Rooz Mohazzabi

➰ APIContext's latest insights on cloud-based API performance have been featured on Nordic APIs! In the 2024 report, we delve into crucial aspects affecting API efficiency: 🔐 Authentication is key. Ensuring robust authentication mechanisms in APIs is crucial, yet offloading this function can introduce complex challenges. 📖 DNS configurations matter. How you handle DNS settings can significantly impact API performance, particularly when tied to authentication processes. 🌐 The role of third parties. Critical third-party services play a significant role in 🔗 API transactions, underscoring the need for careful integration and monitoring. ⛅ Not all clouds are created equal. Differences in cloud services can drastically affect API performance, an essential consideration as APIs account for over 80% of all internet traffic. #APIs #CloudComputing #TechInsights #APIContext

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AWS re:Invent is less than two weeks away. Want to accelerate your AI initiatives? Let's connect in Vegas and discuss how Meibel enables your engineering team to build Explainable AI into your products and experiences.

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Worth reading: How the Apache Arrow Format Accelerates Query Result Transfer by Ian Cook One of the hidden problems of intersystem communication is transcription of data formats. Ian does a wonderful job of explaining the "why" of Apache Arrow as well as the "how" of its advantages. Read on...

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The Site Reliability Engineering: How Google Runs Production System book is arguably one of the most prevalent and well-known SRE resources out there, but there are many other great options for folks looking to expand on their learning. We recently spoke to Google's Reliability Advocate, Steve McGhee, in our Humans of Reliability interview series. In addition to his interesting anecdotes on the early days of SRE at Google, and his journey to becoming a Reliability Advocate, he also shared a handful of his favorite SRE resources, which we compiled here into a list: https://lnkd.in/gpUVhyRa

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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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The shift from traditional ML to LLMs has pushed infrastructure requirements to new limits. At neptune.ai, we’re tackling these challenges by focusing on: → Scalable infrastructure, built to handle high-speed data ingestion and processing. → Real-time data display, adapting seamlessly to complex and large volumes. → Consistent UX quality, even under intense backend demands. — (link to the full interview in the comments) #generativeai #genai #llm

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🌟 From Raw Data to Behavioral Predictions—Effortlessly What if AI deployment didn’t require months of preparation? With BaseModel.ai now on the Snowflake Marketplace, you can transform behavioral data into predictions in just a few clicks. ✅ Rapid Deployment: Build and deploy models in a week.  ✅ Scalable Flexibility: Create multiple models for diverse use cases.  ✅ Privacy Guaranteed: Data never leaves the secure Snowflake environment. Say goodbye to complexity and hello to actionable insights. AI for behavioral data has never been this simple. 👉 Try BaseModel.ai Today  #AI #MachineLearning #BehavioralData #BaseModel #Snowflake #Synerise 

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Just a few weeks after the GA release of Arm64 runners, we’re already seeing our clients achieve noticeable reductions in build times and lower runtime costs. If you're looking to scale your CI/CD operations and accelerate feedback loops, now is the time to explore the benefits of Arm64! Key takeaways: - ⚡ Faster build times to streamline development. - 💰 Cost savings through optimized runtimes. Ready to take your CI/CD to the next level? #CI/CD #Arm64 #DevOps #BuildOptimization #CostEfficiency #ContinuousIntegration target: https://lnkd.in/gY-_n6JJ

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💥 Nice preInvent announcement from DynamoDB -- the ability to pre-warm the max throughput on your table. Previously, you'd have to briefly set your table to provisioned mode with high throughput (see Yan Cui's article on this), but now you can do it yourself with an API call. Be careful on oversizing though! You'll see the impact of this if using DDB Streams -- lots of small / empty batches. And if you're not consuming from Lambda, that will be more expensive. https://lnkd.in/dHV-q3zc

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Seismic’s AI enablement assistant, Aura Copilot, is now available for early access. Teams can now get faster access to answers and content, automate tedious tasks, and gain insights for better business decisions. Aura also now integrates with Microsoft Teams and Microsoft 365 Copilot to give teams in-the-moment answers and content recommendation. https://lnkd.in/d_mSbDXK

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This is the initial infrastructure Tradescoop was built on. A few things have changed, some additions and removals; for example, we’ve gone from MongoDB on Digital Ocean to Mongo Atlas, Redis cloud to Memorystore, but the general appraoch remains. Simplicity. Shouts to Karl Obinna Amalu, CSM for cleaning it up and adding color ✨ #gcp #infrastructure #devops

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🚀 Follow along this week as we highlight some of the features we shipped over the past quarter! Up first: Anyscale Replica Compaction. Anyscale’s Replica Compaction optimizes resource scheduling in Ray Serve, solving resource fragmentation and enhancing efficiency. Why it matters:  Resource fragmentation happens when scaling leads to uneven utilization across nodes. As traffic decreases, previously needed nodes become underutilized, leading to increased cost and poor efficiency. Ray Serve scales each model independently, leading to this issue. Solution: Replica Compaction automatically migrates replicas into fewer nodes, optimizing resource use and reducing costs with zero downtime. Results: On an Anyscale Service with multiple LLMs (Mistral, Mixtral, Llama3), efficiency increased by 10.7% (measured by Tokens / GPU Second).  We found instance seconds declined by 3.7% despite an 11.2% traffic increase. Learn more in our blog: https://lnkd.in/e5WjVSFH Get started today: https://bit.ly/3Y6qHrx

