Don’t Let Apache Kafka on Kubernetes Cost You Your Job
By AutoMQ InfoQ
TL;DR: Apache Kafka is not a KubernetesNative data infrastructure. While Kubernetes, as the epitome of cloud-native technology, significantly enhances enterprise efficiency in resource management and DevOps, it also presents new challenges forapplications running on it. To fully leverage the potential of Kubernetes, its Pods need to be able to migrate and recover quickly between nodes. Apache Kafka, born overa decade ago, was designed for traditional data center (IDC) scenarios. Its integrated architecture of computation and storage faces challenges in the cloud-native era, including insufficient elasticity, inability to fully utilize cloud services, complex operations, and high costs, making it difficult to align well with the cloud-native principles followed by Kubernetes. Using non-Kubernetes Native Kafka services on Kubernetes will put your Kafka production environment at risk, requiring careful maintenance to ensure its availability and performance. A slight oversightcould lead to Kafka failures and potentially cost you your job. AutoMQ [1], a new generation of Kafka built on cloud-native principles, effectively addresses these issues and provides users with Kubernetes Native Kafka services. This article will explore the problems associated with deploying Apache Kafka on Kubernetes and how AutoMQ solves them.
What is AutoMQ?
AutoMQ [1] is a Kafka alternative designed with cloud-native principles in mind. It offers a community edition with open-source code available on GitHub [2], along with SaaS and BYOC commercial versions on the cloud. AutoMQ innovatively redesigns the storage layer of ApacheKafka based on the cloud, achieving a 10x cost reduction and 100x elasticity improvement while maintaining 100% compatibility with Kafka by separating persistence to EBS and S3. It also delivers superior performance compared to Apache Kafka. You can further understand AutoMQ through the following comparison articles:
- AutoMQ vs. Apache Kafka [3]
- AutoMQ vs. WarpStream [4]
- AutoMQ vs. Amazon MSK [5]
What is Kubernetes Native Kafka?
The concept of Kubernetes Native [6] was first introduced by Red Hat’s Quarkus. KubernetesNative is a specialized form of Cloud Native. Kubernetes itself is Cloud Native, fully utilizing cloud-native technologies defined by CNCF, such as containerization, immutable infrastructure, and service mesh. Kubernetes Native programs possess all the advantages of Cloud Native. Furthermore, they emphasize deeper integration with Kubernetes. Kubernetes Native Kafka, therefore,refers to Kafka services that can deeply integrate with Kubernetes to fully leverage all of its advantages.
Kubernetes Native Kafka can fully unleash the following advantages of Kubernetes:
- Enhanced Resource Utilization: Kubernetes provides finer-grained scheduling units (Pods) and powerful resource isolation capabilities. Containerized virtualization technology enables Pods to migrate quickly betweennodes, while resource isolation ensures that Pods on the same node can utilize resources reasonably. Combined with Kubernetes’ powerful orchestration capabilities, resource utilization can be significantly improved.
- Shielding IaaS Layer Differences and Supporting Hybrid Cloud to Avoid Vendor Lock-in: By shielding IaaS layer differences through Kubernetes, enterprises canmore easily adopt hybrid cloud architectures, avoiding vendor lock-in and gaining more bargaining power when purchasing cloud vendor services.
- More Efficient DevOps: By adhering to Kubernetes’ best practices, enterprises can implement immutable infrastructure through IaC, integrate with internal CI/CD processes, utilize GitOps in conjunction with Kubernetes’ built-in operational deployment support, and significantly enhance DevOps efficiency and security.
Why Do We Need Kubernetes Native Kafka?
4.1 Kubernetes Gains Popularity in Large Enterprises
Kubernetes is becoming increasingly popular in large enterprises. For these companies, daily resource consumption represents a significant expense. Deploying all applications toKubernetes can significantly improve resource utilization, achieve unified standardized management, and maximize benefits in DevOps processes. When all applications and data infrastructure within an enterprise run on Kubernetes, from a company strategy perspective, core data infrastructure like Kafka should also run on Kubernetes. AutoMQ service customers, such as JD.com and Great Wall Motors,require Kafka to run on Kubernetes from a group strategy perspective.
4.2 Apache Kafka is Not Kubernetes Native
Apache Kafka, designed for traditional data centers, lacks the necessary features for seamless integration with Kubernetes. Its monolithic architecture, where computation and storage are tightly coupled, hinders its ability to fully leverage Kubernetes’advantages. This leads to challenges such as:
- Limited Elasticity: Apache Kafka’s monolithic architecture makes it difficult to scale horizontally and vertically, impacting its ability to handle fluctuating workloads effectively.
- Inefficient Resource Utilization: The integrated architecture results in inefficient resource utilization, as resources are not allocated dynamically based onactual needs.
- Complex Operations and High Costs: Managing and maintaining Apache Kafka on Kubernetes requires significant effort and expertise, leading to higher operational costs and increased risk of errors.
4.3 AutoMQ: A Kubernetes Native Kafka Solution
AutoMQ, designed with cloud-native principles in mind, addressesthe limitations of Apache Kafka and provides a true Kubernetes Native Kafka solution. Its key features include:
- Cloud-Native Architecture: AutoMQ separates computation and storage, enabling flexible scaling and efficient resource utilization.
- Seamless Kubernetes Integration: AutoMQ integrates seamlessly with Kubernetes, leveraging its features for orchestration,resource management, and fault tolerance.
- Improved Performance and Cost Efficiency: AutoMQ’s cloud-native architecture delivers superior performance and significantly reduces costs compared to Apache Kafka.
Conclusion
Running Apache Kafka on Kubernetes poses significant challenges, potentially leading to operational complexities, performance issues, and increased costs. AutoMQ, as a Kubernetes Native Kafka solution, offers a compelling alternative, providing a seamless and efficient experience. By embracing AutoMQ, enterprises can unlock the full potential of Kubernetes and ensure the reliability and scalability of their Kafka deployments.
【source】https://mp.weixin.qq.com/s/O47IIZ1tZEriqfKznTSXFA
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