Open Telekom Cloud for Business Customers

Distributed Message Service (DMS)

The Distributed Message Service (DMS) in the Open Telekom Cloud is based on Apache Foundation's Kafka solution and enables communication between different applications, for example in order to synchronize data and processes. The DMS works like a postal service within the cloud: senders and receivers do not need to be active at the same time. Applications that send messages in the form of JSON objects do not need to wait for acknowledgment of receipt from other applications – the DMS creates a processing queue and sends the message at a later point. This enables coordination between individual components of a cloud application, for instance in order to synchronize the status of data, making DMS the perfect solution for large, distributed application landscapes.

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Reasons for DMS in the Open Telekom Cloud

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High availability

DMS stores queued messages on different servers, and each message has multiple replicas, achieving high reliability and availability.

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High reliability

Data replication and synchronous flushing to disks ensure up to 99.99999999% data reliability, while clustered and cross-AZ deployments ensure up to 99.95% service availability.

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High performance

DMS queues can support millions of messages without compromising performance and can reach a throughput of 100,000 concurrent messages per second. Message delivery time is accurate to the millisecond.

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Security

DMS interacts with Cloud Trace Service (CTS) to record and audit tenant management operations. Encrypted message storage protects them from unauthorized access.


Key Features of DMS

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Message features

  • Message filtering
    Consumers can use labels to filter the messages they want to retrieve from the chosen queue.
  • Message tracking
    Messages that have already been retrieved can be retrieved again from the specified time or position.
  • Intentional delay delivery
    Messages can be delivered after a specified delay.
  • Message broadcasting
    The same message can be delivered to all consumers in a consumer group.
  • Message re-delivery
    Messages that will not be immediately retrieved can be returned to the original queues. Consumers can retrieve them when they wish.
 
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Queue types and access protocols

DMS is compatible with native Kafka queues, so you can migrate your message services without any modifications.

  • Multiple queue types
  • Multi-protocol access
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Queue features

DMS queues support dead letters queues, queue sharing and authorization.

  • Dead letter queue

Use Cases

DMS can be used in various fields, such as enterprise applications, online payments, telecommunications, e-commerce, logistics, marketing, social networking, Instant Messaging (IM), mobile gaming, video, Internet of Things (IoT), and Internet of Vehicles (IoV).

Distributed Message Service is useful in the following scenarios:

Service decoupling

Eventual consistency

Off-peak traffic control

Log synchronization

 

Structure and Function

DMS works in distributed and highly scalable computing clusters and comes with standardized RESTful APIs that are used to access the generated messages. The queued messages are stored on different partitions, and the cloud-native service can be used without any additional hardware or software resources. The DMS can be controlled via the web console, OTC Terraform Provider, or the OpenStack command-line interface. The generated message queues or Apache Kafka Premium clusters are processed in sequence in accordance with the first-in-first-out principle. In addition, the DMS supports dead letter queues (in which messages that could not be delivered are stored).

Step 1: A producer sends message M to a message queue. Message M is redundantly distributed in the queue.

Step 1

A producer sends message M to a message queue. Message M is redundantly distributed in the queue.

Graphic that describes who a consumer receives a message from the queue

Step 2

A consumer receives message M from the queue.

While message M is being retrieved, it remains in the queue. It cannot be retrieved again within 30s since the start of retrieval. If message M fails to be acknowledged within this period, it can be retrieved again.

Diagram When message is confirmed, it can be retrieved to Queue

Step 3

Once message M is acknowledged, it can no longer be retrieved by consumers from the same consumer group.

However, it can still be retrieved by consumers from other consumer groups. It remains in the queue for at least 72 hours (unless the queue is deleted) and will be deleted after this period.

 

Distributed Message Services as a shared or dedicated solution

The Open Telekom Cloud offers message queues as part of a shared model, meaning that computing resources are shared between customers and costs are assigned based on the number of API calls and queues triggered.

Apache Kafka Premium, on the other hand, offers a dedicated, managed cluster solution with maximum availability at the touch of a button. Compared to message queues, Kafka Premium offers a guaranteed data throughput for messages, which is essential for enterprise solutions. Kafka Premium can be used both internally via the secure OTC network, and externally via the internet. The cluster costs depend on your desired cluster size and are incurred on an hourly basis, regardless of the number of API calls and queues. This makes it easy for you to calculate the cost of your business case.

Kafka Premium instances use physically isolated computing, storage, and bandwidth resources. You can customize partitions and replicas for Kafka topics in the instances, and configure the network bandwidth as required. The instances can be used right out of the box, taking off the deployment and O&M pressure for you so that you can focus on developing your services.

 

New Features

Kafka Premium now with Kafka 2.3 available (beta) View details
Kafka Premium now with Kafka 2.3 available (beta phase completed)View details
Discontinue DMS Queue Manager end of June 2022View details

Find out more

 

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