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Martin Mao shared thisI’m super excited to announce that Chronosphere is now Cortex XCOR - our next-generation, AI-native observability platform that provides automated root cause analysis and remediation. Chronosphere was the best placeholder name that Rob Skillington and I could think of on short notice as the company name choice was the main thing blocking investors from wiring us money early on. We thought we would change it later, but we never did - it grew on us and has served us well over the years. It became a huge part of our personal identities and was the title of that rewarding chapter of our lives. It is fitting that we have a new title and name for this next chapter: Cortex XCOR. However, it’s not just a new name / rebrand - it’s the biggest release of our platform ever. One where we reimagined the Observability experience and aimed to deliver the holy grail - a solution that automates root cause analysis and gives you the answer. You’ve probably seen a ton of solutions claiming this along with cool demos, but what impresses me most about what the team has been working on are the results we’re seeing in large production environments: investigations completed in under three minutes on average with a 75% success rate in identifying the root cause. For those who are still concerned about the economics of Observability, don’t worry - we haven’t abandoned our core principles. We’re still helping our customers optimize their data volumes by 89% on average, earning the top ranking Observability platform for cost efficiency and the trust of industry leaders like DoorDash, Affirm and OpenAI. Read more about XCOR in my blog post: https://lnkd.in/gsF7D6cZ
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Martin Mao shared thisI’m thrilled to welcome Michael Cremen to Chronosphere as SVP of Sales! Michael brings an impressive track record of developing sales organizations and driving tremendous growth. As we expand Chronosphere into a full-stack observability platform for Cloud and AI-native enterprises, it’s critical to have a leader who understands the observability space, our customers and how to scale a high-performing GTM organization. I've been searching for the right person for this role for over a year and Michael not only fits the bill, but was one of the rare cases where 100% of backchannels talked about what a great leader and human he was - from those who worked for him, with him or saw him lead from a distance. Welcome, Michael - I look forward to building a multi-billion dollar business with you!
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Martin Mao shared thisHappy to announce the official close of the acquisition of Embrace and a big welcome to Eric Futoran, Fredric Newberg, Andrew Tunall and the entire Embrace team! We’ve been partnering with the Embrace team for many years now, but I’m excited for an integrated solution that extends Palo Alto Networks' observability platform to the end user. This will give our customers real time visibility to the interactions with their mobile and web apps. These capabilities become even more critical as we enter the agentic era and build experiences for both humans and AI agents. I’m looking forward to all the great things we’re going to build together - let’s go!
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Martin Mao shared thisFull visibility is critical to maintaining reliability for modern applications, yet legacy tools are fragmented, expensive, and often miss actual breaks in the user experience. We built the Chronosphere Observability platform to provide deep visibility into applications and infrastructure, but this is only part of the picture. Today, I’m thrilled to share that Palo Alto Networks has announced its intent to acquire Embrace, a pioneer in high-fidelity Real User Monitoring. Eric Futoran, Fredric Newberg and Andrew Tunall created Embrace to offer innovative RUM capabilities for modern environments. Alongside Embrace’s user-focused RUM, we are also introducing Synthetics, a new capability built with our Autonomous Digital Experience Management (ADEM) team to proactively validate app performance from anywhere globally. By combining Embrace’s front-end capabilities and proactive Synthetic monitoring with Chronosphere’s backend visibility and analytics, we will deliver a full-stack solution that eliminates blindspots and prevents downtime. Additionally, with Cortex AgentiX, we will enable customers to automatically fix issues across the entire digital ecosystem, from mobile and web devices to cloud infrastructure. Learn more: https://lnkd.in/gbrhZn_CPalo Alto Networks to Extend Leading Observability Platform with Innovative Digital Experience Monitoring | Palo Alto NetworksPalo Alto Networks to Extend Leading Observability Platform with Innovative Digital Experience Monitoring | Palo Alto Networks
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Martin Mao shared thisI’m proud to share that Chronosphere is recognized as a Leader in the Gartner® Magic Quadrant™ for Observability Platforms for the third consecutive year! Modern cloud and AI native architectures enable unprecedented agility, but one unintended consequence is the massive amount of Observability data they produce. As companies scale, legacy monitoring platforms force them to choose between critical visibility and unpredictable budget overages. We designed Chronosphere to solve this exact problem. It now helps our customers optimize telemetry volumes by an average of 89%, earning the top ranking for Observability Cost Control in the 2026 Gartner® Critical Capabilities™ report. Get a copy of the report here: https://lnkd.in/gaX5Gy_SChronosphere is a 2026 Gartner® Magic Quadrant™ LeaderChronosphere is a 2026 Gartner® Magic Quadrant™ Leader
