Dynasight

Problem

DynamoDB waste can hide in table and index configuration.

How it works

Detects expensive tables, unused or underused GSIs, and overprovisioned provisioned-capacity tables.

Result

Teams get review candidates for cost-saving changes.

Why

These conditions may continue creating storage, write, or unused-capacity costs.

Problem

Frequent scans and late filtering can increase reads and latency.

How it works

Surfaces scan-heavy workloads and FilterExpression misuse alongside table-design context.

Result

Engineers can investigate more targeted query paths, index strategies, or table design changes.

Why

These patterns can signal that existing keys, indexes, or query paths do not fit the workload.

Problem

Raw monitoring signals do not form an actionable backlog.

How it works

Ranks findings by impact, confidence, and engineering context, with plain-English risk and review guidance.

Result

Monitoring becomes a prioritized optimization backlog.

Why

Teams need to decide which cost and performance issues deserve attention first.

Problem

Production audits must not change AWS resources automatically.

How it works

Connects through a read-only AWS IAM role and does not make automatic AWS changes.

Result

Engineers review and implement changes on their own terms.

Why

Teams can inspect DynamoDB safely while retaining control of remediation.

Problem

Optimization work can disappear after an initial review.

How it works

Keeps resolved findings visible and supports sharing findings with the team.

Result

Progress remains trackable over time.

Why

Teams need continuity across cost-review and remediation work.

Features