Distributed Cache Service (DCS)

For e-commerce, video sharing, gaming, and other data-intensive applications, it is essential for data to be retrieved as quickly as possible. Distributed Cache Service (DCS) in T Cloud Public provides a fast, yet inexpensive data retrieval, allowing you to access data from in-memory data stores instead of relying entirely on slower disk-based data sources.

Redis (NoSQL database) is available in T Cloud Public as DCS. It is ideal for use as a cache service, e.g., in order to accelerate the loading times of websites, mobile apps and microservices, and is able to handle various data structures. Clusters made up of individual DCS instances can be used for applications with extremely high performance requirements. DCS in T Cloud Public is billed on an hourly basis is accordance with the chosen RAM size and type (single-node, primary/standby or clustered data store).

The DCS Web Console provides various features, such as easy restarting instances, managing configuration parameters and direct Web-CLI to access your data storage. Configure a detailed backup plan and perform restores with just one click.

DCS supports online migration tasks from backup data or external data sources with minimal downtime. DCS instances can be scaled very easily and securely to larger or smaller instances.

DCS is integrated into T Cloud Public Security services, including Identity and Access Management (IAM), Virtual Private Cloud (VPC) and Cloud Trace Service (CTS). More than 30+ Metrics can be monitored using Cloud Eye Service (CES). The DCS clusters are distributed with multiple nodes across several availability zones and can therefore guarantee high availability and reliability.

DCS is a great choice for implementing a highly available in-memory cache to decrease data access latency, increase throughput, and ease the load of your relational or NoSQL databases. DCS can serve frequently requested items (such as metadata, images and files) at sub-millisecond response times, and enables you to easily scale for higher loads without growing the costlier backend services.

DCS is a popular choice among game developers looking to build real-time leader boards. Simply use the DCS Sorted Set data structure, which provides uniqueness of elements while maintaining the list sorted by users' scores.  You can also use Sorted Sets to handle time series data by using timestamps as the score.

DCS is also often used to manage session data for internet services with high number of concurrent users. DCS provides the sub-millisecond latency, scale, and resiliency required to manage session data such as user profiles, credentials and user-specific personalization.

DCS supports Pub/Sub and Streams with pattern matching. This allows DCS to support high performance chat rooms, real-time comment streams, social media feeds and more.

For use cases like fraud detection in gaming and financial services, real-time bidding, matchmaking and ride sharing, the ability to process live data and make decisions within tens of milliseconds is quite important. DCS gives you a fast in-memory data store to build, train, and deploy machine learning models quickly to support automated decision making.

DCS can be used with streaming solutions such as Apache Kafka as an in-memory data store to ingest, process, and analyze real-time data with sub-millisecond latency. DCS is an ideal choice for real-time analytics use cases such as social media analytics, ad targeting, personalization, and IoT.

• Manage instance: configure DCS parameters, SSL and access lists
• Web command line: get full access to DCS CLI from Console
• Perform cache analysis: hot key analysis, expired key scans and many more
• Online migration & scaling: elastic scaling with limited downtime
• Backup & restore data: advanced backup plan and restore data easily
• Instance switching: switch manually or automated between instances
• Manage shards in clusters: promote and demote nodes in a cluster

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Distributed Cache Service
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