# Low code Low-code is a software development approach that uses visual tools and prebuilt components to build applications with minimal hand coding. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Экосистема Digital Q от "Диасофт" вошла в число лидеров рейтингов CIO Navigator благодаря AI-driven подходу к разработке DevFeed: [Экосистема Digital Q от "Диасофт" вошла в число лидеров рейтингов CIO Navigator благодаря AI-driven подходу к разработке]() Original publisher: [Read original article]() Author: diasoft (Диасофт) Published: 2026-09-17T08:08:22Z Content type: news Language: ru Sources: [Tagir Valeev]() Topics: [Low code](), [Artificial Intelligence](), [Development](), [sdlc](), [Code]() Tags: [2026](), [agents](), [ai](), [ai-driven-ab7423f43dcb](), [development](), [digital-q](), [enterprise](), [low-code](), [sdlc](), [specification-driven-development](), [tag-077d33a42465](), [tag-2c039dce53be](), [tag-463bcbb8c0fe](), [tag-73efb20f7e33](), [tag-7b800b2da0b8]() ### AI overview Diasoft's Digital Q development ecosystem led the 2026 CIO Navigator ranking of Russian low-code solutions with AI features and placed second overall among 14 platforms. The article describes its AI-driven approach, including AI agents across the software development lifecycle and the use of machine-readable specifications to generate development artifacts. ### Source excerpt Компания "Диасофт" вошла в число лидеров сразу двух рейтингов российских low-code платформ 2026 года, опубликованных Санкт-Петербургским Клубом ИТ-директоров CIO Navigator. Экосистема разработки Digital Q возглавила рейтинг low-code решений с ИИ-функциями и заняла второе место в общем рейтинге российских low-code платформ. Лидерство экосистемы для разработчиков Digital Q в рейтинге российских low-code платформ с функциями ИИ стало возможным по мнению организаторов рейтинга благодаря AI-driven подходу, при котором искусственный интеллект используется на всех этапах создания и развития программного обеспечения. Участников исследования оценивали по более чем 170 критериям, охватывающим возможности искусственного интеллекта, архитектуру, инструменты разработки и другие характеристики, значимые для корпоративного применения. В общем рейтинге российских low-code платформ Digital Q заняла второе место среди 14 представленных решений. Исследование включало более 180 критериев - по функциональности, архитектуре, безопасности, интеграционным возможностям, инструментам управления жизненным циклом разработки и ИИ-функциям. CIO Navigator характеризует Digital Q как корпоративную low-code экосистему для создания и развития микросервисных информационных систем уровня enterprise, которая развивается в направлении AI-driven платформы для управляемой ИИ-разработки. В основе развития Digital Q лежит переход от использования ИИ как отдельного помощника разработчика к модели AI-Native SDLC, в которой искусственный интеллект становится полноценным участником жизненного цикла создания программного обеспечения. ИИ-агенты включаются в работу с требованиями, проектирование, разработку, тестирование и последующее сопровождение решений. Для их оркестрации в экосистеме используется платформа Digital Q.Agents. Именно сквозное применение ИИ на протяжении всего цикла разработки CIO Navigator выделяет как одно из ключевых отличий Digital Q. Читать далее ## Six Months vs Six Days: The True Cost of Building Internal Tools DevFeed: [Six Months vs Six Days: The True Cost of Building Internal Tools]() Original publisher: [Read original article]() Author: Daria Kvasnytska Published: 2026-09-01T03:00:00Z Content type: opinion Language: en Sources: [CYBERTEC PostgreSQL | Services & Support]() Topics: [Low-Code / Internal Tools](), [Low code](), [Development](), [Software Engineering]() Tags: [community](), [cost](), [cypex](), [development](), [internal-tools](), [low-code](), [product](), [software](), [tools]() ### AI overview The article examines the direct, opportunity, and maintenance costs of building internal tools, arguing that seemingly small projects can expand beyond their planned scope and reduce time available for customer-facing product work. It also discusses low-code platforms, focusing on data and application ownership, vendor lock-in, and enterprise pricing. ### Source