Vertex AI TensorBoard
Does ZopNight manage Vertex AI TensorBoard?
Vertex AI TensorBoard bills per GB of stored experiment data, a storage-based model in effect since 2023. Old experiment logs accumulate indefinitely unless pruned, so the meter only grows. ZopNight inventories TensorBoard instances through Cloud Asset Inventory and counts their storage in ML cost attribution.
Rules that fire on Vertex AI TensorBoard
A Vertex AI TensorBoard instance stores and visualizes ML experiment data, billed per GB of experiment data stored. Old experiments accumulate storage indefinitely unless pruned.
Experiment logs metered by the gigabyte
Vertex AI TensorBoard has charged on stored experiment data since its 2023 move to storage-based pricing, so cost tracks the volume of scalars, histograms, images, and profiling traces that training runs upload. Nothing expires on its own. Every run adds to the corpus, deletion is manual, and the meter ratchets in one direction until someone prunes, which makes this one of the few Vertex resources whose bill is a pure function of housekeeping.
TensorBoard inside ZopNight’s cost attribution
ZopDev inventories TensorBoard instances via Cloud Asset Inventory and includes their storage in ML cost attribution. That placement puts experiment-tracking overhead next to the training jobs that generated it, so a team’s true experimentation cost (compute plus the telemetry retained about that compute) reads as one attributable figure instead of two scattered line items.
Log hoards from finished research
The failure mode is pure accumulation. Profiling runs get captured at full verbosity for a debugging session and never revisited. Hyperparameter sweeps log hundreds of trials of which exactly one mattered. Shared instances collect experiments from whole teams, and shared ownership means nobody feels responsible for deletion. Because the stored data informs no running system, pruning is risk-free in a way most cloud cleanup is not. The only cost of deleting a two-year-old experiment log is sentiment.
TensorBoard instances in the console
Google Cloud console → Vertex AI → Experiments surfaces TensorBoard instances and their experiments per region. Sorting experiments by last-update time separates living research from archives in a single glance, and the archives are where the stored gigabytes concentrate. Instance-level inventory also catches TensorBoard resources left behind in projects whose training moved elsewhere, where even modest storage is pure residue.