Dharmesh Thakker

Craziest thing in M&A? For Dr. Tianyi (TJ) Jiang, CEO of AvePoint, it’s all about integration. In a recent interview, TJ shared a story about a deal where the acquirer had to remind the acquired employees: “You realize we bought you, right?” Post-acquisition integration is where things get messy. Cultures clash, systems collide, and if people don’t buy into the vision, the deal can fall apart. Buying a company is one thing. Winning over its people? That’s where the madness—and the magic—happens. Want to hear more about navigating this chaos? Watch our podcast with TJ: https://hubs.ly/Q02XgsB50 What’s the craziest thing you’ve seen in M&A? Share your story in the comments. #MAScience #MergersAndAcquisitions #InvestorRelations #CapitalRaising #SustainableGrowth 

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Some additional charts on the aggregate hyperscaler data from Q1. The charts below show 1) The aggregate net new ARR added on q quarterly basis. Q1 is always a seasonal low 2) The YoY growth in net new ARR in Q1. Q1 '23 was the "bottom" with AWS actually adding negative net new ARR (ie they shrunk), so the YoY comp is the "easiest" for the aggregate bucket.

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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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The Forbes 2024 Cloud 100 List is live ☁ Congrats to all the honorees – the world's top 100 private cloud companies –including the 3 healthcare and life sciences companies featured this year: • Benchling - biotech R&D platform • Komodo Health - healthcare data analytics • Abridge - AI for clinical documentation For more on how AI is colliding with cloud computing, check out Bessemer Venture Partners's 2024 Cloud 100 report. Personally I'm focused on advancements in multi-modal AI, as applied to biomedical applications (Trend 3!): https://lnkd.in/euzurvQV

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Why IBM's Acquisition of HashiCorp is a Game-Changer for Investors IBM's $6.4 billion acquisition of HashiCorp significantly bolsters its hybrid and multi-cloud capabilities, positioning it as a leader in the AI era. HashiCorp’s expertise in cloud infrastructure, lifecycle management, and security automation complements IBM’s strengths, creating an end-to-end cloud platform. This strategic move enables IBM to offer enhanced solutions for managing complex cloud environments and generative AI workloads, providing investors with robust growth potential and a competitive edge in the evolving tech landscape. #IBM #HashiCorp #CloudComputing #AI #InvestmentOpportunity #PINCommunityAdvocate #IBMPartner

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At #OffsetSymposium2024, and couldn’t agree more with Corey Jaskolski that wide-spread #cloud adoption across #DOD allows startups to scale more broadly, lowers their costs, allows them to move faster, and ultimately delivers more, saving the limited taxpayer dollars we have for #nationaldefense.

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And we’re live. 🚀 Today, we’re thrilled to announce we’re launching out of stealth with $10.5 million in funding to build a unified dataops platform. When co-founders Benjamin Segal & Geva Segal started Matia, they wanted to solve a real problem they saw in the data and engineering world. They were managing and scaling large teams, and relying on disparate tools to move their data to Snowflake and back to their SaaS platforms, another tool to leverage their data lineage, and another one to monitor their data pipeline quality. Their teams were full of talented engineers, but they were spending most of their time piecing together their data stack and investigating anomalies, rather than focus on their core job. So they spoke to other data and engineering leaders about how they solved this problem. Everyone agreed it was an issue, but no one had the solution. And as more companies adopted AI strategies, the importance of an observability platform that natively monitored data before it was even ingested became even more important. So that’s where the idea of Matia was born: A unified dataops platform bridging together ingestion, reverse ETL, observability and catalog. 🧠 With pre-built connectors, data and AI teams can plug in seamlessly to the tools they use, and integrate with Databricks, Snowflake and even monitor transformations natively in dbt Labs. While it’s only the beginning of our journey, we’re grateful to have amazing customers like Ramp, Obligo, & HoneyBook onboard and already seeing incredible results, and backed by investors including Leaders Fund, Secret Chord Ventures, Cerca Partners & Caffeinated Capital. The best is yet to come. Follow our journey. Link in comments for more.

