Gururaj Pandurangi

➰ 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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JFrog reported its quarterly earnings on Aug 7th. ProntoNLP compared the JFrog earning call transcript to 3 other similar SAAS (DevOps) companies as well as to the average of the software GICS group. ProntoNLP's Aspect based LLM signal gave an early warning for JFrog on May 9th 2024 (their last earning call) when the Aspects score dropped from 0.52 to 0.4. ProntoNLP analyzed the earning call transcripts of these 4 SAAS (DevOps) companies JFrog, Atlassian, Dynatrace and Datadog. As can be seen in the image below the only company that had an increase in the LLM score compared with its score last quarter is Atlassian while JFrog had a much lower LLM score (-16%) compared with their last quarter (Color Legend is at the top part of the image below). The dotted navy blue line shows the average LLM score for each of the last 4 quarters for the whole software GICS group. All these 4 companies are SAAS companies and hence the customer related LLM categories are extremely important. The image below shows that Datadog and Atlassian have extremely high values for Customer Acquisition, Customer Behavior and Customer Retention. ProntoNLP's new LLM Aspects based signal for these companies shows the following trend: JFrog: a huge decline from 0.4 last quarter to 0.08 Atlassian: score stayed the same at 0.43 Dynatrace: slight decline from 0.45 last quarter to 0.42 Datadog : slight decline from 0.47 last quarter to 0.42 Based on the LLM scores in the Customer related categories and the change in the Aspects scores of the 4 software stocks it seems that Atlassian and Datadog are the top picks now and JFrog is at the bottom of the pack. The new comparison feature of ProntoNLP is extremely powerful and can support picking the winners and losers within any GICS group based on the latest #GenerativeAI technologies. ProntoNLP provides via SFTP real time quantitative signals on earning calls, filings, macro and news. Reach out to ProntoNLP to start using our #GenerativeAI based tools and Maintain an edge in alpha creation. #Quant #HedgeFunds #ArtificialIntelligence #StockMarket

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Cloud-native SFTP services, like AWS Transfer, are not easy to set up and manage, in my opinion. Do you agree? It practically requires a full-blown development effort to deploy. SFTP Gateway, on the other hand, can be launched with a click of a button from the cloud marketplaces. Its simple, web-based GUI allows you to manage users and storage locations. It's also less expensive. Who wants to waste all their time managing an SFTP service? SFTP Gateway just works, so you can spend more time on your business applications instead. Check out this blog post for more differences between AWS Transfer and SFTP Gateway. https://lnkd.in/gWyJvdJC

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#Observability sold as SaaS is just 1% of its potential. Here’s why your org is paying full but losing out the remaining 99%: Observability also has four very distinct components: ↳ Generation : Creation of telemetry data using instrumentation in user space or kernel space. ↳ Pipeline: Collecting, processing, and exporting telemetry data to storage. ↳ Storage: Storing the telemetry data efficiently, allowing real-time access and availability. ↳ Visualization: Presenting data in a simple and actionable manner. If we do not decouple these, you can imagine the hindrance in the development of the observability landscape. There are some really useful products, but they are using (or abusing?) this very fact that it is not decoupled yet, thus harder to replace. Ensuring that these components have their own parallel growth provides each institution the means to build observability which bends to their infrastructure not another way around. And that’s our vision at Incerto. Curious to learn more? Here’s a no BS blog on building the perfect observability solution: https://lnkd.in/g2be3JRw #DevOps #monitoring #developercommunity

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💙 Excited to share my latest post on TheNewStack on addressing the staging bottleneck problem impacting Engineering teams building Microservices: https://lnkd.in/gM_hB_wC #stagingenvironments #kubernetes #microservices #testingstrategies #developerexperience

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The Death of SaaS (V1 Arch): A New Era of Technology is Here! A few of us have known this for a few years now, but Satya Nadella, the CEO of Microsoft, recently shared his take on how and why this will happen. He explains that the "stack" we rely on today—layers of UI down to the database—is fundamentally the same across nearly all applications, differing only in domain logic. This resonates deeply with what I’ve been writing about for over a year and is one of the core reasons I founded the first (and currently only) neuromorphic company, Lani. While the idea of the traditional stack "going away" sounds magical, as if technology will no longer need anything at all, this isn't the full picture. The truth is, this shift will lead to the creation of a new suite of tools designed for an ecosystem where AI is at the core. These tools will dynamically drive optimizations and interfaces rather than being painstakingly built and deployed by engineers. Just like the 'flux capacitor' in Back to the Future needed a car to manifest its magic in the real world, the new stack will need analogous tooling to bridge AI's capabilities into tangible, real-world systems. This is the next frontier, and it's an exciting time to innovate. What are your thoughts on how AI will shape this transformation? https://lnkd.in/gXeYZSMY #AI #TechInnovation #NeuromorphicComputing #FutureOfSaaS #AIRevolution #NextGenTech #DigitalTransformation #SaaSIsDead #AIInfrastructure #Lani

