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“Parseable, an open observability datalake, handles 100M time-series/min https://www.parseable.com Landing page content (Parseable | Observability infrastructure for fast growing teams): Parseable | Observability infrastructure for fast growing teams # Observability infrastructure for agents, apps, & systems Parseable unifies telemetry data, keeps full-fidelity data queryable. It all lives in open formats on object store with complete control and ownership THE PROBLEM Your observability stack costs more than it delivers users reported poor return on investment in their observability tooling. Primarily due to tool sprawl, lack of actionable insights, and the reactive nature of the tools. Poor customer experience Failures and performance issues are often detected by customers first, leading to frustration and loss of trust. Productive time lost Fragmented tooling and siloed data sources make it difficult to correlate events and understand root causes Rising costs eat into budgets Today's observability tools are reactive by design. You are always catching up to something that has already happened ### Predictive and proactive Modern time series forecasting model predict future trends and anomalies, giving you the power to proactively address issues before they arise ### Unified signals Single source of truth for all your observability signals. Goodbye tool sprawl! ### Compression up to 90% Columnar design for efficient storage and faster queries. Faster insights at a fraction of the cost ### Natural correlation Correlate across signals using natural language or SQL. Hello better insights and faster troubleshooting! ### Faster queries built-in Hybrid execution engine with columnar storage and indexing. Fast queries, no matter the scale ### Our cloud or yours Available wherever you are. Parseable is available as Parseable Cloud and BYOC model ### Open standards Zero vendor lock-in. From OTel to Parquet and object stores, open standards all the way Features that matter Proactive monitoring with forecasting Automatically analyze historical data to predict future trends and anomalies, enabling proactive monitoring and faster incident response Smart event parsing for filtering One click filters to quickly find the relevant data. Smart event parsing automatically extracts key information from your telemetry, making it easy to filter and analyze your data Slice and dice data with dashboards and SQL editor Power users love the SQL interface to slice and dice telemetry data exactly how they want. Use the assistant to generate SQL queries and dashboards in seconds Granular access control & federated IAM Connect with any”

Subject

“Launch HN: Intuned (YC S22) – Build and run reliable browser automations as code https://intunedhq.com Founder's Show HN post: Hey HN, we're Faisal and Ahmad from Intuned (https://intunedhq.com). We’re building a platform for building, deploying, and maintaining browser automations. Customers primarily use the Intuned AI agent to automate websites that don't expose APIs. Common use-cases include scraping data, pulling reports, and submitting forms. As the website changes, our agent also helps automatically heal the automation. On Intuned, browser automations are created by an AI agent and run as code. Our infra captures the context of every run, allowing our agent to debug and maintain the underlying code - to keep the automations working over time. This way, we’re able to offer the predictability, speed, and cost of code, without the painful parts of writing and maintaining it. Here’s a demo of building a scraper on Intuned: https://youtu.be/ruZP73bK4FU Here’s a demo of using AI to maintain a project: https://youtu.be/e4R4hLdHBro Backstory: we were accepted into YC for a completely different idea. During the batch, because of Faisal's background at UiPath, several batchmates asked us whether RPA tools could fill API gaps in their products by automating websites without APIs. When it was time to pivot, we went back to those founders to dig deeper. (RPA in this context is referring to using UI automation to do complete non-testing tasks) We discovered that the actual hard problem in browser automation is maintenance. Websites change, selectors break, and failures can be painful to reproduce and fix. So in early 2024, we decided to take a crack at this problem with a handful of customers. It needed a fair number of iterations before we landed on our current code-first approach. How it works: Intuned is infra + agent, deeply integrated. On the infrastructure side, Intuned is a managed runtime for browser automation code. Projects are usually Playwright-based TypeScript or Python. Users can write them directly in our online IDE, or hand the work off to the agent. Either way, once deploy Landing page content (Reliable Integrations for Services with No APIs | Intuned): Reliable Integrations for Services with No APIs | Intuned # Build integrations for services with no APIs Intuned Agent builds and runs integrations for services that don't have APIs. It does this by either copying the service's network calls or automating a browser - whatever works best. Its platform then runs these integrations at scale and handles logins, captchas, and monitoring for you. ## Scrapers Create a scraper for any website - e-commerce, government portals, job boards, or anything else. Intuned Agent is the first AI Agent designed to build and maintain Scrapers. Intuned Agent generates playwright code that will be fast, cheap and predictable when it runs. Key Features: Intuned Agent - Generate any scraper from a prompt and schema, fix issues with AI when sites change. Enable self-healing and Intuned will monitor and fix your scrapers when they break. Support for authenticated scrapers - Scrape any website even if its behind authentication. Intuned Infra support helps you manage the authentication state as needed. Use Jobs to schedule the scraper runs and send the data to your backend, can be done via webhooks or another sink. Intuned observability saves records and traces for all your runs so you can debug them when something goes wrong. ## Crawlers Discover, navigate, and collect data across thousands of pages. Build crawlers that follow links, parse sitemaps, and index content - with built-in stealth, scheduling, and scale. Key Features: Use TypeScript or Python, use any framework you want. With Intuned, you can deploy any code you want. Crawl4AI support - First-class support for Crawl4AI - deploy and scale your crawlers without managing infrastructure Stealth mode - Anti-detection, proxies, and captcha solving built in Scheduled jobs & monitoring - Recurring crawls with full logs and session recordings Scalable infrastructure - Control how many machines to run on, we handle the rest ## Back Office Automation Automate internal operations in back-office systems that have no APIs. Intuned runs reliable browser automations for data entry, status checks, form submissions, report downloads, and account updates - with auth, stealth, concurrency, and monitoring built in. Key Features: Back-office workflows - Automate repetitive work inside CRMs, vendor portals, admin panels, and legacy systems. Authenticated operations - Intuned manages login sessions and auth state for systems your team already uses. Read, write, and submit -”

