AI-native on-call and incident response. Modern Slack and MS Teams native incident management—from your first alert to retrospective. Trusted by 100s of leading companies including NVIDIA, Squarespace, Canva, Grammarly, Elastic, Tripadvisor, and Figma. See why they rate us 5 stars on G2: https://www.g2.com/products/rootly-manage-incidents-on-slack/reviews
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Some things you can automate with Rootly: 🧪 Creating dedicated incident channels, Zoom rooms, and Jira tickets 🧑🏾🤝🧑🏾 Looping in the right teams/responders and assign roles (e.g. Commander) ⏰ Setting reminders and tasks (e.g. updating Statuspage every 30min) 🎤 Communication with stakeholders (e.g. Statuspage, Slack, Email) 📌 Automated postmortem timeline generation and action item tracking 📟 Create and manage on-call schedules and escalation policies 🚨 Page responders directly from Slack 📊 Tracking and visualizing metrics such as MTTR and incident causes 📝 Write postmortems in tools you use like Confluence, Google Docs, and more ...and much more! Will Rootly work with my existing process? Yes! 🔮 Workflow builder lets you customize Rootly (e.g. page Infra and email leadership when incident > SEV1) 🎛️ 70+ integrations across PagerDuty, Opsgenie, Jira, GitHub, Datadog, Zendesk, and API for custom requests
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The Rootly team is headed to Atlanta next week for KubeCon! Come find us at the booth to chat all things reliability. We’re also throwing two happy hours: 🍸 Monday kickoff with Checkly, AuthZed, iTmethods, and Atolio. 🍻 Wednesday with Chronosphere, Thoughtworks, Google Cloud, and Embrace. RSVP links are in the comments. If you end up on the waitlist, DM me.
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At Rootly, it’s become a bit of a tradition to put together the Unofficial SRE Track for KubeCon. After a heated lunch debate last week, we narrowed 300+ sessions down to five must-sees for SREs heading to Atlanta. The list includes standout talks like Vasudev Bongale (LinkedIn, a Rootly customer) on observable rollouts and the Operations Resilience TAG panel with Alolita Sharma. Find our SRE Track in my latest article: https://lnkd.in/gVTJsbbH
Our Unofficial KubeCon NA’ 2025 SRE track is out! After going through the 300+ sessions in the schedule, we’ve narrowed it down to 5 must-see for SREs going to Atlanta: • Making Application Rollouts Observable, Actionable and Boring (Vasudev Bongale, LinkedIn) • Maximizing the Launch Reliability: Ensuring Stable Application Lift-off and Orbit on Kubernetes (Hiroshi Hayakawa) • Beyond the Dashboard: Modern Observability for Platform Engineering at Scale (Whitney Lee, Danielle Cook, Stevie Caldwell, Khallai Taylor, Payal Bagga) • Building Resilient Cloud-Native Infrastructure in the Second Decade: TAG Operational Resilience (Alolita S., Rafael Brito, Mario Fahlandt, Saiyam Pathak, and Nabarun Pal) • But What About Reliability? - The Multi-Million Dollar Kubernetes Cost Optimization Question (Zain M. & Nibir Bora) For times, descriptions, and links to each session check out our blog post (linked below).
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For platform engineers, the AI wave means two things: you need to build with AI and build for AI. And with 75% of platform engineers already running AI workloads or gearing up to, adoption is moving fast, and the learning curve is steep. This paper is both: -a report based on a survey of 300+ platform engineers: what they’re doing, what’s working, and how AI is reshaping the role AND -a practical playbook with best practices for using AI to build platforms and how platforms should evolve to host AI workloads. It's an initiative from the Platform Engineering community, written by an amazing group: Sam Barlien Luca Galante, Ajay Chankramath, Rickey Zachary, and me.😬👋 Big thanks to Kaspar Von Grünberg for bringing me in; I had a blast contributing.
Traditional reliability is built on cause and effect: same code, same infra, same result. Machine learning breaks that rule. You can change nothing and your model still fails. Maria Vechtomova, MLOps Tech Lead, joins Sylvain Kalache, Head of Rootly AI Labs, to unpack why ML systems fail differently from traditional ones and what that means for reliability engineering. Read all of Maria's insights in our latest blog post (linked below).
When operating at scale, figuring out who should get paged isn’t trivial. Especially when teams manage multiple escalation policies or shared services. Rootly makes it simple to route incoming alerts to the right person while giving managers a bird’s-eye view of how paging is distributed across the organization. Learn more in our changelog (linked below).
Attending KubeCon in Atlanta? Join Rootly, Checkly, AuthZed, and more, high above Midtown for a relaxed happy hour at Polaris, the iconic revolving restaurant with panoramic views of the Atlanta skyline. Rotate through 360° city vistas while enjoying greats conversations with SREs, platform engineers, and observability leaders. Expect great drinks, easy networking, and just enough buzz to spark collaboration before the showroom floors open the next day. Register using the link in the comments below.
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Incident response, meet AI assistance. 👋 Rootly’s AI helps engineers investigate, communicate, learn from, and resolve incidents faster — automating root cause analysis, generating clear updates, pulling data from across tools, and coordinating the right individuals, all within Slack. That means fewer dashboards, less context switching, and faster fixes. 🪄 Slack 🤝 Rootly = Agentic collaboration 👉 https://sforce.co/48Fd3Ru
Some incidents call for more hands on deck. With Rootly, you can now page multiple responders at once, directly from Slack or the web. Escalate across on-call schedules, teams, or services to get the support you need with fewer clicks and faster coordination. Read more in our changelog (linked below).
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So proud to share Rootly made #8 of Deloitte’s Fast 50! This one’s for the team, our customers, partners, and everyone pushing reliability into its next era. AI and code assistants are helping teams ship faster than ever…but also adding a whole new layer of chaos. Rootly’s been leading the charge on AI-native incident response, helping SREs stay ahead of that curve. Huge thanks to Deloitte for recognizing the work (and grit) behind it all. Full Deloitte Fast 50 list in the comments ↓