{"schema_version":1,"experiment_id":"eoa_inverse_innovation_exp11_mechanism_context_external20_20260804","research_id":"eoa_inverse_innovation_exp11_external_scrutiny_20260804","cell_id":"invariant_mode_decomposition_design__computer_science","opaque_id":"invariant_mode_decomposition_design__computer_science__A","search_lanes":{"direct_problem":{"queries":["microservices retry storm cascading failures queue latency individually thresholds multivariate detection eigenvalue","microservice cascading failure spectral analysis eigenvalues dynamic mode decomposition telemetry","retry storm microservices detection graph anomaly monitoring academic paper"],"source_ids":["SRC1","SRC2","SRC3","SRC4"],"no_result_note":null},"closest_prior_art":{"queries":["\"dynamic mode decomposition\" microservices","\"Koopman\" microservice anomaly detection","eigenvalue stability \"retry storm\" distributed system","\"system identification\" \"microservices\" anomaly detection"],"source_ids":["SRC4","SRC5","SRC7"],"no_result_note":null},"historical_terminology":{"queries":["distributed systems retries positive feedback overload cascade metastable failure paper","microservice overload cascading failure retries queueing feedback loop SRE","dynamic mode decomposition computer network anomaly detection telemetry eigenvalues"],"source_ids":["SRC1","SRC3","SRC7"],"no_result_note":null},"products_practices_standards":{"queries":["official microservices retry storm detection metrics product retry budget service mesh","site:opentelemetry.io semantic conventions HTTP retry metrics queue latency","site:aws.amazon.com builders library retries overload retry storm"],"source_ids":["SRC1","SRC2","SRC6","SRC8"],"no_result_note":null},"non_english_regional":{"queries":["微服务 重试风暴 雪崩 监控 依赖图 模态 特征值","微服务 重试放大 队列 超时 级联故障 检测","Tormenta de reintentos microservicios fallo en cascada detección","Retry-Sturm Microservices kaskadierende Ausfälle Erkennung"],"source_ids":["SRC8"],"no_result_note":null},"composition_subproblems":{"queries":["queueing network spectral radius stability distributed services overload retries","microservice queueing network stability control admission concurrency model paper","service dependency graph spectral radius cascading failure computer systems","multivariate telemetry local linear model eigenvalues cloud anomaly detection"],"source_ids":["SRC3","SRC4","SRC5","SRC6","SRC7"],"no_result_note":null}},"sources":[{"source_id":"SRC1","title":"Addressing Cascading Failures","url":"https://sre.google/sre-book/addressing-cascading-failures/","publisher":"Google / O'Reilly Media","date_or_year":"2017","source_type":"OFFICIAL_GUIDANCE","language":"English","claims_supported":["Cascading failures grow through positive feedback in distributed services.","Queues, missed deadlines, retries, and overload can reinforce one another and cause global failure.","Service-wide retry budgets, backoff, load shedding, and controlled degradation are established mitigations.","Service owners and SRE teams are identifiable operational adopters."]},{"source_id":"SRC2","title":"Retry Storm antipattern","url":"https://learn.microsoft.com/en-us/azure/architecture/antipatterns/retry-storm/","publisher":"Microsoft","date_or_year":"2025-08-11","source_type":"OFFICIAL_GUIDANCE","language":"English","claims_supported":["Frequent retries can prevent a busy service from recovering and intensify the original problem.","Client and server telemetry can be used to diagnose retry storms.","Application Insights and Azure Front Door illustrate currently available threshold, chart, and query-based detection practices.","Retry limits, increasing delay, Retry-After signaling, and error classification are established mitigations."]},{"source_id":"SRC3","title":"Metastable Failures in the Wild","url":"https://www.usenix.org/system/files/osdi22-huang-lexiang.pdf","publisher":"USENIX Association","date_or_year":"2022","source_type":"PRIMARY_RESEARCH","language":"English","claims_supported":["Metastable failures are emergent work-amplification failures also described as overload, persistent congestion, cascading failures, retry storms, and death spirals.","The study identified severe real-world metastable failures across multiple organizations and reproduced amplification mechanisms experimentally.","Interacting components can sustain failure after a temporary trigger disappears.","Small timing or load changes can separate recovery from sustained failure, supporting bounded fault-injection evaluation while also showing model sensitivity."]