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LLMs are moving into the #Observability space.. LLMs will change the game for these vendors and their customers. By harnessing the power of LLMs, companies will be able to process massive quantities of data in real-time, enabling them to detect potential issues before they escalate into costly problems. But with #AI, #Data cost will be a huge problem.  Vendors leveraging cheap storage like S3 will have an upper hand. Worth a read.. #datadog, #Elastic, #Chaossearch, #Newrelic https://lnkd.in/ekV2NciT

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➰ 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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#Confluent Acquires #WarpStream: A Strategic Move in Data Streaming Confluent has made waves by acquiring WarpStream, a startup known for its Kafka-compatible streaming data solutions. This acquisition aims to bolster Confluent's product offerings by introducing a "bring your own cloud" model, which sits between their fully managed Confluent Cloud and self-managed Confluent Platform. As Co-founder and CEO Jay Kreps explains, this model addresses the needs of organizations requiring more control and customization without fully managing everything themselves. This strategic move highlights Confluent's commitment to providing a comprehensive portfolio for diverse data streaming use cases. With WarpStream's expertise in areas like IoT and observability, Confluent is poised to enhance its cloud-native solutions. As the demand for seamless data streaming grows, how will this acquisition impact the landscape of data architecture? #Confluent #WarpStream #DataStreaming #Kafka #CloudComputing #TechAcquisition #Saasverse

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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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🚀 AWS re:Invent 2024 introduces a game-changing feature: “Buy with AWS”! This powerful new tool simplifies procurement for ISVs, allowing customers to effortlessly browse, evaluate, and purchase software directly from an ISV's website—no need to navigate AWS Marketplace separately. As an integration partner, SaaSify is thrilled to support this innovative advancement and is eager to help ISVs implement this feature seamlessly on their sites. Key Benefits of "Buy with AWS" Integration:  ● Empower buyers to make purchases directly on your site.  ● Streamline every transaction and lead with minimal effort.  ● Gain deeper insights by tracking visits, clicks, and conversions like never before. Learn More https://lnkd.in/gu3hCqeS   Ready to take advantage of this breakthrough? Connect with SaaSify experts today and get started! https://lnkd.in/gfW-grMe   #AWS #reinvent #awsreinvent #partnerships

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Anthropic Partners with Palantir and AWS to Target Defense Sector with AI Solutions - Anthropic has teamed up with Palantir and Amazon Web Services (AWS) to offer its advanced AI technology to defense customers, focusing on secure and strategic applications. - This collaboration seeks to leverage Palantir's data integration capabilities and AWS's cloud infrastructure to enhance AI deployment within defense environments. - By aligning with these industry leaders, Anthropic aims to extend its reach into the defense sector, providing sophisticated AI tools designed to support complex, mission-critical operations. - The partnership underscores the increasing intersection of AI technology and defense, highlighting the demand for cutting-edge solutions in national security contexts. #DefenseTech #AIInnovation #AnthropicAI Read more: [https://buff.ly/3NUTxVD]

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If you are working with Docker... I highly recommend looking at the Slim toolkit. https://lnkd.in/gX_Gb9Kf Why? Slim allows developers to inspect, optimize, and debug their containers using its xray, lint, build, debug, run, images, merge, registry, vulnerability (and other) commands. It simplifies and improves your developer experience building, customizing and using containers. It makes your containers better, smaller and more secure while providing advanced visibility and improved usability working with the original and minified containers. Don't change anything in your container image; minify it by up to 30x to make it secure, too! Optimizing images isn't the only thing it can do, though. It can also help you understand and author better container images. Keep doing what you are doing. No need to change anything. Use the base image you want. Use the package manager you want. Don't worry about hand-optimizing your Dockerfile. You shouldn't have to throw away your tools and your workflow to have small container images. Node.js application images: from ubuntu:14.04 - 432MB => 14MB (minified by 30.85X) from debian:jessie - 406MB => 25.1MB (minified by 16.21X) from node:alpine - 66.7MB => 34.7MB (minified by 1.92X) from node:distroless - 72.7MB => 39.7MB (minified by 1.83X) Go application images: from golang:latest - 700MB => 1.56MB (minified by 448.76X) from ubuntu:14.04 - 531MB => 1.87MB (minified by 284.10X) from golang:alpine - 258MB => 1.56MB (minified by 165.61X) from centos:7 - 615MB => 1.87MB (minified by 329.14X) Rust application images: from rust:1.31 - 2GB => 14MB (minified by 147.16X) Java application images: from ubuntu:14.04 - 743.6 MB => 100.3 MB

