Mark Cusack

A really nice read from Sai Maddali on the benefits of Tiered Storage with Amazon MSK. https://lnkd.in/gGNJ5nyt #ApacheKafka #Kafka #AWS #MSK #tieredstorage #streaming #storage

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What is Trino? Why might Trino be the future of data lakehouse compute? Check out this blog from Starburst's Evan Smith to learn all things Trino from definition to use case: https://okt.to/aM8hKz #trinodb #queryengine #DataLakehouse

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The speed at which these models improve is staggering, so is the cost to build them. Only way to keep up is to leverage principles such as AWS Bedrock so you have the flexibility you need to quickly select the model that works best for your task. https://lnkd.in/gNAR63YC https://lnkd.in/g_FtP6e9

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Truth. This blog articulates the shortcomings of most tiered storage solutions in delivering predictable performance at scale. Without some rebuild that harnesses cloud primitives like AWS S3 and GCP GCS, mere incremental adjustments to existing products won't adequately serve users. From a product manager's perspective, sometimes incremental adjustments isn't a path to sustainable product adoption and success.

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I love this quote from Prefect’s most recent case study: “This streamlined migration process enabled the teams to collectively build an additional 78 pipelines within a single quarter, each tailored to unique compute resource requirements—an efficiency that would have been unattainable with Astronomer… Switching from Astronomer to Prefect resulted in a 73.78% reduction in invoice costs alone.” Orchestration is the automation of *when* and *where* code should run, and a good orchestrator should allow you to configure *where* in a resource efficient manner. Read more here: https://lnkd.in/gFCSxGvh

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Aggregation policy in #Snowflake makes it very simple to prevent inadvertent exposure of identifiable sensitive data to users who just need aggregated information. Check out this blog highlighting the value of this feature using HR data as an example. https://lnkd.in/ewpQdrbx

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🤔 Unlock revenue tied to data streaming or keep your focus on the rest of your roadmap? Good news: that’s a choice you no longer need to make—the Confluent OEM Program is here to empower you to do both! MSPs, CSPs, and ISVs, don’t miss out—learn more about the program on our blog!

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Incredibly proud of the latest Kinesis Client Library version (3.0) which, when compared to previous KCL versions, reduces compute costs by up to 33%. KCL 3.0 introduces an enhanced load balancing algorithm that continuously monitors resource utilization of the stream processing workers and automatically redistributes the load from over-utilized workers to other underutilized workers. This ensures even CPU utilization across workers and removes the need to over-provision the stream processing compute workers which reduces cost. Additionally, KCL 3.0 is built with the AWS SDK for Java 2.x for improved performance and security features, fully removing the dependency on the AWS SDK for Java 1.x. #Kinesis #DataStreaming #KCL

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The Kubernetes ecosystem may get too complicated for its own good. Picking stack components has become a top Kubernetes pain point! You can learn more from this new survey by Spectro Cloud. #openshift #aro #rosa #osd #rhoic https://lnkd.in/g8T88f4a

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Discover how scalar quantization can be used to reduce the memory footprint of vector embeddings in Elasticsearch: https://gag.gl/tVVrxQ #ElasticSearchLabs #ML #Elasticsearch

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In case you missed it, we have now released the second issue of our Confluent Chronicles – a fun and entertaining take on the fundamentals of stream processing, Apache Flink, and Confluent! We had such great feedback on the first issue that we couldn’t just stop there – you can check out and download the latest edition here: https://lnkd.in/gEFxA7af Would love to hear what you think of it!   #ApacheFlink #ApacheKafka #Confluent

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Are you curious how #ApacheKafka is different from #messageBroker? Do you like to learn from a video? Look no further - Kai will walk you through how they compare. #datastreaming #confluent

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#MySQL 8 with the SYS Schema provides real-time insights into buffer pool activity, data I/O, and transaction logs. Monitoring these metrics helps identify bottlenecks, optimize configurations, and enhance database performance and availability. #MySQLPerformance @MinervaDB #dba https://zurl.co/X0wb

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Justin McCarthy answers all. In this segment, he covers: ☑️ Managing Resource and Role Explosion in Complex Enterprises ☑️ Scaling Authorization for Dynamic Workloads ☑️ Tools for Auditing and Improving PAM Systems ☑️ Balancing Complexity in Authorization with Ease of Management ☑️ Addressing User Lifecycles in a PAM Environment Tune in!

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#API Management is often thought in terms of one direction: ingress. Managing API traffic whether ingress, east-west, or egress happens very inconsistently in most organizations. I'll be in #Boston next week for the #Kubernetes #Meetup to discuss omni-directional API management, API gateways, and service mesh, and how organizations should adopt a strategy that strives for consistent, secure, and observable API connectivity in #AllDirections not just #OneDirection. https://lnkd.in/dy6KQAgj

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Elasticsearch open inference API adds support for OpenAI chat completions. Learn more in this blog post: https://gag.gl/hEDnXw #ElasticSearchLabs #OpenAI

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