Actual-time knowledge streaming and occasion processing are crucial elements of recent distributed techniques architectures. Apache Kafka has emerged as a number one platform for constructing real-time knowledge pipelines and enabling asynchronous communication between microservices and purposes. Nonetheless, operating and managing Kafka clusters at scale may 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 may depend on AWS to deal with the heavy lifting of provisioning and managing Kafka clusters, when you deal with constructing progressive purposes and real-time knowledge processing pipelines.
On this put up, we discover how Fitch Group, one of many prime credit standing firms, 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 data companies supplier, Fitch Group delivers very important credit score and threat insights, sturdy knowledge, and dynamic instruments to champion extra environment friendly, clear monetary markets. With workers in over 30 international locations, Fitch Group’s tradition of credibility, independence, and transparency is embedded all through its construction, which incorporates Fitch Scores, one of many world’s prime three credit score scores businesses, and Fitch Options, a number one supplier of insights, knowledge, 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 knowledge integration techniques.
Fitch Group makes use of Kafka to allow purposes to ship ratings-related enterprise occasions, facilitating automation inside their scores workflow techniques and offering real-time or close to real-time processing. This architectural alternative has considerably lowered the time to marketplace for end-user-facing techniques like Fitch Scores Professional and Fitch Group Scores web sites. Furthermore, Kafka’s sturdy capabilities permit for seamless aggregation and distribution of knowledge from many disparate techniques via their knowledge platform, enhancing knowledge consistency, reliability, and accessibility throughout the group.
Given the crucial position that Kafka performs in Fitch Group structure, offering sturdy catastrophe restoration (DR) mechanisms turned paramount. Any disruption to their Kafka infrastructure may have vital repercussions on their scores workflow automation, real-time processing, and end-user-facing techniques, doubtlessly exposing Fitch Group to regulatory, monetary, and reputational dangers.
To attain 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 knowledge throughout Areas in close to actual time with minimal latency and knowledge loss
- Constant subject namespaces – Preserve the identical Kafka subject names and constructions throughout supply and vacation spot clusters to reduce utility adjustments
- 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 allows steady, automated knowledge replication between MSK clusters inside the similar Area or throughout totally different Areas. It helps replicating knowledge 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 principle Area and the secondary cluster in a unique Area for catastrophe restoration
- Configured MSK Replicator to repeatedly replicate knowledge from the first cluster to the secondary cluster, sustaining the identical subject names and constructions throughout each clusters
- Applied utility failover logic to robotically change to consuming from the secondary cluster in case of a main cluster unavailability, with minimal restoration time and knowledge 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 supplies 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 crew
- Scalability – The answer can scale to deal with various knowledge masses, ensuring that DR capabilities develop alongside enterprise wants
- Minimal utility adjustments – 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 easy reversion after the first Area is restored
- Improved testing capabilities – The setup facilitates common DR workout routines with out impacting manufacturing techniques, permitting Fitch Group to validate their DR plans constantly
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 knowledge at scale whereas offering minimal downtime and knowledge loss within the occasion of service occasions or disasters. As Fitch Group continues to innovate and develop, their sturdy Kafka infrastructure supplies a stable basis for future growth and the event of recent data-driven companies, finally enhancing their capability to ship well timed and correct monetary insights to their purchasers.
In regards to the authors
Kalyan Janaki is Senior Large Knowledge & Analytics Specialist with Amazon Internet Companies. He helps prospects 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 data companies supplier working in over 30 international locations. His main tasks embody overseeing the structure and implementation of occasion streaming options, making certain the seamless integration and efficiency of techniques that ship credit score scores, analysis, knowledge, and analytics to a worldwide clientele.
Chaitanya Shah is a Principal Technical Account Supervisor with AWS, primarily based out of New York. He likes to code and actively contributes to the AWS options labs to assist prospects resolve advanced issues. He supplies steerage to AWS prospects on greatest practices for his or her Cloud migrations. He’s additionally specialised in AWS knowledge switch and the information 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 prospects via their cloud transformation journeys by changing advanced challenges into actionable roadmaps for each technical and enterprise audiences.