Aptible

Our engineering team spent 6+ months getting our AI Agent just right for our SRE team. Now we put together a guide so that you can build your own in 30 minutes 👇 Aptible AI has been a game changer for us because it has the ability to: - Understand and investigate any debugging-related question you ask it in Slack or Microsoft Teams, regardless of your system complexity - Fetch any relevant data about a production issue from your real-time logs, metrics, docs, deployment history, etc. - Return that data back to you in Slack or Teams with links back to the sources (in Grafana, Notion, Datadog, etc.) - Save you a ton of time by letting you to use your brain to interpret data instead of fetch it 😄 Just having the ability to retrieve real-time system information instantly from chat has allowed our team to decrease MTTR (by 22%) with fewer engineers (53% decrease in # of incidents requiring multiple respondents). So, don’t waste 6 months building something that’s already been built for you. Either follow our guide (📌 link in comments) to build your own AI Agent for SRE or try Aptible AI yourself. 👋 Request access to our Agent by connecting with me and sending a DM or by commenting on this post.

Supported by Aptible’s secure infrastructure, Greenspace Health’s behavioral health solution enables providers to make data-driven decisions that enhance mental health outcomes for millions across Canada. By ensuring compliance and scalability, Greenspace delivers accessible, personalized care on a national scale. With Aptible, Greenspace has confidently met every enterprise-level security and privacy audit, making a strong case for purpose-built infrastructure that scales seamlessly. For organizations prioritizing patient-centered outcomes and growth, the success is clear. Is your platform ready for this level of scalability? #privacyaudit #dataprivacy #compliance #healthcaredata

There’s a game-changer for production debugging: AI. So many engineering teams are struggling to launch an AI Agent for SREs, so we wrote a guide on how to build one 👇 Since this summer, we’ve been building our own AI Agent internally to help our team fix bugs, investigate incidents, and resolve production issues faster (and without pulling in other team members or more senior engineers). We did this by creating an Agent that doesn’t try to answer your questions for you or tell you what to do next. Instead, it surfaces all the relevant information that you need to resolve the problem yourself. This has saved our team HOURS of time digging through logs, metrics, docs, recent deployments, etc. And because it’s been so helpful for us, we want to share how we did it 😄 We’ve put together a 3-part guide that shows you how to build your own AI Agent to help production engineers debug and fix production issues as quickly and efficiently as possible. You can find the link to parts 1 and 2 in the comments below 📌 Part one shows you how to: 1. Set up a new application in Chainlit 2. Connect your application to an LLM Part two is how to: 1. Make your Agent faster and add real-time “typing” (similar to ChatGPT) 2. Give your Agent a personality and specialization Stay tuned for part 3 next week! If you want a sneak peek at it, connect with me and send me a DM and I’ll share the link to the private page.

Happy Halloween! 🎃 Managing over 100 Kubernetes clusters—each a unique snowflake with slightly different codebases—sounds like a DevOps nightmare, right? This team was left with only 2 engineers to manage the chaos, and the result? Sky-high AWS bills and endless deployment issues. 📧 Got a similar horror story? We want to hear it. Share your own DevOps nightmares at [email protected] #DevOps #HorrorStory #K8s #AWS #Halloween #DevOpsNightmares

We just figured out a very cool trick to massively cut down on AI hallucination with our AI SRE Agent 🤗👇 We decided to give up on trying to provide the “right answer” and instead started focusing on surfacing the “right data.” To build an AI Agent that actually helped our engineers debug issues, it needed to be accurate AND useful. But what do we mean by “accurate” and “useful”? - 𝗔𝗰𝗰𝘂𝗿𝗮𝗰𝘆 = AI hallucinations are rare to nonexistent; incorrect answers from the AI Agent in production engineering could take down your infrastructure! - 𝗨𝘀𝗲𝗳𝘂𝗹 = surfacing the data that ACTUALLY HELPS engineers; Aptible AI grabs everything needed for troubleshooting and incident response, from realtime logs and metrics to relevant runbooks and recent deployments. If you expect the AI to be accurate and useful in instantly providing THE answer to a given question… good luck. Trying to do so renders the entire concept of an AI Agent for SRE teams risky at best and destructive at worst. Our key to turning the AI Agent into an asset instead of a liability? Allowing AI to do what it does best and let the humans do the rest. - 𝗪𝗵𝗮𝘁 𝗔𝗜 𝗱𝗼𝗲𝘀 𝗯𝗲𝘀𝘁: finding and presenting accurate information from a sprawling mess of data. - 𝗪𝗵𝗮𝘁 𝗔𝗜 𝗱𝗼𝗲𝘀𝗻’𝘁 𝗱𝗼 𝘀𝗼 𝘄𝗲𝗹𝗹: stringing multiple steps of evaluating data together to independently determine the “right” answer. (← This is a hallucination risk for AI, but humans are pretty good at being intuitive. Doubly so if they are looking at the right info!) With the right prompt engineering and tuning, our AI Agent surfaces accurate and useful information from logs, monitoring tools, docs, configuration, and testing scripts right to your chat and into a dynamic dashboard that you can use for the truly gnarly investigations. With the help of the Agent, our engineers can now skip the whole step of digging up the information they need and get right to the analyzing and responding. This has allowed our team to quickly debug the smallest issues and the most complex incidents. ___ P.S. We’ve finally opened our internal AI SRE Agent to other companies who want to test it out. The more testing, the better… If you want to try it out, comment or DM me and let me know 😎