Subject

“Launch HN: Freestyle – Sandboxes for Coding Agents https://www.freestyle.sh/ Founder's Show HN post: We’re Ben and Jacob, cofounders of Freestyle (https://freestyle.sh). We’re building a cloud for Coding Agents. For the first generation of agents it looked like workflows with minimal tools. 2 years ago we published a package to let AI work in SQL, at that time GPT-4 could write simple scripts. Soon after the first AI App Builders started using AI to make whole websites; we supported that with a serverless deploy system. But the current generation is going much further, instead of minimal tools and basic serverless apps AI can utilize the full power of a computer (“sandbox”). We’re building sandboxes that are interchangeable with EC2s from your agents perspective, with bonus features: 1. We’ve figured out how to fork a sandbox horizontally without more than a 400ms pause in it. That's not forking the filesystem, we mean forking the whole memory of it. If you’re half way down a browser page with animations running, they’ll be in the same place in all the forks. If you’re running a minecraft server every block and player will be in the same place on the forks. If you’re running a local environment and an error comes up in process that error will be there in all the forks. This works for snapshotting as well, you can save your place and come back weeks later. 2. Our sandboxes start in ~500ms. Demo: https://www.loom.com/share/8b3d294d515442f296aecde1f42f5524 Compared with other sandboxes, our goal is to be the most powerful. We support full Linux + hardware-virtualization, eBPF, Fuse, etc. We run full Debian with multiple users and we use a systemd init instead of runc. Whatever your AI expects to work on debian should work on these vms, and if it doesn’t send a bug report. In order to make this possible, we’ve moved to our own bare metal racks. Early in our testing we realized that moving VMs across cloud nodes would not have acceptable performance properties. We asked Google Cloud and AWS for a quote on their bare metal nodes and found that the monthly cost wa Landing page content (Freestyle - VMs for AI Agents): Freestyle - VMs for AI Agents # Full Linux VMs for AI Agents Built for complex tasks that run for hours, days, or weeks. OpenWork cmux ### Instant Startup A full Linux machine, ready in 65 ms. 65 ms ### Live Cloning Copy a running VM, memory included. ### Pause Pause and resume with your state intact. ### Network controls Set the rules for network access. Default deny Per-VM rules ### Live previews Give your app a URL. Custom domains Managed HTTPS ### Your cloud, connected Connect to your private cloud. ### Nested virtualization Run Docker and VMs inside your VM. ### Your toolchain Install the tools your workload needs. ### Full Linux A full kernel with support for FUSE, eBPF, and more. ## Put your agent to work. Your next project starts with a Linux VM. Onboard onto Freestyle.sh, build an integration with it on a branch, tell me how it did. Copy prompt ## Good questions. Everything else is in the docs.”