Product
Introducing Sonar: Real-time FinOps
Sonar brings cloud and AI cost monitoring together with the speed of streaming data, giving engineering teams one place to see every dollar leaking out.
BlogUpdated on January 15, 2025•4 min read
Read how we approach engineering here at Sonar.
Sonar brings cloud and AI cost monitoring together with the speed of streaming data, giving engineering teams one place to see every dollar leaking out.
Data transfer fees can quietly bloat your cloud bill when cross-region traffic and replication are left unmonitored. Here is how to spot them early.
Token usage spikes, legacy models, and retry storms can double your monthly OpenAI costs overnight. Here is how to detect the culprits.
Detecting cost spikes in real-time requires streaming CloudWatch metrics, not daily exports. Here is our approach to catching $500 surprises before they become $5,000 problems.
Reducing token usage by 40% is possible with prompt engineering, model selection, and caching strategies. Here is how we do it at Sonar.
Startups often ignore cloud costs until they become a problem. Here is why early FinOps practices can save you from painful budget cuts later.
Most EC2 instances are over-provisioned. Here is how to use CloudWatch metrics to find the perfect instance size and cut costs by 30-50%.
Rate limit errors trigger automatic retries that can double your API costs. Here is how to implement smart retry logic and exponential backoff.
S3 storage costs can balloon if you never delete old data. Here is how to set up lifecycle policies that move data to cheaper tiers automatically.
How we built Sonar to stream AWS and OpenAI costs in real-time without breaking the bank. A deep dive into our technical architecture.
Tags are the foundation of FinOps, but most teams tag inconsistently. Here is a tagging strategy that actually works for cost allocation.
GPT-4 costs 10x more than GPT-3.5, but sometimes it's worth it. Here is how to decide when to use each model based on your use case.
Lambda costs depend on memory allocation, execution duration, and concurrent invocations. Here is how to optimize all three dimensions.