Engineering Blog

DoiT joins the Tokenomics Foundation as a founding member, bringing the runtime measurement experience behind Attribute to help define open standards for AI spend attribution and governance.

DoiT's talent acquisition team, paired with one embedded Applied AI engineer, now ships production software: an AI job description builder, candidate screener, sourcing tool, and more.

GKE's new CPU startup boost lets you give containers extra CPU during initialization, then scale back to baseline in place—no more over-provisioning for JVM warm-up.

DynamoDB is one of AWS's most powerful databases — but most teams that struggle with it are making the same schema design mistakes. Here's what to know before you build.

Kubernetes jobs creating metric loss and cardinality explosions? Learn how vmagent streaming aggregation solves observability for ephemeral workloads at scale.

Tokenomics is the discipline of measuring and attributing AI token consumption to customers, features, and agents. Here's why traditional FinOps tagging breaks down for AI spend.

Part 2 of our Iceberg data lake series walks through the hands-on implementation: deploying Debezium Server on GKE to replicate Postgres into Iceberg tables on GCS.

AI infrastructure breaks the tagging and SDK playbook that powered traditional cloud cost allocation. Kernel-level eBPF measurement offers a structural fix without code changes.

eBPF sensors run sandboxed programs inside the Linux kernel to observe every syscall, packet, and GPU interaction. Here's why they're becoming the foundation for modern AI cost attribution.

Tokens tell you what AI costs, but not why. A former FinOps practitioner explains why attribution — not tagging — is what turns cost numbers into real business decisions.