Causely provides a Causal Reasoning Platform that automatically pinpoints root causes of issues in cloud-native application environments based on observed symptoms.

Causely

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!

Amity Ventures

Our experience adopting #OpenTelemetry within our Causal Reasoning Platform prompted us to share a production-focused guide to help #DevOps, #engineers and #SREs get going with OTel and the OTel Collector as part of a comprehensive strategy to monitor and observe applications. Here it is ⤵ 
https://bit.ly/46KmGv4

Recent research from PagerDuty underscores the need for -- and current lack of -- automation in application environments. Ellen Rubin shares her perspective here.

The latest episode from Andrew Mallaband covers the importance of explainability in causal reasoning software. How critical is the explainability of models running in your environment? What workloads or use cases do those models support? Comment below 👇 

#causality #rootcauseanalysis

Experience Causal AI for #DevOps first-hand-- take the new self-guided tour of our Causal Reasoning Platform and let us know what you think! Comment below or DM us directly with feedback 👇

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

"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

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

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.

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.

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

IO:CAUSELY

Causely

name

homepage url

country

linkedin url

sector

industry

monthly webtraffic

monthly webtraffic growth

Description

investor of

Metrics