Plans and audits backup retention (grandfather-father-son) policies. Simulates hourly, daily, weekly, monthly and yearly keep rules like restic or borg, lists the restore points you really keep and the gaps between them, and estimates storage and cost now and in 12 months. Flags missed RPO, short history, legal retention gaps, no offsite or immutable copy, stale restore tests and job overlap. Includes a stdlib Python planner with --self-test.
Reviews nginx.conf and site configs for security problems such as TLS 1.0/1.1, weak ciphers, missing HSTS and security headers, the add_header inheritance trap, alias off-by-slash path traversal, autoindex, unlimited body size, $uri in redirects, HTTP without an HTTPS redirect, open admin paths and logins without rate limits. Gives a fixed config. Includes a stdlib Python checker with --self-test.
Rightsizes Kubernetes CPU and memory requests and limits from real usage (p50, p95 and max per container). Recommends requests at p95 plus headroom, memory limits above the peak and no CPU limits, and estimates the cores, GiB and money freed. Flags OOM kills, memory above the request, CPU throttling, missing requests or memory limits, overprovisioning and short data windows. Includes a stdlib Python rightsizer with --self-test.
Plans and checks IPv4 subnet layouts for AWS, Azure, GCP or on-prem networks. Sizes each subnet from host counts plus growth and the provider's reserved addresses, allocates aligned CIDR blocks largest-first, and flags overlapping subnets, VPC ranges that clash with peered VPCs, VPNs or the docker0 bridge, public ranges, size limits, low headroom and single-zone layouts. Includes a stdlib Python planner with --self-test.
Turns request counts into SLO answers: SLI, error budget for a 28d or 30d window, budget consumed and remaining, burn rates over 5m to 3d, multiwindow burn-rate alerts (page at 14.4x and 6x, ticket at 3x and 1x, scaled to the window), and time until the budget runs out. Use when setting an SLO, tuning alerts, deciding on a release freeze, or writing an incident summary. Includes a stdlib Python calculator with --self-test.
