Quality, incidents & reliability
Incident dynamics, CI assurance, reliability growth, and where observability spend earns its keep.
17 of 388 tools.
Audit CI pipeline evidence integrity
Audit the complete point-in-time change-to-pipeline-to-job-to-rerun cohort, exposing missing CI, orphan records, future leakage, inconsistent required-job outcomes, incomplete provider evidence and same-configuration fail-then-pass flake proxies without scoring people.
Audit incident learning evidence integrity
Audit the complete point-in-time incident-to-postmortem-to-corrective-action lineage, separating missing or contradictory evidence from genuine overdue learning debt without attributing individual fault.
Audit operational alert decision integrity
Audit every point-in-time operational alert evaluation by recomputing fire/suppress decisions and verifying effective policy, cooldown, evidence freshness, context, controls, severity routing, acknowledgement, action and mature outcome lineage.
Audit root cause traceback evidence integrity
Audit whether an anomaly traceback is complete, point-in-time, multiplicity-controlled and honestly labeled as temporal or causal, including every upstream candidate, path lag, edge identification basis and later root-recovery validation.
Estimate software reliability growth
Estimate long-run software reliability growth with a power-law nonhomogeneous Poisson process, bootstrap trend evidence, and future incident exposure.
Estimate transportable root cause probability
Estimate how likely a mechanism actually caused an observed failure using transport-weighted Bayesian random-effects MCMC across remediation studies, posterior probability of necessity, convergence diagnostics and mandatory unmeasured-confounding sensitivity.
Fit incident hawkes process
Estimate incident aftershock dynamics with a stationary exponential Hawkes process and conditionally simulate near-term incident counts.
Forecast alert fatigue and missed risk loss
Forecast alert storms, duplicate notifications, aggregate attention-state saturation, missed material conditions, interruption cost and financial VaR/CVaR with a Markov-modulated Gamma-Poisson and compound log-normal model.
Forecast CI feedback loop economics
Forecast company-local CI feedback delay, compute spend, terminal failure and governed post-release escape loss with hierarchical Dirichlet/Beta outcomes, log-normal feedback, runner-queue amplification, coherent common shocks and strict latest-period validation against global baselines.
Forecast incident learning debt economics
Forecast how much corrective-action debt will remain open and what recurrent incident and operating loss it may create using hierarchical closure, recurrence and severity models that must beat global baselines on the latest whole period.
Infer competing root cause posterior
Rank competing, compound and unknown root mechanisms from company-local resolved incidents using partially pooled Dirichlet-Beta learning, strict temporal holdout scoring, reliability-tempered signals and posterior uncertainty rather than a single brittle traceback winner.
Optimize attention aware alerting portfolio
Choose one governed alert policy per risk class with Erlang-C response queues and Monte Carlo risk, maximizing protected value net of missed/common loss, false-alert interruption, operating cost and CVaR under hard evidence, quality, response, budget, relation and capacity constraints.
Optimize CI assurance portfolio
Choose one baseline, cache, shard, test-selection, flaky-repair, mutation, integration-suite or runner-scale option per assurance unit using only prospective randomized/known-propensity fault-detection and feedback evidence, common random scenarios, controls, relations, budget, implementation and runner capacity, undetected-fault, latency and CVaR gates.
Optimize engineering observability portfolio
Exactly select the budget-feasible metric and integration subset maximizing multivariate Gaussian information, then require held-out information retention with bootstrap uncertainty.
Optimize error budget portfolio
Choose dependency-safe reliability interventions under money and capacity constraints using posterior SLO-breach economics.
Optimize incident learning portfolio
Choose immediate remediation or a predeclared experiment-contingent action for each failure mode using Bayesian value of information, prospective test accuracy and causal remediation effects, common scenarios, shared-loss accounting, Pareto search and hard cost, capacity and tail-risk gates.
Optimize preventive maintenance policy
Optimize preventive replacement or refactoring intervals with Bayesian-scenario Weibull renewal-reward economics and a worst-case cost penalty.