Vidhya Arvind

This is a big deal for using AI in production - Claude 3.5 Sonnet and 3 Haiku are now available in more regions. us-west-2 tends to get new AI stuff first, and it is great to see these 2 models now more geographically available. https://lnkd.in/gvQkMQbX

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Today's Topic - Why is Redis so Fast? Redis consistently ranks among the fastest databases available. Several factors contribute to its remarkable speed and performance - 1. 𝐈𝐧-𝐌𝐞𝐦𝐨𝐫𝐲 𝐃𝐚𝐭𝐚 𝐒𝐭𝐨𝐫𝐚𝐠𝐞 Lightning-Fast Access - Redis primarily operates in-memory. - This means data resides in RAM, eliminating the latency of disk reads and writes. - The image clearly demonstrates the significant speed difference between RAM and storage mediums like SSDs or HDDs. Data Persistence Options - While primarily in-memory, Redis offers options for persistence (RDB snapshots, AOF logging) to safeguard data durability. 2. 𝐎𝐩𝐭𝐢𝐦𝐢𝐳𝐞𝐝 𝐃𝐚𝐭𝐚 𝐒𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞𝐬 Efficient Implementation - Redis data structures (strings, lists, hashes, sets, sorted sets) are implemented with highly optimized algorithms and data structures, tailored for specific use cases. - The image showcases how each Redis structure maps to a well-chosen underlying implementation (e.g., ziplists for small lists, skip lists for sorted sets). Minimal Overhead - These specialized structures minimize memory overhead and computational complexity, leading to faster operations. 3. 𝐒𝐢𝐧𝐠𝐥𝐞-𝐓𝐡𝐫𝐞𝐚𝐝𝐞𝐝 𝐀𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐮𝐫𝐞 No Context Switching - Redis uses a single thread for command processing, eliminating the overhead of context switching between multiple threads. Event Loop - The event loop model allows Redis to handle multiple client connections concurrently without the need for multithreading, avoiding the contention and synchronization issues that can arise. 4. 𝐈/𝐎 𝐌𝐮𝐥𝐭𝐢𝐩𝐥𝐞𝐱𝐢𝐧𝐠 (𝐑𝐞𝐝𝐢𝐬 6.0 𝐎𝐧𝐰𝐚𝐫𝐝𝐬) Enhanced Scalability - I/O multiplexing (using the io_uring interface on Linux) further improves Redis' ability to handle many concurrent connections efficiently. - The image depicts how this mechanism enables a single thread to manage multiple client connections simultaneously. Networking Performance - Redis leverages various networking optimizations (e.g., TCP backlog, SO_REUSEPORT) to enhance network throughput. Minimalistic Design - Redis focuses on core features and avoids unnecessary bloat, resulting in a lean and efficient codebase. Connect/Follow - Pallavi Ghanshani

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For all customers using Amazon OpenSearch Service remember that enabling concurrent search on segments may get you a considerable reduction on search latency. Let's do some searches! #aws #analytics https://lnkd.in/dZCg3jGY

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One of my fav blog of the year. Prime Day by AWS numbers. Aurora: Processed over 376 Billion transactions spread over 6,311 database instances running the PostgreSQL-compatible and MySQL-compatible editions of Amazon Aurora. ElastiCache: Served more than a quadrillion requests in a single day. Peak of over 1 trillion requests per minute. EC2: 80,000 AI chips (Tranium and Inferentia) and 250,000 AWS Graviton chips powered Amazon.com services. SageMaker – SageMaker processed more than 145 Billion inference requests during Prime Day. EBS: Provisioned 264 PiB of storage, a 62% increase from 2023. Amazon.com performance on Amazon EBS jumped by 5.6 Trillion read/write I/O operations during the event, or an increase of 64 percent compared to 2023. DynamoDB: Handled tens of trillions of API calls, peaking at 146 Million requests per second. https://lnkd.in/g6bTtPbm

