Shaunak Godbole

Gwen (Chen) Shapira talks about Nile’s architecture in this amazing podcast from Kaivalya Apte. Things we have built and things we plan to build. Lots of details Why Postgres? How tenant isolation works? How is compute isolated? How is storage isolated? What parts of Postgres are reused? Can multiple tenants exist in a single transaction context? https://lnkd.in/ehH5J2e3

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Recently Haytham Abuelfutuh presented about Batch Workloads and how Union and Flyte are used for Large scale batch and near realtime workloads. Check out this post to 1. Learn about the challenges in using Kubernetes for running Batch workloads 2. The problems in the programming model with Batch workloads. Often times its not a single job - but it may start with one 3. The simplification that can be introduced by using Union. Union runs them across multiple clouds, multiple kubernetes clusters, securely accessing large amounts of data, while maintaining efficiency through - caching, smart techniques in which container state is saved, how pods are used, how back pressure is maintained etc. Check out the blog.

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Hey everyone, I am an investor and advisor to Katanemo.... They are reinventing the infrastructure primitives for GenAI and launched Arch - https://lnkd.in/gCrbbkEV - an intelligent prompt gateway. Give the project a look on Github, and star the project if it resonates

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An eye-opening piece on the "Observability Cost Crisis" by bitdrifts Matt Klein. It suggests a major shift in how we handle logging, metrics, and traces to curb the spiraling costs. The idea? . . . . . . . . . . . . Default to storing no telemetry data unless specifically identified as needed on the fly. While this sounds radical, the argument is that recent advancements in infrastructure AI/ML can make it a reality. #CloudEngineering #Infrastructure #Observability #SaaS #CostEfficiency

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This is a great paper from the Confluent team for those interested in building large-scale, cloud-native platforms. It's rare to see this level of detail shared by cloud providers. https://lnkd.in/eGYJ-NZz #kora #korapaper #confluent

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One of the challenges with #kubernetes workloads is pod startup times. This gets exacerbated at scale. This blog post from Maya Aravot from Riskified goes in detail how Volume Snapshots can be leveraged to improve pod startup times by 83%. It also contains the detailed steps how it should be implemented. Good read. #kubernetes #security #cloudsecurity #ekssecurity #awssecurity At Cloudanix, we offer realtime monitoring of Kubernetes Clusters from a Security standpoint and also monitor for Pod failures at scale. https://lnkd.in/gyfUbjDW

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Ever wonder why some companies can ship software at lightning speeds while others seem stuck in the mud? 🚀⏳ . . . . . . . . . Daksh Gupta of Greptile collected real-world insights from engineers at many of the world's largest tech companies, unpacking the intricacies that either propel or impede the speed of shipping code. The big reveal? Older and larger companies tend to move more slowly because the costs of missteps become greater. In some cases, those costs are fairly non-negotiable (e.g. ensuring software for customers in production remains secure) while in other cases, the costs are more optional and cultural (e.g. wanting a lot of accurate estimates, forcing a manager's vs. maker's schedule, etc). #SoftwareEngineering #Tech #DevelopmentVelocity #Innovation #Productivity

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I just got off a call with a large client POC ( Annual rev - $90B) for Akto’s platform integration. Here's why I am excited: We used our Kubernetes DaemonSet integration for API Discovery. I was expecting it to take 1-2 calls of 1 hour each given the complex architecture of the client. We are talking about a Fortune 500! To give context: 1 year ago, these integrations used to take 1-2 weeks because of the 100+ unknowns, variables, and complexity involved. BUT... Today, it took Akto only 14 minutes to complete end-to-end implementation with APIs starting to be discovered in the dashboard. BOOM!! 1000 APIs discovered in next 10 mins. LFG Complex env? Bring it on!

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Is your observability bill out of control? Are you wasting engineering time trying to justify the cost? There's a better solution… https://hubs.la/Q02PsJZM0 #kubernetes #devops #cloud #observability

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Managing production software, and especially "root causing" issues, whether at the infra or app layer, continues to be a growing challenge despite the success of companies like Datadog. I have looked at applying deep learning to this problem since 2017 when we worked with Gurashish Brar & Mohit Gupta to incubate Opas.ai. The team was exceptional, and they even hired a great SDR (me 😜 ). We learnt the hard way that it was too early and #AI was just not ready. A lot has changed since in terms of data infrastructure (check out Conviva's Operational Data Platform), causal inference models and LLMs. Jaya Gupta and I are excited to take another whack at this market, which we call #AgentSRE to distinguish from the outdated #AIOps framing. If you are building an #AgentSRE company, ping us. https://lnkd.in/gvBgfN7k

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Large Language Models (#LLMs) are evolving rapidly, and the demand for running them at scale is skyrocketing. #Ollama is stepping up to meet this need with its official container image on Docker Hub, excelling in local #deployments. However, there’s a catch for containerized environments: downloading #models requires the ollama serve command to be running within the #container. This extra step complicates automated deployments via #CI #CD #pipelines, making seamless model access challenging. To take your #model to production, it needs to be #container-ready—a feature Ollama has yet to fully support. The gap in #AIOps for smooth deployments gets blurred with the inference services available as an easy way to take it to production. Goal is to overcome obstacles and deliver solutions 😉 so here is to get you started on having your (O)#llama #production ready in a private #deployment from your #local to #cloud all in #oneshot . Enjoy Medium: https://lnkd.in/g9jqBQ8d dev.to: https://lnkd.in/gi_gGwam #AI #LLM #Ollama #llama3 #phi3 #mistral #S6overlay #AIOps #CI #CD #oneshot #container #docker #podmanEnjoy

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I endorse this message, and also send the spirit of the same to the Apple Siri team, with perhaps several more exclamation marks and "WTF"'s appended. To carry forward with poor version of an old school SAT analogy question based on Dharmesh's set up: If ChatGPT makes Alexa seem antiquated by pre-2022 standards Then Siri ________ I invite you to fill in the blank.