},{"source_id":"SRC4","title":"RetryGuard: Preventing Self-Inflicted Retry Storms in Cloud Microservices Applications","url":"https://arxiv.org/abs/2511.23278","publisher":"arXiv","date_or_year":"2025-11-28","source_type":"PRIMARY_RESEARCH","language":"English","claims_supported":["Retry storms were experimentally demonstrated in AWS and a Kubernetes/Istio microservice deployment.","A distributed controller already uses retry volume, rejections, delays, and an analytic stability model to disable counterproductive retries.","The work evaluates against standard and adaptive retry policies and reports reduced retry volume, latency, resource consumption, and cost.","This is close prior art for the same problem and coordinated retry control, but it does not estimate persistent eigenmodes of a fitted graph-wide transition operator."]},{"source_id":"SRC5","title":"ServiceAnomaly: An Anomaly Detection Approach in Microservices Using Distributed Traces and Profiling Metrics","url":"https://users.encs.concordia.ca/home/a/abdelw/papers/JSS24-ServiceAnomaly_preprint.pdf","publisher":"Journal of Systems and Software / Elsevier","date_or_year":"2024","source_type":"PRIMARY_RESEARCH","language":"English","claims_supported":["Graph-aware microservice anomaly detection using distributed traces and multiple profiling metrics is existing research practice.","The method models linear and nonlinear relationships on an annotated context-propagation graph and supports anomaly explanation.","Evaluation on TeaStore and TrainTicket provides a concrete graph-aware multivariate baseline for a bounded comparison.","The method detects deviations from learned normal behavior rather than estimating growing or weakly damped dynamical modes."]},{"source_id":"SRC6","title":"Semantic conventions for HTTP spans","url":"https://opentelemetry.io/docs/specs/semconv/http/http-spans/","publisher":"OpenTelemetry","date_or_year":"Accessed 2026-08-04","source_type":"OFFICIAL_STANDARD","language":"English","claims_supported":["Stable HTTP client-span conventions support per-attempt outbound request telemetry.","Retry attempts can be represented with separate spans and resend information, supplying part of the proposed observable state without request payloads.","Standardized service, error, duration, and retry-related telemetry makes a bounded offline prototype technically plausible."]},{"source_id":"SRC7","title":"On Dynamic Mode Decomposition: Theory and Applications","url":"https://arxiv.org/abs/1312.0041","publisher":"Journal of Computational Dynamics / AIMS","date_or_year":"2014","source_type":"PRIMARY_RESEARCH","language":"English","claims_supported":["Dynamic mode decomposition is the eigendecomposition of an approximating linear operator learned from observations.","It yields modes and eigenvalues for time-indexed data and connects to system-identification methods.","The paper identifies linear-consistency, rank deficiency, sampling, and noise pitfalls, supporting the proposal's residual, uncertainty, and validity gates.","It establishes the generic causal lever but does not apply it to microservice retry propagation."]},{"source_id":"SRC8","title":"快速失败和重试 (Fast Failure and Retry), Java Chassis 3 Development Guide","url":"https://servicecomb.apache.org/references/java-chassis/zh_CN/references-handlers/fail-retry.html","publisher":"Apache ServiceComb / Apache Software Foundation","date_or_year":"Accessed 2026-08-04","source_type":"FIRST_PARTY_PRODUCT","language":"Chinese","claims_supported":["Chinese microservice product guidance recognizes timeout, burst-load, retry, and reconnection interactions that can degrade performance.","It recommends bounded retries and combines rate limiting, retry control, circuit breaking, and concurrency bulkheads.","The documented configuration demonstrates that retry, admission/rate, and concurrency controls are identifiable implementation targets.","It also shows that threshold-based local controls are established regional product practice."]