IONOS Event Streams for Apache Kafka offers a range of cluster sizes to meet the diverse needs of different applications, from development and testing environments to large-scale production deployments. Each cluster size is designed with specific hardware configurations to provide the right balance of performance, capacity, and cost-efficiency.
Node Count: 3
Cores per Node: 1
RAM per Kafka Broker: 2 GB
Storage per Broker: 195 GB
Total Storage: 585 GB
The XS cluster is ideal for development, testing, and small-scale applications that require a modest amount of resources. It provides sufficient capacity to handle light workloads while maintaining cost efficiency.
Node Count: 3
Cores per Node: 2
RAM per Kafka Broker: 4 GB
Storage per Broker: 250 GB
Total Storage: 750 GB
The S cluster is suitable for small to medium-sized applications that need moderate resources. It offers enhanced performance and storage capacity compared to the XS cluster, making it a good choice for applications with higher throughput and storage requirements.
Node Count: 3
Cores per Node: 2
RAM per Kafka Broker: 8 GB
Storage per Broker: 400 GB
Total Storage: 1200 GB
The M cluster is designed for medium-sized applications that demand higher performance and greater storage capacity. It provides a balanced configuration that can handle increased data volumes and more intensive processing tasks.
Node Count: 3
Cores per Node: 4
RAM per Kafka Broker: 16 GB
Storage per Broker: 800 GB
Total Storage: 2400 GB
The L cluster is well-suited for large applications with high throughput and substantial storage needs. With more cores and RAM per broker, this cluster size delivers superior performance and can support more demanding workloads.
Node Count: 3
Cores per Node: 8
RAM per Kafka Broker: 32 GB
Storage per Broker: 1500 GB
Total Storage: 4500 GB
The XL cluster is designed for enterprise-level applications and extremely high-throughput environments. It offers the highest performance and storage capacity, ensuring that even the most demanding applications can run smoothly and efficiently.
IONOS Event Streams for Apache Kafka allows you to choose the cluster size that best fits your current needs while providing the flexibility to scale as your requirements evolve. You can start with a smaller cluster and easily upgrade to a larger size as your data volumes and processing demands increase. This flexibility ensures that you can optimize costs while maintaining the ability to grow your Kafka deployment seamlessly.
To determine the best cluster size for your needs, consider your application’s data throughput, processing requirements, and storage demands. For more detailed guidance, please refer to our Cluster Sizing Guide or contact our support team for personalized assistance. By selecting the appropriate cluster size, you can ensure that your Kafka deployment is both cost-effective and capable of meeting your application’s performance requirements.
High availability is critical for applications that require uninterrupted data flow and processing. Our Kafka service is designed to deliver robust fault tolerance and automatic recovery mechanisms to keep your data pipelines resilient.
You can provision a cluster with multiple redundant nodes, ensuring that the failure of a single node does not impact the overall availability of the service. This redundancy is pivotal in maintaining data integrity and continuous service operation.
Our service includes automatic failover capabilities, which promptly redirect traffic to healthy nodes in the event of a failure. This mechanism minimizes downtime and ensures your applications remain unaffected by individual node outages.
You can set the replication factor for your Kafka topics to determine how many copies of each message are stored across different brokers. A higher replication factor enhances fault tolerance by ensuring that even if one or more brokers fail, your data remains available.
Our Kafka service provides extensive configuration options to fine-tune your deployment.
You can configure the number of partitions for each topic, allowing for parallel processing and increasing throughput. More partitions enable better load balancing across consumers, improving the overall performance and scalability of your Kafka cluster.
The retention time determines how long messages are retained in a topic before being discarded. You can adjust the retention time to suit your application's data lifecycle needs, ensuring that data is available for as long as necessary without overwhelming your storage capacity.
Along with retention time, you can set the retention size, which limits the total amount of data stored for a topic. Once the size limit is reached, older messages are purged to make room for new ones. This setting helps manage storage usage and costs effectively.
High Throughput and Low Latency: Kafka is designed for high-throughput, low-latency data streaming, making it suitable for real-time data pipelines and event-driven architectures.
Durability and Reliability: Kafka ensures data durability by replicating messages across multiple brokers, ensuring that data is not lost even in case of broker failures.