excerpt This blog is about how CYPEX can cut costs on building internal tools. The post Six Months vs Six Days: The True Cost of Building Internal Tools appeared first on CYBERTEC PostgreSQL | Services & Support. ## Port Workflows: Orchestrate Agents, Approvals, and Automations DevFeed: [Port Workflows: Orchestrate Agents, Approvals, and Automations]() Original publisher: [Read original article]() Author: Dor Meiri Published: 2026-08-28T12:34:07Z Content type: article Language: en Sources: [Developer Experience & Platform Engineering Blog | Port]() Topics: [Orchestration](), [Automation](), [Low code](), [CI/CD](), [incident]() Tags: [agents](), [automation](), [ci-cd](), [incident](), [low-code](), [orchestration](), [workflows]() ### AI overview Port Workflows is an orchestration layer that combines agents, automations, business rules, and human approvals in a governed flow using shared, real-time context. It is designed to reduce context loss, platform-team bottlenecks, and delays in incident approvals, while enabling non-engineering teams to build and edit workflows with a low-code builder. ### Source excerpt Port Workflows chains AI agents, automations, and human approvals into one governed flow. Features, use cases, and how to start. ## What are the best platforms for network automation? DevFeed: [What are the best platforms for network automation?]() Original publisher: [Read original article]() Author: Roger Perkin Published: 2026-07-24T08:25:02Z Content type: article Language: en Sources: [Roger Perkin Network Automation Consultant]() Topics: [Network](), [Automation](), [Ansible](), [Orchestration](), [awx](), [Low code]() Tags: [ansible](), [automation](), [awx](), [faq](), [low-code](), [nautobot](), [network](), [network-automation](), [orchestration](), [red-hat](), [source-of-truth]() ### AI overview The article lists Nautobot, Itential, Ansible, AWX, and Red Hat Ansible Automation Platform as network automation platforms. It states that they serve different purposes, including configuration, orchestration, source of truth and inventory, and enterprise low-code use cases. ### Source excerpt The best platforms for network automation include Nautobot, Itential, Ansible, AWX, Red Hat Ansible Automation Platform to name a few. Each one serves a different purpose including configuration and orchestration, source of truth and inventory and enterprise low code. Check out my dedicated post on network automation platforms ## Building secure AI agents at scale: Introducing Loom for AWS DevFeed: [Building secure AI agents at scale: Introducing Loom for AWS]() Original publisher: [Read original article]() Author: Heeki Park Published: 2026-07-09T21:16:33Z Content type: article Language: en Sources: [AWS Open Source Blog]() Topics: [AI Agent](), [Security](), [Amazon Web Services](), [Amazon Bedrock](), [Authorization](), [API](), [Serverless](), [Back end](), [Inference](), [Python](), [Low code](), [No-code]() Tags: [agentic](), [agents](), [ai](), [ai-agent](), [ai-agents](), [amazon-bedrock-agentcore](), [api](), [aws](), [backend](), [code](), [deployment](), [mcp](), [model](), [no-code](), [open-source](), [python](), [security](), [serverless](), [strands-agents]() ### AI overview Loom for AWS is an enterprise-grade platform for building, deploying, and operating secure AI agents at scale. It combines AWS Strands Agents with Amazon Bedrock AgentCore and provides management, authorization, identity integration, lifecycle controls, memory, MCP and A2A integrations, governance, and usage tracking. Loom supports low-code Python agents and no-code deployment through AgentCore's managed harness. ### Source excerpt As organizations move to adopt agentic capabilities to accelerate their business objectives, they are challenged with enabling those capabilities within a security and governance framework that complies with enterprise requirements. Some organizations lean into the promise of serverless capabilities, as those fully managed services enable them to build fast and deliver customer value quickly. Amazon [...] ## How to Accept One-Time Payments Without Stripe Checkout DevFeed: [How to Accept One-Time Payments Without Stripe Checkout]() Original publisher: [Read original article]() Author: Aarthi