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🚀 Get ready for another Tech Deep Dive! Come learn how to integrate Apache Kafka with RisingWave from Emily L. on August 22! 💻✨ Emily will showcase how RisingWave handles data streams with Kafka topics, finishing with a live demo. 🎫 Don’t miss out—grab your spot here: https://lnkd.in/g6NJF3EP #risingwave #kafka #apachekafka #dataprocessing #streamprocessing

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GraphQL makes your APIs better. The days of #GraphQL vs #REST are over, now it is all about how both technologies can work together to deliver value to your end users and customers as part of cohesive #API strategy. They can exist side by side and enable each other. I’m genuinely excited about what Apollo GraphQL and our product roadmap will be delivering to show the world just what is possible! Check out this great interview with Matt DeBergalis by Intuit Open Source and hear his thoughts on how the the two technologies can build on each other 👇🏻 #EnterpriseArchitecture #PlatformEngineering

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Want to hear from Intuit on how they are using AI? Avni Sharma and Todd Ekenstam are presenting at KubeCrash on October 9th! Intuit’s AI-Native Platform: Simplifying Kubernetes for Developers After running 3,000+ microservices and monoliths on Kubernetes for the last four years, Intuit is building its next-generation AI-native paved-road platform that will enable its developers to define app intent, and the platform will take care of the rest, thereby alleviating the developers from the K8s cognitive overload. We will share our end-user perspective on using Kubernetes and why abstracting networking and compute infrastructure and utilizing AI-powered application autoscaling will enable developers to focus more on what they excel at: writing code. This improves platform maturity and provides developers with an internal developer platform to deliver a delightful developer experience. Attending this talk will teach you how open-source projects, such as Open Application Model, Istio, Karpenter, Argo Rollouts, and Numalogic/Numaflow, can be integrated and extended to build your AI-native application platform, thereby paving a path for increasing our developer velocity by 25%. Don't miss the free, virtual event focused on cloud native / platform engineering! kubecrash.io

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Exciting news for teams leveraging monorepos! Coherence now supports glob patterns for selective build configuration, bringing unprecedented efficiency to your development pipeline. 🔧 Technical Highlights: • Granular control over build and deploy processes • Intelligent file change detection • Seamless integration with existing CI/CD workflows 💡 Key Advantages: 1. Dramatic reduction in build and deploy times 2. Optimized resource allocation 3. Precision targeting of updates for changed code only 🏗️ Real-world Impact: • Accelerated development cycles • Enhanced productivity for large-scale projects • Significant cost savings on computational resources This feature empowers you to fine-tune your build process, ensuring only necessary services are built and deployed based on actual code changes. It's a game-changer for maintaining velocity in complex, multi-service architectures. Ready to supercharge your monorepo? Dive into our comprehensive documentation to implement selective builds and experience the future of efficient development.

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💥 We recently announced Temporal Nexus - the feature that connects durable executions across team, namespace, region, and cloud boundaries. Nexus endpoints are API proxies for Nexus services that abstract Temporal primitives like Workflows for seamless integration and collaboration across teams 🤝 
 
Benefits for developers: - Familiar API programming model that supports both sync and async patterns for connecting durable executions using existing queue-based Workers. - Modular architecture that allows teams to independently develop, scale, and maintain parts of an application with clear API contracts backed by robust Nexus machinery. - Enhanced security, troubleshooting, and fault isolation that reduces the risk of misbehaving workers, since each team can run their workflows in separate namespaces. Use the Temporal SDK to add Nexus services to your existing workers with clean API contracts for others to use. Read more: http://temporal.io/nexus

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Something that stuck with me during my interview with Naveen Rao, VP of Generative AI at Databricks: "I take the hard path." He built an AI-focused chip company Nervana in 2014 when machine learning was still academic theory and the chip industry was deeply out of favor. Naveen saw computing architecture would need to fundamentally change for ML workloads. And then in 2019, observing the power of LLMs like BERT, Naveen foresaw the need for enterprise-grade services to manage their training, deployment, and customization. That vision led to a $1.3B acquisition by Databricks in 2023. What I love about Naveen's approach is his willingness to build for markets that don't exist yet. "There isn't a market, employees don't even know about it. So how the hell do you build a company?" You educate. You convince. You get people to see what you see. It's brutal work, but it's important work. You're reshaping how people think about problems.

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How @IronMountain built its InSight DXP on @MongoDB https://buff.ly/3zD1gUu We caught up with Adam Williams, Vice President of Global Platforms at Iron Mountain, to talk about use of MongoDB and scaling. Here's a look at some of the key takeaways.

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