Stream Processing: Kafka Streams API allows for real-time stream processing directly within Kafka, enabling complex transformations and aggregations on the fly.
Multi-tenancy: Kafka supports multi-tenancy by isolating different workloads and clients within the same cluster, providing resource quotas and access control.
Log Compaction: Kafka offers log compaction to retain only the latest value for a key, which is useful for scenarios requiring long-term storage of a compacted dataset.
Partitioning and Ordering: Kafka allows data partitioning for parallel processing and maintains the order of messages within a partition, ensuring consistency and ordered delivery.
Upgrades: IONOS Event Streams for Apache Kafka supports user-defined maintenance windows with minimal service disruption. The service ensures seamless upgrades with minimal downtime by adding and removing nodes dynamically.
Easy Configuration: Configure your Kafka clusters quickly and easily with IONOS Event Streams for Apache Kafka. Use the intuitive graphical interface, API commands, or SDKs to create topics, manage brokers, and assign permissions.
High Availability: Kafka's architecture ensures high availability with automatic failover and replication across multiple nodes, minimizing downtime and ensuring continuous data flow.
Security: Secure communication between clients and Kafka brokers using TLS encryption, along with robust authentication and authorization mechanisms, ensures data protection.
Programmatic Resource Management: Easily deploy and manage Kafka clusters in cloud environments using APIs, SDKs, and configuration management tools.
Resources: IONOS Event Streams for Apache Kafka offers dedicated resources, including CPU, storage, and RAM, with SSD storage for optimal performance.
Network: The service supports private LANs, ensuring secure and isolated network communication for your Kafka clusters.
As with our other services, IONOS Event Streams for Apache Kafka is fully integrated into the Data Center Designer and has a dedicated API.
You can provision a robust cluster composed of multiple redundant nodes designed to maintain continuous operation, even in the event of individual node failures. This setup includes automatic failover mechanisms to ensure high availability and minimize downtime. For more comprehensive information on configuring and managing these features, please see our High Availability and Scaling documentation.
Explore the powerful features and benefits of IONOS Event Streams for Apache Kafka. This fully-managed service offers high throughput, low latency, scalability, and robust security features for all your data streaming and real-time analytics needs. Learn more about how IONOS Event Streams for Apache Kafka can transform your data infrastructure in the Features and Benefits page.
IONOS Kafka is suitable for various use cases such as real-time data processing, event-driven architectures, log aggregation, monitoring, and many more where high-throughput, fault tolerance, and real-time streaming data processing are required. Visit our Use Cases section for more information.
The IONOS Event Streams for Apache Kafka service is designed to support the needs of your applications and development cycles. At this time, we support version 3.7.0, ensuring a stable and optimized experience for all users.
IONOS offers a variety of cluster sizes tailored to different application needs, from development to enterprise-level deployments. Each cluster size is designed with specific hardware configurations to ensure optimal performance and capacity. For a detailed breakdown of our cluster sizes and their respective configurations, including node count, cores, RAM, and storage, please refer to our comprehensive Cluster Sizes section.
Our cloud-hosted Kafka service is designed to provide high availability and low-latency access to your data, regardless of where your applications are hosted. We offer Kafka clusters in multiple geographical regions to ensure optimal performance and compliance with local data regulations. The following locations are currently available:
Berlin, Germany (de-txl)
Frankfurt, Germany (de-fra)
Security is a paramount consideration for any cloud-hosted service, and IONOS Event Streams for Kafka offering is designed with multiple layers of security to protect your data and ensure compliance with industry standards. We provide a comprehensive suite of security features to safeguard your Kafka clusters against unauthorized access, data breaches, and other security threats.
Encrypted Communication: Our Kafka service supports Transport Layer Security (TLS) to encrypt data in transit. This ensures that all communication between clients and Kafka brokers, as well as between Kafka brokers themselves, is securely encrypted, preventing eavesdropping and man-in-the-middle attacks.
Beyond encryption, TLS also provides robust authentication mechanisms. By using TLS certificates, we ensure that both the client and server can verify each other's identity, adding an extra layer of security to prevent unauthorized access to your Kafka cluster.