Poonia Published: 2026-03-30T00:00:00Z Content type: tutorial Language: en Sources: [Dodo Payments Blog]() Topics: [stripe](), [Software as a service](), [Low code](), [No-code]() Tags: [alternatives](), [automatic](), [backend](), [checkout](), [compliance](), [fees](), [how-to](), [low-code](), [merchant-of-record](), [no-code](), [payments](), [saas](), [tax](), [webhooks]() ### AI overview This guide explains two alternatives to Stripe Checkout for accepting one-time payments: dashboard-generated payment links and a low-code modal checkout. It argues that these approaches can reduce server-side session work, webhook fulfillment plumbing, and tax-compliance responsibilities when a Merchant of Record handles the legal sale and taxes. ### Source excerpt Simpler alternatives to Stripe Checkout for one-time payments. Use payment links, overlay checkout, and Merchant of Record for instant setup with automatic tax handling. ## CUGA on Hugging Face: Democratizing Configurable AI Agents DevFeed: [CUGA on Hugging Face: Democratizing Configurable AI Agents]() Original publisher: [Read original article]() Author: Jim Laredo; Avi Yaeli; Sami Marreed; Ayhan Sebin; Merve Unuvar Published: 2025-12-15T16:01:04Z Content type: article Language: en Sources: [Hugging Face - Blog]() Topics: [AI Agent](), [Artificial Intelligence](), [hugging face](), [Open Source](), [computer-use](), [Orchestration](), [spaces](), [OpenAPI Specification](), [LangChain](), [MCP](), [Low code](), [Python]() Tags: [ai](), [ai-agent](), [computer-use](), [hugging-face](), [langchain](), [low-code](), [mcp](), [open-source](), [openapi](), [orchestration](), [python]() ### AI overview CUGA, or Configurable Generalist Agent, is an open-source AI agent for complex, multi-step tasks across web and API environments. The article describes its enterprise-oriented architecture, configurable reasoning modes, computer-use capabilities, integrations with OpenAPI, MCP servers, LangChain, and Python functions, plus support for low-code workflow design, policy controls, human oversight, reuse of successful execution paths, and multi-agent collaboration. It also highlights CUGA's integration with Hugging Face Spaces and reported benchmark performance on AppWorld and WebArena. ### Source excerpt CUGA (Configurable Generalist Agent) was designed to overcome these limitations. It's an open-source, AI Agent that combines flexibility, reliability, and ease of use for enterprise use cases. By abstracting orchestration complexity, CUGA empowers developers to focus on domain requirements rather than the internals of agent building. And now, with its integration into 🚀Hugging Face Spaces🚀, experimenting with CUGA and open models has never been easier. What is CUGA? ## Beyond Automation: Securing Low-Code Agentic AI with MCP Guardrails DevFeed: [Beyond Automation: Securing Low-Code Agentic AI with MCP Guardrails]() Original publisher: [Read original article]() Author: Pas Apicella Published: 2025-11-19T05:00:00Z Content type: article Language: en Sources: [Blog RSS Feed | Snyk]() Topics: [Model Context Protocol](), [Artificial Intelligence](), [Low code](), [Security](), [AI Development](), [Automation](), [observability]() Tags: [agentic-ai](), [ai](), [automation](), [blog](), [developer](), [developers](), [interest](), [low-code](), [mcp](), [observability](), [policy](), [security]() ### AI overview This article explains how Model Context Protocol (MCP) connects agentic AI systems with external tools, APIs, data sources, and applications in low-code and no-code environments. It describes integrated scanning, guardrails, policy enforcement, and immutable observability logs as controls for reducing risks such as sensitive-data exposure and insecure actions while supporting compliance and governance. ### Source excerpt Explore how Model Context Protocol (MCP) servers and integrated security scanning workflows are redefining guardrails for low-code/no-code (LCNC) and AI-driven development environments. ## Introducing low-code MCP servers in Redpanda Cloud DevFeed: [Introducing low-code MCP servers in Redpanda Cloud]() Original publisher: [Read original article]() Author: Johannes Brüderl Published: 2025-10-28T00:00:00Z Content type: article Language: en Sources: [Redpanda]() Topics: [Model Context Protocol (MCP)](), [Low code](), [AI Development](), [Cloud](), [YAML](), [stream-processing](), [PostgreSQL](), [Redis]() Tags: [ai](), [ai-agents](), [announcement](), [anthropic](), [apis](), [applications](), [cloud](), [connectors](), [kafka](), [low-code](), [mcp](), [postgresql](), [redis](), [servers](), [tool](), [yaml]() ### AI overview This article introduces Redpanda Cloud Remote MCP, a managed service for building MCP servers with low-code YAML. It explains how the service uses Redpanda Connect and more than 300 connectors to link data sources, APIs, and databases with AI applications, enabling standardized access to live organizational context. ### Source excerpt Introducing Redpanda Cloud Remote MCP, a managed solution for low-code MCP servers that easily integrates your data sources with AI apps. ## Increasing Agility & Flexibility: How Mercato Solutions tackles the application security vs. flexibility conundrum with Snyk DevFeed: [Increasing Agility & Flexibility: How Mercato Solutions tackles the application security vs. flexibility conundrum with Snyk]() Original publisher: [Read original article]() Author: Nina McClure Published: 2025-10-16T04:00:00Z Content type: article Language: en Sources: [Blog RSS Feed | Snyk]() Topics: [Application Security](), [Low code](), [snyk](), [Web](), [Cloud]() Tags: [application-security](), [awareness](), [blog](), [cloud](), [customer](), [devops](), [low-code](), [security](), [snyk](), [snyk-platform](), [web]() ### AI overview This customer article explains how Mercato Solutions, a low-code enterprise application provider, works with Snyk to address application security challenges while preserving the flexibility of its cloud-first platform. The article highlights the security risks of headless infrastructure, the resulting attack surface, and Mercato's goal of maintaining strong security with a small team. ### Source excerpt Learn how Mercato Solutions, a fast-growing low-code application provider, achieved near-zero security incidents and maintained development flexibility by partnering with Snyk API & Web. ## SyGra is a low-code/no-code framework for creating and transforming LLM and SLM datasets DevFeed: [SyGra is a low-code/no-code framework for creating and transforming LLM and SLM datasets]() Original publisher: [Read original article]() Author: Bidyapati Pradhan; Vipul Mittal; Amit Kumar Saha; Surajit Dasgupta Published: 2025-09-22T06:45:05Z Content type: article Language: en Sources: [Hugging Face - Blog]() Topics: [datasets](), [Large Language Model](), [Low code](), [dpo](), [Python]() Tags: [ai](), [datasets](), [dpo](), [llms](), [low-code](), [ollama](), [python](), [rag](), [tgi](), [vllm]() ### AI overview SyGra is presented as a low-code/no-code Python framework for creating, transforming, and aligning datasets for large and small language models. It supports use cases including Q&A generation, preference-pair creation, reasoning data, multilingual adaptation, quality filtering, and RAG-oriented datasets. ### Source excerpt You start with a simple dataset, but the model fails on advanced reasoning tasks. How do you generate more complex datasets to strengthen performance? You already have a knowledge base, but it's not in Q&A format. How can you transform it into a usable question-answering dataset? You've prepared a supervised fine-tuning (SFT) dataset. But now you want to align your model using Direct Preference Optimization (DPO). How can you generate preference pairs? ## xpander.ai Brings AI Agents to Slack, With Neon Powering the Backend DevFeed: [xpander.ai Brings AI Agents to Slack, With Neon Powering the Backend]() Original publisher: [Read original article]() Author: Carlota Soto Published: 2025-08-07T16:50:28Z Content type: news Language: en Sources: [Blog -- Neon Docs]() Topics: [Artificial Intelligence](), [Slack](), [Back end](), [Orchestration](), [Model Context Protocol](), [Low code](), [CI/CD](), [Provisioning]() Tags: [agent-orchestration](), [ai](), [ai-agents](), [backend](), [case-studies](), [ci-cd](), [database](), [llm](), [mcp](), [product](), [provisioning](), [slack]() ### AI overview xpander.ai is launching a Slack integration that deploys production-ready AI agents as