}],"problem_evidence":{"status":"PARTLY_SUPPORTED","finding":"The general problem is strongly supported: public operational guidance and primary research document positive-feedback overload, retry amplification, cascading failure, and metastable states produced by interacting queues, timeouts, retries, and dependencies. RetryGuard reproduces the phenomenon in cloud and Istio microservice deployments. However, the narrower assertion that a repeatable graph-wide growing mode becomes detectable while every individual service metric remains within an acceptable threshold was not directly demonstrated by the retained sources.","source_ids":["SRC1","SRC2","SRC3","SRC4","SRC8"],"uncertainty":"Evidence establishes coupled amplification and shortcomings of purely local reasoning, but not the proposal's exact pre-threshold modal signature for a particular service graph."},"adopter_evidence":{"status":"SUPPORTED","finding":"Service owners, SRE/on-call teams, and platform or service-mesh operators are identifiable adopters; they already configure retry budgets, timeouts, rate limits, circuit breakers, and concurrency controls and investigate dependency telemetry.","source_ids":["SRC1","SRC2","SRC4","SRC8"],"uncertainty":"The accountable owner will vary across organizations, and coordinated changes spanning several services may require more than one team's approval."},"implementation_evidence":{"status":"PARTLY_SUPPORTED","finding":"The ingredients are implementable: OpenTelemetry supplies standardized per-attempt HTTP telemetry; graph-aware multimetric microservice detectors have been evaluated; DMD estimates eigenmodes of a fitted transition operator; and retry, rate, circuit-breaker, and concurrency controls exist in products. No retained source validates this exact telemetry vector, local linearization, modal-gain warning rule, and intervention map together in a microservice retry storm.","source_ids":["SRC4","SRC5","SRC6","SRC7","SRC8"],"uncertainty":"Topology changes, nonlinear policy transitions, scaling, normalization, noisy or missing observations, rank deficiency, and unstable modes may make the fitted operator nonpersistent or unactionable."},"prior_art":{"disposition":"ADJACENT_PRIOR_ART","closest_analogues":[{"name":"RetryGuard productive-retry controller","source_ids":["SRC4"],"same_problem":true,"same_causal_lever":false,"overlap":"Detects and suppresses counterproductive retries in interconnected cloud microservices using retry volume, rejections, delays, and an analytic stability model; it includes experimental multi-layer evaluation.","remaining_difference":"It makes service-level productive-retry decisions rather than fitting a graph-wide state-transition operator, estimating persistent modes and gains, checking modal reconstruction and drift, or mapping a mode to coordinated retry, admission, and concurrency proposals."},{"name":"ServiceAnomaly graph-aware multimetric detector","source_ids":["SRC5"],"same_problem":false,"same_causal_lever":false,"overlap":"Uses distributed traces, a service graph, multiple metrics, learned relationships, and explanatory anomaly localization in microservices.","remaining_difference":"It detects deviations from normal graph and metric relationships, not a retry-specific weakly damped or amplifying transition mode with an estimated gain."},{"name":"Dynamic mode decomposition","source_ids":["SRC7"],"same_problem":false,"same_causal_lever":true,"overlap":"Fits an approximate linear evolution operator and extracts modes and eigenvalues from time-indexed observations, with known noise and consistency limitations.","remaining_difference":"It supplies the generic mathematical mechanism but not the microservice state design, retry-storm hypothesis, operational thresholds, action mapping, or SRE evaluation."},{"name":"Application Insights retry-storm diagnosis","source_ids":["SRC2"],"same_problem":true,"same_causal_lever":false,"overlap":"Uses dependency and server telemetry to identify concentrated retry attempts and dependency failures.","remaining_difference":"It is retrospective or contemporaneous metric/query diagnosis and does not estimate latent propagation modes or their growth before local alarm thresholds."