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Dinesh Adhithya inspired me to rethink the MOQ CDN design. Now clusters of edges will check for content in the directory and direct the request to pull from a regional origin, which will then check the directory and pull from the actual origin. This implements a multi-tier MOQ relay network. Here is the source code to the Cloudflare Worker Directory: https://lnkd.in/eUgt8Ddq ... Here is the implementation: https://vivoh.earth

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💡 The idea in this video isn’t new—but now someone influential has said it out loud: 👉 SaaS is dead. Is SaaS Really Dead❓ Yes. Software in general is being redefined. Software boils down to: a database, business logic, and a user interface. Traditionally, a developer would structure these based on your instructions. In the future, AI agents will. You explain your requirements, the agent: - Sets up the database. - Generates the code for business logic and UI. - Deploys and maintains the solution. This disintermediates the traditional SaaS business model. Does this work today? How long until❓ Not yet. Currently, code generated by LLMs needs review, often containing errors. Most models can’t yet deploy, integrate, or maintain applications independently. But given the immense value this will bring, it’s only a matter of time. Looking at the rapid improvements in LLMs, especially in solving complex problems, it’s hard not to wonder how soon we’ll reach this point. While predicting timelines is tricky, it might happen much faster than you think. Starting a business today, only to have it disrupted within 2–5 years, is a risky bet. Can't you say: “SaaS is evolving, integrating AI into their solutions”❓ Sure, if you want to feel good... It’s like automakers doubling down on hybrids to compete with EVs—it keeps them relevant for a while, but it won’t stop the inevitable. Integrating AI into SaaS tools may buy time, but it’s not the same as embracing an AI-driven paradigm. AI agents have the potential to automate processes entirely, eliminating the need for the SaaS structure itself. This "evolutionary mindset” reflects reluctance to face disruption. Incremental changes might delay the shift, but won’t prevent it. So, how can you navigate this dilemma❓ If you haven’t started yet, rethink: Focus on a strong differentiator and adjust. If you’ve already started, pivot. Some ideas: Leverage Network Effects: Build something that becomes more valuable as more people use it. This is harder for AI to replicate. Think PaaS: Create a platform that others can build on. While this alone might not guarantee success, it's pointing to the right direction.  Think Ecosystem: Explore how you can create an interconnected ecosystem for your business. This ties back to the ideas of Network Effects and PaaS above, but can also introduce other unique opportunities for differentiation. The key is to focus on what AI can’t replicate. An example of an AI-proof software business❓ bfluence (our micro-influencer platform) and B4AConnect (e-commerce platform) are deeply integrated into an ecosystem: bfluence gains value with every new influencer, amplifying network effects for brands. B4AConnect leverages user data to enhance beauty brand development, creating increasing value as usage grows. 💡The value is not just the software—it’s the ecosystem, where each part strengthens the whole. That kind of model is much harder for AI to disrupt. #Ecosystem #AI

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This is incredible news for Amazon Kinesis Data Streams On-Demand users! KDS On-Demand now allows writing up to 10 GB/s, a significant 5x enhancement! The most remarkable aspect is that there is no action required to leverage this feature. #Kinesis #data #BigData #streamingdata #Datastreaming #ondemand #AWS Link: https://lnkd.in/gdm_FXrU

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My whole career has been at companies whose biggest competitor is business as usual. Cloud Virtualization Deduplicated back up Direct attached storage Automated resource allocation Hyperconverged infrastructure These were crazy ideas initially. Now they are industry standards. Not because they are cool. But because the business outcomes they drove were powerful. Powerful enough to cut through the political and organizational debt that exists in every large company. Powerful enough to CREATE budget for. Powerful enough to change the way people thought about solving a problem they’ve dealt with for a long time. Shift Group is different in that we don’t solve a technical problem, but the problem we solve is a function of business as usual. Posting jobs online, going through resumes, spending time screening candidates that aren’t a fit, hiring people that are not committed to success and then realizing it too late. High attrition. Slow ramp time. Onboarding risk. Every single company in the world deals with these problems. Our brains are so broken through years of conditioning companies actually brag about the problem!!! “We get 1000 applicants for every job post” Sick bud - then what happens? Wasted time, money, and energy - that’s what. I’ve seen this movie for 2 decades and I know how it ends. We will change this. We will be the industry standard. #AllGasNoBrakes #DialedIn