autonomous teammates. Its platform provides agent memory, tools, multi-agent orchestration, MCP support, integrations, CI/CD, versioning, and governance. Neon powers the backend by storing agent memory and providing an isolated Postgres project for each tenant. ### Source excerpt "The entire memory layer of our agent, all its session data, is stored in Neon. It's the backend for everything the agent remembers." (Ran Sheinberg, co-founder and CPO of xpander.ai) xpander is a new platform built for helping developers build and run production-ready AI agents.... ## Building Diving Nomads: Automating Dive Center Onboarding and Memberships with No-Code Tools DevFeed: [Building Diving Nomads: Automating Dive Center Onboarding and Memberships with No-Code Tools]() Original publisher: [Read original article]() Author: tobi@techunicorn.builders (Tobias Mende) Published: 2025-07-25T05:00:00Z Content type: tutorial Language: en Sources: [Tobias Mende]() Topics: [Automation](), [n8n](), [No-code](), [Low code](), [Database](), [email](), [Self-hosted](), [Notion](), [Cloud]() Tags: [automate](), [automation](), [building](), [created](), [database](), [email](), [hooks](), [low-code](), [n8n](), [no-code](), [platform](), [startup-business-automation-software-development-case-study-practices]() ### AI overview This article describes how Diving Nomads uses an automation-first stack to onboard dive centers and manage memberships. It covers scraping directories into NocoDB, sending outreach through Brevo, tracking responses with webhooks, and using n8n workflows to reduce manual work. ### Source excerpt Building Diving Nomads in Public: How We Onboard Dive Centers and Automate Memberships with (Almost) No Code TL;DR We're building a platform for digital nomads with a passion for scuba diving. Our lean, automation-first tech stack allows us to move fast, deliver value early, and maybe inspire other early-stage founders to rethink how they build. ## How to Create an AI Agent With Heroku and Agentforce DevFeed: [How to Create an AI Agent With Heroku and Agentforce]() Original publisher: [Read original article]() Author: Andrew Fawcett Published: 2024-10-17T18:15:00Z Content type: tutorial Language: en Sources: [Heroku]() Topics: [AI Agent](), [Heroku](), [Artificial Intelligence](), [data](), [Low code]() Tags: [agent](), [agentforce](), [ai](), [ai-agent](), [data](), [engineering](), [heroku](), [how-to](), [integrations](), [low-code](), [product-features](), [salesforce]() ### AI overview A tutorial on creating an AI agent with Salesforce Agentforce and Heroku. It explains how Heroku can provide access to diverse, high-volume data and scalable compute, and describes Agentforce capabilities for building, testing, and extending agents with code or low-code actions. ### Source excerpt Heroku is a powerful general-purpose PaaS offering, but when combined with the broader Salesforce portfolio, it excels in unlocking and unifying customer data, regardless of its age, location, size, or structure. Salesforce customers turn to Heroku when they need to leverage high data volumes from sources such as consumer web or mobile apps or when [...] The post How to Create an AI Agent With Heroku and Agentforce appeared first on Heroku. ## Expanding our Partner Program DevFeed: [Expanding our Partner Program]() Original publisher: [Read original article]() Author: Arjun Rajeswaran Published: 2024-02-20T16:27:05Z Content type: article Language: en Sources: [Blog -- Neon Docs]() Topics: [Developer Platform](), [Serverless](), [Databases](), [autoscaling](), [API](), [Security](), [Front end](), [Low code](), [No-code](), [Repl.it](), [Vercel]() Tags: [api](), [autoscaling](), [building](), [company](), [customers](), [data](), [developer](), [developer-platform](), [developers](), [ecosystem](), [infrastructure](), [launch](), [partner](), [partners](), [platforms](), [postgres](), [product](), [program](), [scale](), [security](), [vercel]() ### AI overview Neon announces an expanded partner program with Standard and Premier tiers. The program helps developer platforms embed serverless Postgres, offer scalable databases, and access features such as database branching, scale to zero, autoscaling, API integration, security enhancements, technical