Why Your AI SRE Agent Is Stuck on Read-Only
Most AI SRE agents are stuck on Read-Only — not because teams lack trust, but because raw telemetry offers no causal context to act on with confidence.
How Humm Group Delivered Flawlessly in a High-Stakes Product Launch
Launching a new fintech product required certainty across a complex microservices platform. With Causely modeling cause-and-effect relationships across services, Humm Group gained system-level understanding and confidence that critical dependencies behaved correctly during launch.
Reliability Is Managed In Services, But Felt In Transactions
Reliability is managed in services, but users experience outcomes. In complex, multi-service and AI-driven architectures, systems can look healthy in isolation while end-to-end workflows still fail. Product reliability needs visibility at the level of transactions and flows.
Alerts Aren’t the Investigation: What Comes Next in Incident Response?
Alerts are signals, not explanations. By explicitly mapping alerts to symptoms and inferred root causes, Causely turns alert noise into a coherent explanation of what is actually happening in the system.
How to Turn Slow Queries into Actionable Reliability Metrics with OpenTelemetry
Slow SQL queries degrade UX and reliability. This guide shows how to distill OpenTelemetry DB spans into actionable metrics: build span-derived slow-query dashboards, rank queries by traffic impact, and detect regressions with anomaly baselines, so you fix what matters first. Hands-on lab included.
When Asynchronous Systems Fail Quietly, Reliability Teams Pay the Price
Causely’s causal model has been expanded for asynchronous messaging systems. Instead of treating queues as opaque buffers, Causely models messaging infrastructure as it operates in production, making asynchronous failures explicit and explainable.
Alerts Aren’t the Investigation
Alerts are supposed to start an investigation. Too often, they start translation: what is the system doing right now? That translation slows containment, splinters context, and stretches customer impact.
Queue Growth, Dead-Letter Queues, and Why Asynchronous Failures Are Easy to Misread
Asynchronous pipelines sit at the core of most modern systems. Message brokers accept traffic, consumers process it in the background, and downstream services depend on the results. When these systems fail, the failure rarely shows up where it starts.
Slight Reliability EP 113: AI Use-cases for SRE with Shmuel Kliger
Originally published to the Slight Reliability Podcast.
Causely Expands Datadog Integration to Deliver Causal Intelligence Across Hybrid Environments
Causely’s expanded Datadog integration turns Datadog APM signals into system-level causal intelligence, helping teams understand how issues propagate across services and pinpoint true root cause.
Thank You, FluxCD: How it helps us, and how you can use it too!
How Causely uses FluxCD and GitOps to ship weekly on Kubernetes, keep clusters in sync, and wire up OpenTelemetry and Causely in a hands-on lab you can copy.
Causely Named a Gartner Cool Vendor in AI for IT Operations 2025
Gartner recognized Causely for maintaining a live causality graph and using continuous inference to identify the underlying driver behind changes in golden signals as they emerge, even when failures cascade across multiple services.