Here’s a list of 18 YC companies with fewer than 500 employees that have posted job openings for DevOps, SRE, Platform, and Infrastructure Engineering in the last 14 days 👀 👇 1. Darrow AI - Top litigators partner with Darrow to access high-value, meritorious cases... and win. - Senior Software Engineer (Data Team) 2. Weekday - At Weekday, we help companies hire engineers vouched by other software engineers. - AI Platform Engineer 3. ElectroNeek - Unlock efficiency gains for business processes with AI-powered automation. - Middle Software Engineer (Argentina) 4. Motion - The app that uses AI to help you get 25% more done. - Software Engineer (Algorithms) 5. Dynamo AI - End-to-end AI performance, security, and compliance solutions for enterprises. - Senior Software Engineer, Core Infra 6. Kular - Compliant-Ready AI for the Enterprise - Founding Software Engineer 7. voize - AI-powered speech-to-text for care documentation. - Senior Software Engineer (Backend) 8. 1910 Genetics - Computational medicines for the world's most difficult diseases. - Senior Software Engineer 9. Reflex - Generative AI-powered accounting automation for businesses - Software Engineer (AI / Open Source) 10. Truewind - AI-powered platform to optimize customer feedback processes - Founding Full-Stack Software Engineer 11. Monterey AI - AI-driven retail compliance with automated workflows - Senior Full-Stack Software Engineer 12. Retail Ready - AI-powered partnership solutions for corporate institutions - Full Stack Software Engineer 13. FirstIgnite - AI software for managing solar installation workflows - Full Stack Developer / Software Engineer 14. Aether Energy - AI-powered automation solutions for restaurant drive-thrus - Senior Software Engineer, Front-end and CAD 15. OfOne (YC W23) - Payment solutions for freight businesses using AI - Founding Software Engineer 16. Tank Payments - AI-driven simulation for engineering and product design - Founding Software Engineer 17. Navier AI - AI-powered marketing solutions delivering efficient campaigns - Rust Software Engineer 18. Kaya (YC S21) - Automated customer service solutions with advanced AI - Software Engineer, Python Links to job postings are in the comments! — 👀 Repost to help those in your network who may be looking for a job. For 2️⃣ weekly job drops (SRE, DevOps / Engineering Leadership) give me a follow: Henry Hund Hiring Managers: Did I miss your job? Connect with me and DM your info for inclusion in the next post!

Stress-free infrastructure management? Yes, please! For hims & hers, Aptible is more than just a platform—it’s peace of mind. 🙏 Managing deployments is made easy, and with zero-downtime restarts, the headaches of handling infrastructure disappear. Petr Hecko, Lead DevOps Engineer, shares how Aptible simplifies DevOps, leaving his team to focus on building, not worrying. If you're tired of infrastructure stress, it might be time for a change. #DevOps #CloudInfrastructure #Aptible #Compliance

🚨 NEW RELEASE ALERT: InfluxDB 2.7 is now available on Aptible, bringing enhanced tools for data visualization and processing with Flux, the data scripting language. Prefer SQL-like queries? No worries! We’re keeping InfluxDB 1.8 available as part of our managed database offering until InfluxDB 3.0 OSS arrives or security concerns come up. We're committed to offering flexibility for all your data needs. Let us know if you’d want to upgrade and read more about these changes in InfluxDB’s release blog post: https://lnkd.in/enzqB4Dq #InfluxDB #SQL #OSS #DevOps #OpenSource #DataVisualization

DevOps handled and HIPAA compliance simplified—all in one platform. Ion Feldman, CTO of Rightway, shares how Aptible’s turnkey solutions and stellar support give his team peace of mind, ensuring we can confidently manage PHI in the cloud. No stress, just seamless compliance and security built for the future of healthcare tech. #HealthcareTech #PHI #HIPAA #HITRUST