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🚀 AWS now supports L40S GPUs in EC2. 🚀 It's hard to overstate how much of a game changer this is for organizations looking to adopt Small Language Models (SLMs) in their VPCs. With FP8, L40S can provide higher throughput and lower latency than A100s, and can be rented per hour for a fraction of the cost: $1.86 / hour for 1x L40S vs $32.77 / hour for 8x A100s (EC2 doesn't offer single A100s, so you need to rent 8 at a time -- if you can even find any capacity). If you're looking to migrate off OpenAI onto SLMs in your VPC, come talk to us at Predibase. We deploy our batteries-included platform for fine-tuning and serving SLMs securely into your VPC -- no data ever leaves your environment. Keep your data and models in your private cloud, and let us handle the SLA. Check out the full AWS announcement here: https://lnkd.in/grKYXu9S And get started with Predibase for free here: https://lnkd.in/ghiV48Tw

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Learn the ins and outs of data latency with this expert guide from Oracle. https://lnkd.in/gnQJdJgS

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Here's a practical example of how Formal Methods can make code faster: AWS's new proven-correct authorization engine is 65% faster (even at p99.9) than the previous version. https://lnkd.in/gVCdurKh Sean says in the talk "we wouldn't have attempted a lot of optimizations we did without this backing of proof". Formal methods allow us to optimize systems more boldly, by removing the risk that optimizations will affect correctness. They also allow our teams to move faster, with lower risk, by building confidence in correctness early on in the software development process.

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We are pleased to announce that you can now achieve up to an aggregate 1.3 million I/O operations per second (IOPS) and 12 GB/s throughput per OCI compute instance with the OCI Block Volume Service. In addition, you can also attach up to 32 Ultra High Performance (UHP) volumes to a single OCI compute instance. This service update is particularly useful for high I/O workloads, such as OLTP, AI/ML, data warehousing and analytics, databases with large data sets and extensive complex processing. https://lnkd.in/gFN8nrtF

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Thrilled to share our latest blog from OCI Data Science Team! In this post, we walk through how we built a state-of-the-art enterprise chatbot using the cutting-edge capabilities of OCI Data Science, Oracle Database 23ai, and Oracle Digital Assistant, backed by LLM models with the LangChain pipeline for RAG. From foundational AI models to creating a seamless conversational experience, this blog covers it all. Special thanks to Piyush Gajjariya (Thacker), Tzvi Keisar, Ashutosh Kumar Jha and SriRanjith R from OCI Data Science. Check it out here: [https://lnkd.in/dAudXG4J] #AI #Chatbots #OCIDatascience #EnterpriseAI #Oracle, #OCI, #oracle_database_23ai, #oda, #langchain, #rag, #LLM

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It's a great time to try out AlloyDB for PostgreSQL for free .. we just launched AlloyDB Free Trial clusters. These clusters let you test the majority of AlloyDB features for up to 30 days through a 8 vCPU basic primary instance along with an optional 8 vCPU read pool instance, and automatically scale storage up to 1TB. #alloydb #postgresql #gcp https://lnkd.in/gvUPjfSk

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For those following the Redis license changes, Valkey, the OSS alternative which forked off from Redis before the license changed is now in preview on Google Cloud. Details on the cloud blog below. I've noticed that Google Cloud specifically has taken an pretty strong view to helping people run open source stuff on their cloud, steering (in general) away from proprietary stuff. They've led from the front with things like cloud storage egress for free when closing an account (which was later adopted by the other clouds) as well as supporting stuff like Kubernetes, Buildpacks for building and running code, and using industry-standard stuff for other parts of their cloud like pub/sub. This announcement is just another way they're bringing OSS tools like Valkey and giving it legs to survive.

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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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Kapil Khangaonkar, CEO of Clodura.AI, shares how Google Cloud fueled their growth: 71% less tech debt, 12x faster app delivery, & significant customer growth. 🚀 Ready to transform your startup? The Google for Startups Cloud Program now offers new benefits for AI startups, giving you the technology and resources to build easily. Take advantage of our open AI ecosystem and tap into the best of Google’s infrastructure, AI products, and foundation models.   Sign up today and unlock your startup's potential! #startups #cloud #GoogleCloud #CloduraAI #techstartup #startuplife #AI #buildwithAI #GoogleAI #GoogleforStartups #GoogleCloudforStartups https://goo.gle/GFSCP_CS Clodura.AI Google for Startups

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How to do iterative development for ML with Dockers on Amazon SageMaker Studio

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