support, and marketing assistance. ### Source excerpt At Neon, we aspire to bring Postgres to as many developers as possible, a vision that is shared by our rapidly growing ecosystem of partners. Since the launch of our partner program, we have been fortunate to work with partners like Vercel, Replit, and others to reach hundreds of... ## How to build AI-powered apps using Postgres and DronaHQ DevFeed: [How to build AI-powered apps using Postgres and DronaHQ]() Original publisher: [Read original article]() Author: Aaikansh Agrawal Published: 2024-01-17T12:15:36Z Content type: tutorial Language: en Sources: [Blog -- Neon Docs]() Topics: [Low code](), [Artificial Intelligence](), [Low-Code / Internal Tools](), [Databases](), [Front end](), [OpenAI]() Tags: [ai](), [ai-apis](), [ai-models](), [apis](), [applications](), [article](), [community](), [dashboards](), [data](), [database](), [developers](), [forms](), [frontend](), [how-to](), [internal-tools](), [low-code](), [no-code](), [openai]() ### AI overview This article explains how low-code tools can help developers build internal, AI-powered applications. It describes connecting stored lead data and databases to unified frontends, forms, workflows, tables, dashboards, and AI APIs or models that generate personalized email content. The supplied text ends while beginning a demonstration involving Neon and DronaHQ. ### Source excerpt AI, no-code, and low-code have captured the world's imagination. Developers now have an easier time adding new features than ever before. These new tools have really made a difference for developers, helping them build bigger systems, and do it all much faster. In this article, I... ## Low-code analytics with James Devonport of UserLoop DevFeed: [Low-code analytics with James Devonport of UserLoop]() Original publisher: [Read original article]() Author: Tinybird Published: 2023-05-05T00:00:00Z Content type: article Language: en Sources: [Tinybird]() Topics: [Low code](), [data]() Tags: [data](), [i-built-this](), [low-code]() ### AI overview James Devonport built analytics for Userloop without hiring a data team, using a low-code approach. ### Source excerpt James built analytics for Userloop without hiring a data team. Low-code made it possible. Here's his exact approach. ## Automating customer usage alerts with Tinybird and Make DevFeed: [Automating customer usage alerts with Tinybird and Make]() Original publisher: [Read original article]() Author: David Margulies Published: 2023-05-01T00:00:00Z Content type: tutorial Language: en Sources: [Tinybird]() Topics: [make](), [Automation](), [Low code]() Tags: [automation](), [customer](), [i-built-this](), [low-code](), [make]() ### AI overview The article describes using low-code analytics and automation with Tinybird and Make to help a team become more proactive about customer usage alerts. ### Source excerpt Here's how I used "low-code" analytics and automation to help my team be more proactive. ## Community Day DevFeed: [Community Day]() Original publisher: [Read original article]() Author: Andrew Smith; Jon Meyers; Thor Schaeff; Tyler Shukert Published: 2022-12-16T07:00:00Z Content type: article Language: en Sources: [Supabase Blog]() Topics: [Supabase](), [Open Source](), [Flutter](), [Next.js](), [Authentication](), [Messaging](), [Database](), [Low code](), [Back end](), [Security]() Tags: [authentication](), [backend](), [community](), [contributors](), [database](), [flutter](), [guides](), [integration](), [launch](), [low-code](), [messaging](), [next-js](), [open-source](), [partners](), [postgres](), [security](), [video]() ### AI overview Supabase's Community Day article highlights recent community activity and new integrations. It covers FlutterFlow for low-code Flutter application development with Supabase as the backend, OneSignal for messaging triggered by database changes, and a community-built Supabase Adapter for NextAuth.js authentication and Row Level Security. It also begins discussing the Postgres ecosystem and the PGroonga multilingual search extension. ### Source excerpt Wrapping up Launch Week 6 with contributors, partners, and friends. ## Hacktoberfest with Astro Docs DevFeed: [Hacktoberfest with Astro Docs]() Original publisher: [Read original