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🚨 Heading to #ObservabilityDay on Nov. 12? Be sure to stop by Altinity #Developer Advocate Josh Lee's talk "Where's the auto in auto-instrumentation? A look at current automation strategies with #OTel." He will do a deep dive on how to achieve end-to-end #observability coverage with no custom code and minimal setup. 😎 https://hubs.la/Q02VG70t0

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When adding all of their clients to a new Confluent Cloud-based architecture, interactive ad-tech platform Skai realized their initial design would require 90,000 topics in order to accommodate everyone. Using many-to-one relationships between producers and topics, and between consumers and topics, Skai devised an ingenious architecture that reduced that number to 1,800 topics. Learn how they did it in a new blog: https://cnfl.io/3WIEQcf

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#ObservCrew, Anil just stumbled upon Ross Lazerowitz's post on emerging trends. In it Ross envisions an ELK-like stack built on open-source data warehouses. It's a thought-provoking idea, combining ELK's familiarity with modern warehouses' scalability but could our shard friends handle it. While it seems like reinventing the wheel, I wonder if there's untapped potential. What's your take, revolutionary or redundant? 🤔 Would you like to hear Ross's perspective on our podcast? https://lnkd.in/e_Qr9g8p #observability #opensource #innovation

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🌍🔋 Europe takes the lead in the new era of tech infrastructure! DataCrunch, Europe's first AI cloud hyperscaler, is breaking boundaries by running on 100% renewable energy. This move not only transforms cloud computing but also sets a high standard for sustainability in the tech industry. 🌱💡 Hyperscalers are rethinking their strategies as renewable energy becomes the focal point. The era of chasing cheap utility grid rates is fading, giving way to scalable investments with lower operating costs. Wind, solar, and battery systems are now key players in ensuring robust and cost-effective electric systems for megawatt to gigawatt-class data centers. Exciting times lie ahead as we anticipate the ripple effects of this groundbreaking initiative across the tech landscape and beyond. Stay updated on this game-changing development: [Link to article] 📊🌐 #AICloud #RenewableEnergy #Sustainability #GreenTech #Hyperscalers #DigitalTransformation #TechInnovation #CleanEnergy #CloudComputing #EuropeTech #DataInfrastructure #AIInfrastructure #Telecom #Manufacturing #TechForGood #SustainableDevelopment #AI #CloudTech #EnergyTransition #NextGenTech

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JFrog Ltd., the Liquid Software company and creators of the JFrog Software Supply Chain Platform, today announced a new product integration with NVIDIA NIM microservices, a component of the NVIDIA AI Enterprise software platform. Their platform has been expanded to include a unified MLOps platform as a result of the acquisition of Qwak AI. It is anticipated that the JFrog Platform will be integrated with the JFrog Artifactory model registry and NVIDIA NIM to create an end-to-end software supply chain workflow that combines GPU-optimized, pre-approved AI models with centralized DevSecOps processes. Read more - https://lnkd.in/gpy_sCJZ For Startup funding reach out us at: https://lnkd.in/gra5x2Xi To share your startup information write us on - [email protected] Join Our Whatsapp Channel To Get The Latest Updates & News: https://lnkd.in/esJEFzan #tech #AI #automation #nvidia #JFrog #AIEnterprise #microservices

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