Amazon Managed Streaming for Kafka is a fully managed service that facilitates organizations to build and run applications that process streaming data. With Amazon MSK, you can boost your productivity and uptime by continuously alerting and monitoring your infrastructure operations. As businesses realize the need to shift from monitoring metrics to performance and business outcomes, the ability to connect the data source and extract data in real-time is critical.
Besides, digital transformation is continually rising, meaning that organizations with on-demand infrastructure and high availability will gain a competitive advantage. Amazon MSK can help your company get real-time statistics of its infrastructure and make quicker, more informed decisions. However, the transition to Amazon MSK is not always a breeze.
Common Challenges with the On-Premises Apache Kafka
Apache Kafka offers an optimized, distributed data storage solution for the effective processing and consumption of streaming data. It allows you to implement data pipelines with real-time streaming and seamless processing of events. Unfortunately, Apache Kafka has a myriad of challenges when deployed on-premises.
Your organizations may also face significant difficulties with scalability when workloads begin to expand. Additionally, achieving high availability and disaster recovery is challenging with on-premises infrastructure, not to mention the need for extra administration efforts. You’ll also need specialized skills to manage the on-premises Apache Kafka clusters. Such maintenance costs can easily eat into your bottom line in the long term.
When evaluating possible migration options, your focus should be on balancing the business impact that the migration process would cause vs. experiencing potential disruptions by rushing through the migration process. Depending on your kind of content and existing regulatory frameworks, you may need to handle the migration diligently to avoid regulatory, monetary, and reputational risks.
Additionally, if your business runs 24/7, you may only have a finite, planned downtime window. Any migration option you opt for must satisfy completion within the set window. To achieve that, here are two migration approaches to consider:
The first option is to switch all your services at one go to point to Amazon MSK. This will perform an atomic cutover of all Apache Kafka-dependent solutions to point to Amazon MSK at once. However, you’ll need to plan a maintenance window with stringent downtime to ensure that services don’t actively process requests during the cutover period.
With this approach, you only switch specific services to point to Amazon MSK. It means that only a specific subset of services will begin using Amazon MSK as the entire application functions in a hybrid model. Only the migrated services connect to Amazon MSK, while others continue to run on on-premises Apache Kafka.
Option 1 seems to work best for most businesses, provided you can complete the migration process within the stipulated planned downtime window. Although migrating all your services at one go is the cleanest option, you can also explore option 2 for your service migration.
Best Practices for Migrating Apache Kafka to Amazon MSK
If you’re looking for a reliable implementation option for Apache Kafka, the Amazon MSK is a great option, particularly for a long-term approach. It can help your business achieve fast scalability and flexibility while improving the utilization of cluster resources. Additionally, Amazon MSK can help your organization realize cost optimization. Since it’s a fully managed service, migrating to Amazon MSK eliminates the need for infrastructure management and maintenance.
However, there are some important considerations to take into account while migrating Apache Kafka to Amazon MSK. The best practices for migrating Apache Kafka to Amazon MSK include:
- Performing cluster sizing before migrating your services to Amazon MSK
- Adhering to the cluster sizing guidelines
- Migrating each Apache Kafka topic individually and validating the data after every migration
- Building highly available clusters to avoid any downtime
- Writing logs to CloudWatch and S3 to ensure data validations during the primary phases of migration
- Enabling low and granular monitoring for every broker and topic
- Ensuring that the Apache Kafka clusters are right-sized
Additionally, you need to give thorough attention while choosing the number of partitions per topic. Be sure to set the CloudWatch alarms on disk utilization to ensure proper validation during the migration. Besides, building highly available clusters ensures faster provisioning of resources to running updates, particularly for upscaling.
It’s also good practice to remove the unused Kafka topics to avoid exhausting the storage space. Set the retention period only to the time duration required for the migration and enable encryption for data in transit to enhance security. In addition, establish auto-scaling policies for automatic upgrading of the cluster’s storage to accommodate any workload hikes.
After migrating to Amazon MSK, your organization can continue using its native Kafka APIs since no major code changes are needed.
Benefits of Migrating to Amazon MSK
Migrating your workload from Apache Kafka to Amazon MSK offers a myriad of benefits, including:
- Managed content streaming
- Fully managed workloads
- High availability of clusters with just a few clicks
- Automatic management and provisioning of clusters
- Effort reduction, enabling you to direct resources to business development
- Highly secured clusters and encryption to ensure security for data at rest and on transit
- Multi-AZ replication
- Open-source compatibility
If your organization still depends on Apache Kafka, you could be wasting a lot of time taking care of the system instead of focusing on delivering business value. Amazon MSK enables you to be more productive by minimizing the time you spend on maintaining your infrastructure, diagnosing, and fixing issues, and maintaining your brokers. In addition, it handles Apache Kafka maintenance protocols in the background, giving you the level of monitoring you need while freeing up your team to handle more activities to enhance your applications and provide real value to your customers.
At Agilisium, we specialize in Big Data and Analytics to help businesses take the “Data-to-Insights-Leap.” We are an AWS Advanced Consulting Partner with EMR, Redshift, QuickSight, and DevOps competencies. Additionally, we have invested in all stages of the data journey, including Data Architecture, Consulting, Integration, Storage, Governance, and Analytics. With a thriving Partner Eco-system, advanced Design Thinking capabilities, and top-notch industry certifications, Agilisium is fully vested in your business success. Contact us today to schedule your consultation!
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