article]() Author: Chris Swithinbank; Sarah Rainsberger; Dan Jutan Published: 2022-10-31T00:00:00Z Content type: article Language: en Sources: [The Astro Blog]() Topics: [Astro](), [Open Source](), [Maintainers](), [Pull Request](), [Low code](), [ci](), [Deno](), [Discord bot]() Tags: [astro](), [ci](), [digital-ocean](), [discord](), [github](), [go](), [low-code](), [maintainers](), [open-source](), [review]() ### AI overview Astro Docs Week highlights how Hacktoberfest supported Astro's open-source documentation community. The project merged more than 130 pull requests from 58 contributors, including 41 first-time contributors, with many contributions focused on translations and reviews. ### Source excerpt It's Astro Docs week! See how we hacked Hacktoberfest to celebrate our awesome contributors this October. ## Developer Spotlight: Payable Forms DevFeed: [Developer Spotlight: Payable Forms]() Original publisher: [Read original article]() Author: Joan Mweu Published: 2022-07-29T19:00:00Z Content type: article Language: en Sources: [Square Corner Blog RSS Feed]() Topics: [App](), [Low code](), [Automation](), [SDKs](), [Tooling](), [Google]() Tags: [apis](), [app](), [automation](), [business](), [developer](), [google](), [low-code](), [payments](), [sdk](), [small-business](), [spotlight](), [tooling](), [tools]() ### AI overview This Developer Spotlight profiles Payable Forms, a low-code app for small businesses that connects forms, subscriptions, automations, and payments. Its founder discusses choosing Square, onboarding sellers, and using Web Payments SDK for Afterpay and Cash App Pay integrations. ### Source excerpt Bringing the power of payments to small business tools ## Supabase Beta Sept 2021 DevFeed: [Supabase Beta Sept 2021]() Original publisher: [Read original article]() Author: Paul Copplestone Published: 2021-10-04T07:00:00Z Content type: release Language: en Sources: [Supabase Blog]() Topics: [Supabase](), [PostgreSQL](), [real-time](), [Authentication](), [Authorization](), [dashboards](), [Low code](), [OAuth](), [React](), [Expo](), [interactive website]() Tags: [auth](), [authorization](), [discord](), [flutter](), [github](), [hackathon](), [low-code](), [oauth](), [open-source](), [postgresql](), [react](), [react-native](), [real-time](), [remote](), [ui](), [updates]() ### AI overview Supabase's September 2021 update covers a new hackathon, AbortController support for aborting long-running queries, dashboard improvements for PostgreSQL table management, revised authentication and authorization documentation, a low-code integration demo, community content, and hiring for remote SRE roles. ### Source excerpt Hackathon, Aborting request, UI updates, and now Hiring. ## Implementing ETL on GCP DevFeed: [Implementing ETL on GCP]() Original publisher: [Read original article]() Author: Deepmala Published: 2020-07-15T20:53:17Z Content type: tutorial Language: en Sources: [Brave New Geek]() Topics: [DataOps](), [Cloud](), [BigQuery](), [data loss prevention](), [Low code](), [No-code](), [olap]() Tags: [analytics](), [analytics-pipeline](), [bi-tools](), [bigquery](), [cdap](), [cloud-data-loss-prevention](), [cloud-dataflow](), [cloud-dataprep](), [cloud-dataproc](), [cloud-pub-sub](), [cloud-storage](), [cloud-tasks](), [data-analytics](), [data-fusion](), [data-lake](), [data-loss-prevention](), [elt](), [etl](), [gcp](), [no-code](), [serverless](), [sql]() ### AI overview A practical guide to building ETL pipelines on Google Cloud Platform using Google-managed services. It explains a two-phase architecture with Cloud Storage as a data lake, Cloud Data Loss Prevention for sensitive-data detection or redaction, and BigQuery as the curated data warehouse, with attention to low-code and no-code approaches. ### Source excerpt ETL (Extract-Transform-Load) processes are an essential component of any data analytics program. This typically involves loading data from disparate sources, transforming or enriching it, and storing the curated data in a data warehouse for consumption by different users or systems. An example of this would be taking customer data from operational databases, joining it with data from Salesforce and Google Analytics, and writing it to an OLAP database or BI engine.