4 ways our Causal Reasoning Platform is transforming the way DevOps and SRE teams operate: 1️⃣ Incident response is accelerated, thanks to machine-speed root cause analysis 2️⃣ Causal remediation is automated 3️⃣ Postmortems are streamlined (or better yet, made obsolete!) 4️⃣ Unintended consequences of application changes are prevented Learn more about top use cases for Causely ➡ https://bit.ly/4bYVj1e
Causely
Software Development
Enabling self-managed, resilient applications by bridging observability with automated orchestration
About us
Causely assures continuous application performance and reliability. Our Causal Reasoning Platform automatically captures cause and effect relationships based on real-time, dynamic data across the entire application environment. We're hiring - join us!
- Website
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http://causely.io
External link for Causely
- Industry
- Software Development
- Company size
- 11-50 employees
- Type
- Privately Held
- Founded
- 2022
- Specialties
- causalAI, causality, rootcauseanalysis, devops, and cloud
Employees at Causely
Updates
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"Lags and missing data can be silent assassins, causing unseen disruptions that ripple through various industries." Andrew Mallaband discusses the ways these issues can impact different sectors and introduces Causal AI for DevOps in this post ⤵ https://bit.ly/3WENKHN #causalai #causalreasoning #devops
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This post provides specific examples of how seemingly minor bottlenecks -- such as a degraded microservices, message queue backups, cache misses, and kubernetes lags -- can snowball into major UX problems. 🚨 Spoiler alert: our Causal Reasoning Platform can help! https://lnkd.in/ez63UE9M
Real-time Data & Modern UXs: The Power and the Peril When Things Go Wrong
Causely on LinkedIn
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Causely reposted this
In his latest Observability 360 newsletter, John Hayes highlights a recent LI debate kicked off by Josh Grose: "Observability in the Dock" - challenging the approach observability vendors have been taking for decades (https://lnkd.in/ecyiXdfH). These challenges are what compelled us to start Causely, and why the deep expertise of Shmuel Kliger and our team in #causalreasoning is so critical to what we’re building. In the world of cloud-native applications and real-time data, every second of service disruption can have serious impact. While more metrics/logs/traces and better dashboards can improve observability tools, it still always comes down to *humans* interpreting the data and sifting through alerts to understand what’s happening - usually after the fact. What the industry actually needs is causal reasoning software (not humans) for the resolution and prevention of complex problems. This offers a significant leap forward by: - Rapidly identifying root causes and their effects - Providing more consistent and explainable answers - Prioritizing actions based on a clear understanding of user impact - Preventing future incidents by showing potential problems and what-if scenarios To learn more, check out this article: https://bit.ly/3Y3NYdD. Better yet, try Causely in your live environment to see the difference: https://bit.ly/4cY83pW.
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The adoption of cloud-native technologies and microservices architectures mean that seemingly minor issues can quickly snowball. Every second of service disruption matters. This post from Andrew Mallaband provides examples of this and explains how #causalAI for #devops can help.
Beyond the Blast Radius: Demystifying and Mitigating Cascading Microservice Issues
Causely on LinkedIn
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We at Causely have adopted #OpenTelemetry within our own platform, which prompted us to share a production-focused guide. Hopefully this helps practitioners get started with OTel and the OTel Collector as part of a broader strategy to build resilient applications. 💪 #devops #otel #cloudnative
Using OpenTelemetry and the OTel Collector for Logs, Metrics, and Traces
Causely on LinkedIn
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Welcome aboard, Francis Cordón -- an amazing addition to the team! We're so excited you're here. 🚀
Passionate about fulfilling the promise of Continuous Application Reliability. Placing human empathy at the center. Key contributor to three successful SaaS exits
I’ve spent a lifetime in the application performance management space, now part of Observability. I prefer to call it application resiliency, a term I learned from David Lewis, as his vendor at Dynatrace and his employee at BNY Mellon. Some years ago, after many years with industry pioneers like Mercury Interactive, Compuware and Dynatrace, I made a bold move to the customer side. When BNY Mellon asked me to oversee performance for all applications across the Bank's LOBs, I was both excited and daunted. There, I invested heavily in vendor technologies. Despite multi-million dollar investments in tools, it took us hours and hundreds of people in war rooms to determine the root cause and remediation steps. Then, we had the tough job of explaining the penalties and next steps. It’s not that these technologies failed—they offered unprecedented visibility into application tiers we didn’t have before! However, they weren’t designed to instantly separate root causes from symptoms. They provided data, but we still needed my talented team—almost 70 brave souls I feel so thankful for (I couldn’t have done it without them!)—to interpret and act on it. And now it is more difficult than ever due to cloud native environments and microservices. I dream of something better—continuous application service assurance with no disruption, at all! When I left the Bank, I joined Shmuel Kliger to tackle this issue at the infrastructure level for virtual and cloud environments, which we did, at IBM Turbonomic! And now, enter Shmuel, once again! I’m thrilled to announce that I’ve joined Causely to tackle the problem I’ve been gearing up to solve my entire career: ensuring continuous application reliability without disruption. At Causely, we aim for our Causal AI, not humans, to consume observability data, ensuring seamless service performance and business continuity. A huge thanks to Shmuel Kliger, Ellen Rubin, Aaron Holiday, Peter Bell, Daniel Karp, Endre Sara, Enlin Xu, Christine Miller, Akhand Singh, Brandon Kearns and the entire Causely Team for believing in me and giving me this chance to 'come back'. And to my friends out there, stay tuned! I also want to express my gratitude to my friend and mentor Mark Treschl, and to Mario Ciabarra, Glenn Trattner and Quantum Metric for allowing me to grow and learn over the past 4.5 years in one of my best professional experiences ever, where I was inspired by translating technology to human empathy, and working with the single best Customer Success Team I know of. I couldn’t be more excited to join this team I fully trust - the same thought leadership that addressed this in network management at Smarts (now EMC) and infrastructure and cloud at IBM Turbonomic. This has been ~30 years in the making! And it is NOW here. I changed my entire life and my career to come here - if you are curious about it, send me a message and let’s chat! https://www.causely.io/ 🙏🏽 #Causely #CausalAI #SRE #DevOps #Kubernetes
Causal AI for DevOps | Causal Reasoning Platform
https://www.causely.io
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Curious about Causely? Our #causalAI platform assures continuous reliability of #cloud applications by automatically capturing cause and effect relationships based on real-time, dynamic data across the entire application environment. This means that we can detect, remediate and even prevent problems that result in service impact. Watch the demo to see the causal AI platform in action. We'd love your feedback -- comment with your thoughts or tag someone you know that could benefit! https://bit.ly/4ewxzV1 #ITOps #DevOps
Causely Demo - Causal AI Platform
https://www.causely.io
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This is a great illustration of the painful work we're working to automate at Causely, so Isala Piyarisi and others like him spend less time on troubleshooting and postmortems, and more time developing.
I just shared a write-up explaining how one bad Cilium config took down one of our clusters, 8 months after the initial deployment. A ticking time bomb, if you will. https://lnkd.in/gfXvZTzY
Learned it the hard way: Don’t use Cilium’s default Pod CIDR
medium.com
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"Lags and missing data can be silent assassins, causing unseen disruptions that ripple through various industries." 🌊 🌊 🌊 Andrew Mallaband unpacks several hidden culprits that can cause issues to real-time data streams with far-reaching implications in this post: https://bit.ly/4cbMiDi
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