strategy that must respond only in case when the results change in a query.
4. Local Caches:
A node can always be deployed at client’s end to provide access to application data in low bandwidth connection. The client will get access to data through the local cache feature and a higher bandwidth connection can update the cache, later on. This will enhance the user experience even in the low bandwidth and offline mode, by making high availability of data.
5. Loose coupling of Components:
The design principle of loosely coupling the system provides a way for asynchronous messaging. It ensures that highly distributed cloud applications are not needlessly reliant on each-other. This also lessens the burden of message delivery application system and allows central management of all messages. The loose coupling of components in cloud database allows the message restoration and re-delivery facility in case anything goes wrong.
6. Atomic and Unchanged Services:
Atomicity is the smallest and independent part of any process. Atomic services are the services which can’t be logically made smaller through division.
An Idempotent (unchanged) service provides a safe method of invoking a service several times, without changing the original value. The clients can invoke both these services several times until they get a satisfactory outcome. Being atomic means that in case if a service is not available at all, minimum amount of functionality is lost on the client side. Idempotent means, the service can be used to facilitate multiple invocations and no accidental results are obtained. For example: providing same pin more than once for a mobile recharge should not result in a successful account credit for the customer twice.