? It's time to improve the reliability of critical services in your environment. Don't wait until something fails to do something about it! ?? We're now offering complimentary reliability assessments, where we'll analyze your environment's dependencies and show you opportunities to improve reliability. You'll walk away with: ?? A service dependency view of your key service topology and associated cause-and-effect relationships. ?? A better understanding of your critical services environment's ability to withstand application updates and changes. ?? A recommendations report?with specific actions to prevent SLO violations. From quick wins to strategic improvements, we'll lay out a clear path to stronger, more reliable services. Learn more or sign up ?? https://bit.ly/417Tlbt
Causely
软件开发
New York,NY 1,258 位关注者
Assuring continuous service reliability with causal reasoning software
关于我们
Causely assures continuous application performance and service 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!
- 网站
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https://causely.ai
Causely的外部链接
- 所属行业
- 软件开发
- 规模
- 11-50 人
- 总部
- New York,NY
- 类型
- 私人持股
- 创立
- 2022
- 领域
- causalAI、causality、rootcauseanalysis、devops和cloud
地点
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主要
US,NY,New York
Causely员工
动态
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With Google NEXT just around the corner, Causely is thrilled to announce that we're now officially live on the GCP Marketplace! Google Cloud #GoogleNEXT #GCPMarketplace #CloudNative #DevOps #SiteReliability #Causely #Observability #SRE #PlatformEngineering #ai #genai
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According to Grafana Labs' 3rd annual #observability survey, nearly half of organizations say observability is a business-critical concern among senior execs, and 39% say its biggest impediment is complexity/overhead. ?? in comments for (ungated!) access to the survey report and a slick Grafana Play dashboard where you can explore the data on your own ?? ??
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Implementing OpenTelemetry at the core of our own #observability strategy was a natural decision. Endre Sara shares the back story in this post: ?? Eating Our Own Dogfood: Causely's Journey with OpenTelemetry. (?? in comments)
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?? Who else is en route to #SREcon? Don't forget to visit Causely at booth #13 to learn more about how our Causal Reasoning Platform can help you automate service reliability. We'll also have sweet swag and the chance to win a Meta Quest 3! What are you hoping to get out of the show?
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"Causely's founder, Shmuel Kliger, has been thinking about the frustrations in observability (which was once called monitoring) for decades... His opinions are blunt and straightforward about machines handling some tasks better than humans, and he says that we should embrace the opportunities for software to help engineers solve problems faster." ?? Read the rest of the Tech Times article ( ?? in comments). #opentelemetry #observability #causalreasoning
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? Happening in 1 hour! ? Tune into the AMA between Viktor Farcic and Endre Sara - you'll probably learn something and be entertained too. ??
??? Endre Sara will be joining the legendary Viktor Farcic for an Ask Me Anything session on DevOps Toolkit this Thursday at 3pm ET! Bring all those lingering questions about Kubernetes, devops, platform engineering... or just bring popcorn and tune in for the banter ?? https://lnkd.in/erPBxgMi #DevOps #DevOpsToolkit #kubernetes
Ep15 - Ask Me Anything About DevOps, Cloud, Kubernetes, Platform Engineering,... w/Endre Sara
https://www.youtube.com/
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"OpenTelemetry is shifting accountability and ownership of telling me what's going on from the management software to the application itself to the application developer... Now we have a lot of valuable information about the application... but this comes with a cost." Hear more from Shmuel Kliger ?? check out his Techstrong TV interview with Alan Shimel https://lnkd.in/e4AMGn7J #observability
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Causely转发了
Beyond Observability: How Causely is Revolutionizing Service Reliability In this latest VMblog Q&A, Yotam Yemini, CEO of Causely, explains why traditional observability tools show you what is happening, but fail to reduce the cognitive load of figuring out why issues occur. Causely's approach is different: ?? Purpose-built, model-driven #AI system ?? Reasoning about cause-and-effect relationships between services ?? Automatic instrumentation with zero configuration ?? Immediate visibility into service dependencies and reliability risks "Engineering teams spend 25% or more of their time firefighting service reliability issues; that's time that could be spent building and shipping product or just enjoying some well-earned downtime," notes Yemini. Read the full Q&A to learn how Causely is solving problems that traditional observability platforms can't address: https://lnkd.in/eC5_uCWx #CloudNative #DevOps #Observability #ServiceReliability #AIforDevOps