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Martin Mao shared thisIt’s official. Chronosphere has joined Palo Alto Networks! Today marks the beginning of an incredible new chapter for our team, our technology, and the future of observability. When Rob Skillington and I started Chronosphere 6 years ago, our goal was to solve the most complex observability challenges for cloud-native enterprises. By joining the global cybersecurity leader, we are now positioned to solve those challenges at an unprecedented scale. To the Chronosphere team: I couldn’t be more proud of you all and what we’ve achieved. I’m even more excited to see what we will build as part of Palo Alto Networks. To our customers and partners: Our mission to provide the world’s most powerful observability platform remains unchanged, and our ability to execute has just been supercharged. We look forward to continuing this journey with you. We are ready to hit the ground running and accelerate the move toward autonomous remediation with Cortex AgentiX. Thank you again Nikesh Arora, Lee Klarich, and Dipak Golechha for the warm welcome and for your partnership. Day one - let’s go! https://bit.ly/4sZNan3
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Martin Mao shared thisA momentous day for Chronosphere: I’m thrilled to announce that we have entered into a definitive agreement to be acquired by Palo Alto Networks! When Rob Skillington and I started Chronosphere 6 years ago, we set out to build a next-generation observability platform capable of handling the most complex Cloud Native workloads. Today, we are the observability leader trusted by the world’s top AI and digital-native innovators. A huge thank you to our customers for trusting us, to our partners and investors for supporting us and most importantly, thank you to the incredible team here at Chronosphere who made this possible. These past few years have been an amazing journey with you all and we’re definitely not done! Joining Palo Alto Networks, the global cybersecurity leader, will allow us to accelerate our mission. On the heels of our ‘AI Guided Troubleshooting’ launch last week, I’m super excited about expanding from autonomous investigation to autonomous, agent-driven remediation of issues with Cortex AgentiX. Thank you Nikesh Arora, Dipak Golechha and Lee Klarich for believing in our vision and trusting our execution - Rob and I are excited to lead the team into this next chapter! https://lnkd.in/giAaKdz7Palo Alto Networks to Acquire Chronosphere, Next-Gen Observability Leader, for the AI EraPalo Alto Networks to Acquire Chronosphere, Next-Gen Observability Leader, for the AI Era
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Martin Mao shared thisSuper excited to be sharing a major update of our product today and something we've been working on for a while! It's no secret that AI is changing the world and disrupting many industries. Observability is no different and here at Chronosphere, we've been busy figuring out the best way to improve Observability outcomes with AI - not just AI-washing our product. We believe in a future world where most root cause analysis and remediation is automated in an agentic way, but there are practical technical barriers that prevent effective results (hint: you can't just unleash the LLMs on the raw data). That's what we've been focused on solving as well as optimizing for this transitionary period where trust in a new way of doing things needs to be built and tribal knowledge needs to be captured by the system. Read more about it below or if you're around at Kubecon this week, we'd love to show you what we've been working on! https://lnkd.in/gJ7fKyxxObservability in transition: Building confidence on the path to agentic workflowsObservability in transition: Building confidence on the path to agentic workflows
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Martin Mao shared thisThanks for having me on Kevin S Lin, it was great fun chatting with you!Martin Mao shared thisNew Founders Table Episode with Martin Mao, founder of Chronosphere Chronosphere is a modern observability platform focused on cloud native architecture and fine grained control of observability data. In our conversation, we discuss: - skipping the seed stage and directly raising a series A with an 80-page business plan - the challenges of cloud native architectures: more data, more cost, more issues - understanding actual market needs vs theoretical projections Catch the full episode on the founders table podcast where ever you get your podcasts! https://lnkd.in/g-6JK6Ys
Martin Mao replied to a comment
6h
Shan Huang For the remaining 25%, when it's not sure, but has useful information, it will give the useful information - that happens 19% of the time. The remaining 6%, it says it doesn't know - not all issues can be detected in Observability data alone.
I agree with you on building trust, but what we've seen is that having it run the analysis and show it's work is helpful, even in the cases it doesn't know the exact root cause. Conversely, I'm not sure blindly running a human written playbook (if it even exists for the alert or is up to date) has a better than 94% success rate.
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