Ali Kazeroonian

Scaling up Kafka and making sure it's performing at its utmost efficiency is a holy grail for enterprise software architecture. Kafka is designed for infinite scale but only if you design and adapt the right Cluster configuration based on your growing needs. These are a few metrics to watch out for.

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Customers often ask if Amazon Q Developer is only for Amazon Web Services (AWS) workloads. The short answer is no. Our developer platform can add value to your on-premises development and multi-cloud needs, regardless of your platform. Our partners at Heroku have a great use case for this. Check out their blog post on how the Amazon Q Developer / Heroku integration simplifies their customer workflows.

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Amazon SES feedback events can now be sent to EventBridge 🌟 🚀 This is such a cool and convenient feature and was on the AWS wishlist for a long time 👏 If you worked with SES, you know the struggle filtering from the dozen or so feedback events you can receive for every email sent to Firehose or SNS. The EventBridge option now makes it easy to have filters for the different types of events and perform downstream analytics and suppression lists. https://lnkd.in/eineVREt #AWS #serverless #SES #email #EventBridge #eventdriven

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🚀 Exciting News Db2 Users! 🚀 ⌚ Amazon Web Services (AWS) has introduced local time zone support for Amazon RDS Db2! 🕒 This innovative solution enables Db2 users to seamlessly manage their databases with time zone flexibility. 💨 At AWS, we're committed to delivering unparalleled reliability, scalability, and convenience to our customers. The addition of local time zone support for Amazon RDS Db2 is just one more way we're achieving that goal. 👏 This game-changing feature is now available, and we invite you to learn more about how it can elevate your database management experience. Check it out here: https://lnkd.in/gtws8a7A Billy L. Sindhu Simhadri Rajib Sarkar #AWS #AmazonRDS #DB2 #DatabaseManagement #Innovation #CloudComputing #TechNews #AWSUpdates

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For anyone involved in large-scale data processing, particularly those considering Apache Flink or Google Cloud Dataflow. The article gives guideline on how to setup a fair benchmark consideration as well as potential optimization that can be done on the pipeline: Real-world Benchmark: It offers a practical, real-world benchmark study conducted by Yahoo, providing valuable insights into the cost and performance of these platforms under specific use cases. This can help organizations make informed decisions about their technology stack. Fair Comparison Methodology: The blog post outlines the methodology used to ensure a fair comparison between Flink and Dataflow, emphasizing the importance of controlling variables and establishing a consistent testing environment. This level of rigor adds credibility to the findings. Cost Optimization Focus: It focuses on cost-effectiveness, a critical factor for businesses. The post helps readers understand how to minimize costs on both platforms.

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The savings of Valkey based ElastiCache are too good to ignore. Considering that every single AWS customer has a cache of some sort, the discount will drive adoption and migration.

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Substack recently moved their ML and AI pipelines over to Modal, from AWS SageMaker. We've had a lot of fun working with them and we just wrote about it on our blog. “Using SageMaker just felt like a very convoluted process. It felt very removed from a normal engineering workflow. With Modal, it’s a lot faster. You don’t feel like you have to wait for notebooks to spin up or remember to turn them off or any of that type of stuff.” – quote from Mike Cohen, Head of AI & ML Engineering at Substack In the process, we actually made several improvements to Modal's system latency, since Substack's use case is very latency-sensitive. These optimizations now benefit all Modal users. Take a look: https://lnkd.in/e8yMCiti

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Amazon RDS Extended Support APIs are now available After the RDS end of standard support date has passed, you can prevent the creation of a new DB instance or a new Multi-AZ DB cluster and avoid RDS Extended Support charges. In the AWS CLI, specify open-source-rds-extended-support-disabled for the --engine-lifecycle-support option.   https://lnkd.in/gi_uX9xZ #Amazon #RDS #PostgreSQL #MySQL #Aurora

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https://lnkd.in/gcJsEKrG Q. What happens when #neural #networks are applied to fields like #Physics? A. In short, a Nobel Prize. More broadly, neural networks, built on the laureates' foundational work, have wide-ranging applications across science, technology, and various industries. They excel at tasks like pattern recognition, classification, and data generation. #Physics #AI #HVSays

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In collaboration with AWS, we are thrilled to announce the Confluent blueprint for Amazon OpenSearch Ingestion! This serverless feature enables customers to effortlessly transfer data from Confluent to OpenSearch Domains or OpenSearch Serverless collections. This capability unlocks numerous new use cases, such as Retrieval-Augmented Generation (RAG), real-time log analytics, and more. Read the full announcement, including a complete example of setting up a Confluent/OpenSearch pipeline using the new blueprint (with optional use of Schema Registry), here ➡️

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Microservices get a bad rap due to complexity and high TCO. A lot of that is because a microservice-based application works the same way as a bunch of dominoes falling. If one misses, or falls out of order, the whole workflow stops. And you have no control over the process once your microservices start ping-ponging events and RPC's back and forth. That's why #microservices are so expensive to manage. Great blog post below by Colt McNealy about how LittleHorse can solve those problems. Give it a read. https://lnkd.in/gJECBwRu

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pgvectorscale: A Game-Changer for Vector Similarity Search 🚀 Timescale's #pgvectorscale extension for PostgreSQL has achieved a remarkable milestone, matching the performance of Pinecone, a dedicated vector database, while being 75% more cost-effective. 💰 In their latest blog post, Timescale showcases the impressive speed and efficiency of pgvectorscale, which leverages the power of PostgreSQL to deliver lightning-fast vector similarity search. This breakthrough opens up new possibilities for applications like semantic search, recommendation systems, and more. 🔍 Key takeaways: 🌟 pgvectorscale now matches Pinecone's performance in vector similarity search 💸 pgvectorscale is 75% more cost-effective compared to Pinecone 🔧 Easy integration with existing PostgreSQL databases 🌐 Scalable solution for handling billions of vectors ⚡ Optimized for fast and efficient search results pgvectorscale's seamless integration with PostgreSQL allows developers to incorporate vector similarity search into their applications with ease, while benefiting from the robustness and scalability of a proven database system. 🗄️ If you're looking for a high-performance, cost-effective solution for vector similarity search, pgvectorscale is definitely worth exploring. 🔍💡 #pgvectorscale #postgresql #vectorsimilaritysearch #semanticsearch #recommendationsystems #timescale https://lnkd.in/gsfgCK32

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For those interested in how cloud scale database systems work, below is a deep dive on Amazon MemoryDB. MemoryDB delivers microsecond-level read latencies, and throughput in the hundreds of millions of queries per second, while offering multi-AZ durability with automatic failover.

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When you need to play with your data in Gen Ai, you need RAG and Chunking is one of the main component in the RAG framework while consuming or processing your data. Excellent post below describing how in different ways chunking in RAG can be implemented..

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The new bytewax-redis module allows you to seamlessly integrate Redis streams and key-value stores into your Bytewax dataflows. Whether you're consuming data from Redis streams, writing processed data back to them, or interacting with Redis' key-value storage, bytewax-redis has you covered. cc: Zander Matheson

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Amazon RDS for PostgreSQL announces Extended Support minor 11.22-RDS.20240418 We recommend that you upgrade to this version to fix known security vulnerabilities and bugs in prior versions of PostgreSQL 11 https://lnkd.in/eF2ixv9f #Amazon #RDS #PostgreSQL

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