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Sometimes small changes are a big deal. S3's per-account bucket limit has meant that buckets have been more of a human provisioning thing, starkly different from objects, which tend to be interacted with primarily from code. For years, customers have been asking us to increase this limit -- and in the storage innovation talk at re:Invent this year, i'd tell a bit of a story about why it was a more complicated bit of work than you might expect. With this limit increase, buckets have become a much more programmatic construct. We hear customers talking about using buckets, with these limit increases, as a way of managing data sharing with their own customers and using them to more effectively isolate data for specific jobs and teams. If larger numbers of buckets opens up a new pattern for you, I'd love to hear more about it. These launches, like object consistency, S3 conditionals, and big bucket limit increases have a tendency to fly a little below radar. But they are the ones that I actually hear the most excitement back from developers about, because they really broaden S3 as a programmatic interface to your data, and a building block for really incredible systems. I'm so impressed with the hard and careful work on the team that went in to getting this one out. https://lnkd.in/gA2cWATM

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THIS ONE is a must watch !!! Kudos to Sarah Guo and Elad Gil for a fascinating discussion with Matt Garman about the past, present, and future of Amazon Web Services (AWS). #AIDecade #InvestorDecade

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SaaS Daily Funding News $330m+ invested into the software industry. Details 👇 Cohesity - Series F - $150m - offers hyperconverged secondary storage for backups, test/dev, file services, and analytics use cases. NightVision - Seed Round - $5.4m - Web & API security testing company Dot Compliance - Series B - $17.5m - delivers the industry's first ready to use cloud-based quality and compliance management solution for regulated industries. HumanX - Seed Round - $6.m - focuses on AI serves as a catalyst for enterprises. PineGap.ai - Seed Round - $2.5m - an AI-powered equity research platform for Wall Street Qureight - Series A - $8.4m - an imaging analytics company. Ecotrak Facility Management Software - Series Unknown - $30.m - offers a mobile-first, web-based asset management SaaS platform to manage its facilities online. Clientell - Seed Round - $2.5m - offers no-code machine learning platform to analyze consumer data and predict behaviour Lawhive - Seed Round - $11.8m - on a mission to make legal help accessible to everyone. Apify - Series Unknown - $2.9m - a web scraping and browser automation platform that can turn any website into an API. Bridgewise - Series A - $21.m - aims to become the industry standard for equity research by applying advanced AI My Emissions - Seed Round - $1.6m - platform for food companies to accurately measure and reduce carbon emissions. Official carbon labelling partner of Just Eat. ClickPost - Series A - $6.m - a logistics intelligence platform that helps companies use data science to improve supply chain performance. Cozero - Series A - $6.9m - empowers companies to decarbonize and boost their business performance. GridBeyond - Series C - $55.3m - wireless energy management and control systems for retail, commercial and industrial users. Take2 AI - Seed Round - $3.m - AI-Powered job simulation platform for sales recruiting. #saas #software #startups #venturecapital #technology #startup

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Key insight from Satya Nadella on the Bg2 Pod that's not getting enough attention: SaaS applications as we know them will collapse in the AI era. Why? The business logic layer is moving entirely to AI agents. The future architecture: • Agents will be multi-repo CRUD, not tied to single databases • Business logic shifts from apps to the AI tier • Backend systems become primarily data stores This isn't just a data transformation - it's a fundamental shift in how business logic and communication flows through enterprise systems. Think supply chains operating like real-time trading desks rather than quarterly review cycles. The architectural implications here are massive and under-appreciated. And to make these AI agents from different vendors collaborate with each other, we need agentic connectors - something we have been thinking about solving for a while. Worth a listen -->Agentic discussion starts around the 30 min mark: https://lnkd.in/gvCqyQau). The future is truly agentic.

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How Kamal Shifted My Perspective on Scaling Beyond the Cloud When David Heinemeier Hansson first suggested that cloud solutions might not be the best choice for scaling, I was skeptical. In a world where cloud providers like AWS or Google Cloud seem like the go-to solutions, moving away from them felt risky. But with the release of Kamal, I’ve completely shifted my perspective. Kamal’s ability to provide zero-downtime deploys, flexibility across low-cost cloud options, and seamless operation on our own hardware has shown me that true scalability can exist without being locked into a single provider. Kamal has proven that freedom, control, and resilience are possible outside the traditional cloud ecosystem—and I’m all in! I also love the name, inspired by the ancient Arab navigational tool that helped sailors stay on course by determining their latitude via the Pole Star. (Kamal was formerly known as MRSK.) you could check it out here: https://kamal-deploy.org #Scaling #OpenSource #Kamal #DevOps #CloudComputing

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