Blogs & Articles
In-depth articles on streaming telemetry, in-flight correlation, and advanced SLA monitoring for modern observability pipelines.
Why the Log-Cost Playbook Needs to Change
Discounts, sampling, shorter retention, and cheaper archives each rest on an assumption. The better question is how much useful information you can preserve while the downstream system processes less.
Correlate related activity in flight, then choose lossless reconstruction or a rich summary. Events outside a policy pass through untouched.
The Part of Your Splunk Bill No Tool Has Been Allowed to Touch
Audit, access and transaction indexes cannot be dropped, sampled, or expired early. Lossless consolidation keeps the same searches, the same rows, and the same panels on a smaller index.
One macro returns every event. What this article shows on our dev cluster, the verification report measures on yours.
How Chiron Changes AI Incident Investigation on ORCA-bench
On 526 public incidents, Claude Sonnet 4.6 with Chiron named every expected root cause in 46.2% of cases, using 154K tokens per trial. The replay kept 27 MB of investigation state from 12.5 GB of telemetry.
Chiron prepares incident context before the agent asks its first question. This is a tuned evaluation, not a zero-shot comparison with the published reference.
How Stream-First Observability Achieves Live Streaming Reliability at Scale
The Problem: Your team spends hours manually correlating CDN logs, SSAI traces, and QoE beacons during live streaming incidents - while viewers churn and ad impressions are lost.
The Solution: A stream-first architecture that pre-computes causal chains as data arrives, delivering a root cause diagnosis in minutes, not hours and at a fraction of the cost.
Custom Window Operators for Observability-Native Stream Processing
Learn how Chiron's purpose-built observability platform uses custom window operators, watermark-free architecture, and adaptive granularity to deliver real-time monitoring that general-purpose stream processors like Apache Flink can't match.
When building real-time monitoring systems, the choice between general-purpose stream processing and purpose-built solutions isn't just technical, it's strategic.
Traces in Chiron
Learn how Chiron's purpose-built observability platform uses traces to deliver real-time monitoring that general-purpose stream processors can't match.
Traces are great at showing where latency or errors happen. In production, the harder part is getting to `why` quickly, without a trace-volume explosion that drives up cost.