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🌟 Tune in to our latest episode with Jacob Moshenko! 🎧 From his groundbreaking work at Amazon and Google to founding AuthZed, Jake shares his journey and the challenges of leading in the open-source world. We discuss: 🗣️ Distributed systems 🗣️ The fear of failure 🗣️ The open-source ecosystem. Get insights into the future of cloud-native technology and more. Click the link to listen! 🔗 ⤵️ https://lnkd.in/g2TA9Qb4 #Entrepreneurship #AI #Cybersecurity #TechTalk #Darkrhiinosecurity #Podcast

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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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Since we have been actively using Amazon Web Services (AWS) Amazon DynamoDB for all our projects, we decided to open-source our service layer to demonstrate how we model our types to DynamoDB tables. We have repackaged our service layer into an easy-to-use service framework and published it on our GitHub page. * 𝗧𝗵𝗶𝘀 𝗶𝘀 𝗼𝘂𝗿 𝘀𝗲𝗰𝗼𝗻𝗱 𝗼𝗽𝗲𝗻-𝘀𝗼𝘂𝗿𝗰𝗲 𝗿𝗲𝗽𝗼𝘀𝗶𝘁𝗼𝗿𝘆 𝗮𝗻𝗱 𝘄𝗲 𝗮𝗿𝗲 𝗮𝗶𝗺𝗶𝗻𝗴 𝘁𝗼 𝗽𝘂𝗯𝗹𝗶𝘀𝗵 𝗺𝗼𝗿𝗲 𝗼𝗳 𝗼𝘂𝗿 𝘁𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝘆 𝗮𝗻𝗱 𝘄𝗼𝗿𝗸𝘀. 𝗪𝗵𝗮𝘁'𝘀 𝗶𝗻 𝗶𝘁 𝗳𝗼𝗿 𝘂𝘀? At initd.sg, 𝘄𝗲 𝗗𝗢 𝗡𝗢𝗧 𝗕𝗘𝗟𝗜𝗘𝗩𝗘 𝗶𝗻 𝘀𝘁𝗮𝗿𝘁𝗶𝗻𝗴 𝗮𝗻𝘆 𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁 𝘄𝗼𝗿𝗸 𝗳𝗿𝗼𝗺 𝘀𝗰𝗿𝗮𝘁𝗰𝗵. Therefore, once we identify a working pattern and if we feel that it helps the community, our first thought is always "Can we open-source this for the benefit of the community?" We have a number of working patterns in our development library ready for use anytime (web app, native app, backend integration, etc) 𝗖𝗹𝗶𝗲𝗻𝘁 𝗮𝗻𝗱 𝗠𝗩𝗣 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁 𝗪𝗼𝗿𝗸 Our clients benefit from: - Faster MVP prototyping turnaround time - Lower cost for MVP development. - Stable MVP builds (less bugs, smoother experience) 𝗖𝗼𝗻𝗰𝗹𝘂𝘀𝗶𝗼𝗻 A well-built and stable MVP is important when gathering feedback from potential customers. Customers are more likely to participate and provide feedback if the app experience is a pleasant one. MVP does not necessarily mean buggy and unstable apps. Let's focus on gathering feedbacks, not fixing bugs. Here's our GitHub Link: https://lnkd.in/gaSBRx-N Medium Article: https://lnkd.in/gKZrfVQ6 𝗚𝗿𝗮𝘁𝗶𝘁𝘂𝗱𝗲 Many thanks to Raziman Mahathir and Thomas Tan for your dedication to opensource. #mvp #prototyping #softwaredevelopment #aws #dynamoDB #opensource

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Here are 5 things we announced this year to continue helping devs secure their apps with Auth0: 1. New free and self-service plans - To help developers with more free users and many more features https://auth0.com/pricing 2. Auth for GenAI - To help developers secure their GenAI apps and agents https://auth0.ai 3. Developer portal -To help developers offer a branded, secure dev portal in a heartbeat https://lnkd.in/duesnsAV 4. UI Components -To help developers accelerate building high-quality UIs that integrate with Auth0 https://lnkd.in/dhPN2_gq 5. Advanced Customization for Universal Login - To help developers fully customize login experiences using the libs and tooling they are used to https://lnkd.in/def4NVUc I learned this year that Auth0 by Okta is by far the most used identity technology among developers That's amazing! And as those announcements show, we are always building the next thing

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🤖 Is test-driven development (TDD) on its way out? In this blog post, I explore the impact of LLMs on software development, specifically the rise of AI-generated tests. As LLMs become more sophisticated, the traditional approach of writing tests manually might become obsolete. I share my experience using LLMs to generate tests, outlining the benefits and challenges. 👉 Read the full blog post here: https://r.cosn.io/tdd

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Lunar.dev is for Lambdas too. API calls in AWS Lambda can be a traffic jam, impacting reliability, speed, and cost. Discover how Lunar.dev smooths the ride by both providing visibility and offering proactive remediations for external API errors. 🔗 Read the full blog for a smoother API Consumption journey!

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