Actual-time information streaming and occasion processing are important elements of recent distributed programs architectures. Apache Kafka has emerged as a number one platform for constructing real-time information pipelines and enabling asynchronous communication between microservices and purposes. Nonetheless, working and managing Kafka clusters at scale will be difficult, requiring specialised experience and vital operational overhead.
Amazon Managed Streaming for Apache Kafka (Amazon MSK) is a totally managed service that lets you construct and run manufacturing Kafka purposes. With Amazon MSK, you possibly can depend on AWS to deal with the heavy lifting of provisioning and managing Kafka clusters, when you deal with constructing revolutionary purposes and real-time information processing pipelines.
On this publish, we discover how Fitch Group, one of many high credit standing corporations, used Amazon MSK and Amazon MSK Replicator to realize multi-Area resiliency for his or her mission-critical Kafka infrastructure.
About Fitch Group and their want for multi-region resiliency
As a number one world monetary info providers supplier, Fitch Group delivers important credit score and threat insights, sturdy information, and dynamic instruments to champion extra environment friendly, clear monetary markets. With staff in over 30 nations, Fitch Group’s tradition of credibility, independence, and transparency is embedded all through its construction, which incorporates Fitch Rankings, one of many world’s high three credit score scores companies, and Fitch Options, a number one supplier of insights, information, and analytics.
To remain aggressive and environment friendly within the fast-paced monetary business, Fitch Group strategically adopted an event-driven microservices structure. On the coronary heart of this ecosystem lies Kafka, particularly Amazon MSK, which serves because the spine for his or her information integration programs.
Fitch Group makes use of Kafka to allow purposes to ship ratings-related enterprise occasions, facilitating automation inside their scores workflow programs and offering real-time or close to real-time processing. This architectural alternative has considerably decreased the time to marketplace for end-user-facing programs like Fitch Rankings Professional and Fitch Group Rankings web sites. Furthermore, Kafka’s sturdy capabilities enable for seamless aggregation and distribution of information from many disparate programs by their information platform, enhancing information consistency, reliability, and accessibility throughout the group.
Given the important position that Kafka performs in Fitch Group structure, offering sturdy catastrophe restoration (DR) mechanisms turned paramount. Any disruption to their Kafka infrastructure might have vital repercussions on their scores workflow automation, real-time processing, and end-user-facing programs, doubtlessly exposing Fitch Group to regulatory, monetary, and reputational dangers.
To realize the specified ranges of resiliency, Fitch Group had the next key necessities:
- Multi-Area deployment – Deploy MSK clusters throughout a number of AWS Areas to offer enterprise continuity and preserve service availability throughout Regional or service occasions
- Automated replication – Replicate Kafka information throughout Areas in close to actual time with minimal latency and information loss
- Constant matter namespaces – Keep the identical Kafka matter names and constructions throughout supply and vacation spot clusters to attenuate utility modifications
- Speedy restoration – Within the occasion of a failover, allow purposes to seamlessly begin consuming from the replicated cluster with minimal Restoration Time Goal (RTO) and Restoration Level Goal (RPO)
Answer overview
Fitch Group selected to implement their multi-Area Kafka deployment utilizing Amazon MSK and MSK Replicator. MSK Replicator is a totally managed replication service that permits steady, automated information replication between MSK clusters throughout the identical Area or throughout totally different Areas. It helps replicating information between clusters with totally different configurations, together with various dealer counts, storage volumes, and Kafka variations. Right here’s how Fitch Group used MSK Replicator to realize their multi-Area resiliency targets:
- Deployed MSK clusters in two separate Areas, with the first cluster in the primary Area and the secondary cluster in a distinct Area for catastrophe restoration
- Configured MSK Replicator to constantly replicate information from the first cluster to the secondary cluster, sustaining the identical matter names and constructions throughout each clusters
- Applied utility failover logic to robotically swap to consuming from the secondary cluster in case of a major cluster unavailability, with minimal restoration time and information loss
The next diagram illustrates this structure
Advantages achieved
By implementing Amazon MSK and MSK Replicator, Fitch Group realized a number of key advantages:
- Enhanced catastrophe restoration – The multi-Area deployment offers enterprise continuity even within the face of Regional or service occasions.
- Simplified operations – The managed functionality of MSK Replicator offloads the operational complexity of self-managing customized replication options, lowering the burden on Fitch Group’s IT workforce
- Scalability – The answer can scale to deal with various information hundreds, ensuring that DR capabilities develop alongside enterprise wants
- Minimal utility modifications – MSK Replicator helps replicating matters with the identical identify, which eliminates the necessity for shopper utility modifications, lowering improvement effort and potential errors
- Seamless failover and failback – Bidirectional replication capabilities allow fast switching of operations to the standby Area with minimal disruption, and simple reversion after the first Area is restored
- Improved testing capabilities – The setup facilitates common DR workouts with out impacting manufacturing programs, permitting Fitch Group to validate their DR plans persistently
Conclusion
Through the use of Amazon MSK and MSK Replicator, Fitch Group has efficiently applied a extremely resilient and scalable Kafka infrastructure that meets their stringent enterprise continuity and catastrophe restoration necessities. This multi-Area deployment allows them to course of mission-critical monetary information at scale whereas offering minimal downtime and information loss within the occasion of service occasions or disasters. As Fitch Group continues to innovate and develop, their sturdy Kafka infrastructure offers a strong basis for future enlargement and the event of recent data-driven providers, in the end enhancing their means to ship well timed and correct monetary insights to their shoppers.
Concerning the authors
Kalyan Janaki is Senior Large Information & Analytics Specialist with Amazon Net Companies. He helps clients architect and construct extremely scalable, performant, and safe cloud-based options on AWS.
Venu Nemallikanti is the Enterprise Architect and Lead for Occasion Streaming at Fitch Group, a globally acknowledged monetary info providers supplier working in over 30 nations. His major tasks embody overseeing the structure and implementation of occasion streaming options, guaranteeing the seamless integration and efficiency of programs that ship credit score scores, analysis, information, and analytics to a worldwide clientele.
Chaitanya Shah is a Principal Technical Account Supervisor with AWS, based mostly out of New York. He likes to code and actively contributes to the AWS options labs to assist clients clear up complicated issues. He offers steering to AWS clients on finest practices for his or her Cloud migrations. He’s additionally specialised in AWS information switch and the info and analytics area.
Oleg Chugaev is a Principal Options Architect and Serverless evangelist with 20+ years in IT, holding a number of AWS certifications. At AWS, he drives clients by their cloud transformation journeys by changing complicated challenges into actionable roadmaps for each technical and enterprise audiences.