}],"contrastive_claim_remaining":"On a fixed, bounded microservice subgraph and matched false-alert rate, a residual-gated local transition-mode monitor will provide reproducibly earlier warning of injected and replayed coupled retry cascades than independent service alarms, ServiceAnomaly-style graph-aware multivariate detection, and a RetryGuard-style service-level controller; its leading-mode loadings will also identify a smaller coordinated set of retry, admission, or concurrency adjustments without reducing held-out transition accuracy below a preregistered budget.","contrastive_claim_falsifier":"The incremental claim is falsified if the modes are not stable across adjacent windows, held-out reconstruction exceeds the preregistered error budget, no distinct amplifying mode appears, or either ordinary alarms or a graph-aware/RetryGuard-style rival matches or beats warning time and actionable localization at the same false-alert rate.","confidence":"MODERATE","search_limitations":"The bounded search used eight retained direct sources across six lanes and included English, Chinese, Spanish, and German terminology searches. It found generic DMD, retry-storm control, metastability, graph anomaly detection, standards, and products, but no direct report of DMD/Koopman modal-gain monitoring for microservice retry storms. Search-engine coverage, inaccessible literature, patents, proprietary tools, and unpublished deployments remain limitations."},"researchability_gates":{"externally_supported_problem":{"status":"PASS","rationale":"Multiple independent official and primary sources establish retry amplification, cascading overload, and emergent metastable failure in distributed and microservice systems, although the exact below-local-threshold signature remains hypothetical.","source_ids":["SRC1","SRC2","SRC3","SRC4","SRC8"]},"identifiable_adopter_or_authorizer":{"status":"PASS","rationale":"Service owners, SRE incident authorities, and platform/service-mesh operators already own the relevant telemetry and controls and can authorize an offline or staging-only evaluation.","source_ids":["SRC1","SRC2","SRC4","SRC8"]},"distinct_testable_incremental_claim":{"status":"PASS","rationale":"Close work covers graph anomaly detection, service-level retry control, and generic DMD separately, but the retained evidence does not combine graph-wide fitted transition modes, modal gain and persistence gates, residual/drift checks, and coordinated action mapping. Earlier warning and localization can be tested against named rivals at matched false-alert rate.","source_ids":["SRC2","SRC4","SRC5","SRC7"]},"bounded_next_evidence_step":{"status":"PASS","rationale":"One fixed subgraph can be replayed offline and tested in staging with six preregistered retry/slowdown scenarios, using standardized retry telemetry and established benchmark methods, without production actuation.","source_ids":["SRC3","SRC4","SRC5","SRC6"]},"no_unresolved_safety_or_authority_stop":{"status":"PASS","rationale":"A read-only offline replay and staging shadow monitor is within ordinary service-owner/SRE authority and avoids production traffic control. Existing sources support bounded testing and human-controlled mitigations; the proposed exclusions and halt rules address telemetry, SLO, residual, and model-instability risks.","source_ids":["SRC1","SRC3","SRC6","SRC8"]},"adequate_search_evidence":{"status":"PASS","rationale":"All six required lanes were searched adversarially, including older metastability and death-spiral terminology, official standards and products, Chinese and European-language terms, and combinations of queueing, graph, retry, stability, system-identification, DMD, and telemetry concepts. Exactly eight retained sources include five primary, official-standard, or first-party sources and multiple independent publishers.","source_ids":["SRC1","SRC2","SRC3","SRC4","SRC5","SRC6","SRC7","SRC8"]}},"strict_success":true,"screen_survival":true,"remaining_research_value":"MODERATE","recommended_next_step":"Preregister and run the authorized bounded study on one fixed service subgraph: assemble incident replays plus six staging injections; fit only on training windows; freeze normalization, sampling interval, rank, spectral-gap, persistence, uncertainty, and residual thresholds; compare independent alarms, a ServiceAnomaly-style graph detector, and a RetryGuard-style controller at matched false-alert rate; score warning lead time, held-out reconstruction error, mode stability, contributing-service localization, operator usefulness, and proposed-control breadth. Keep all controls in shadow mode and reject the intervention under the stated falsifiers.","world_novelty_boundary":"This bounded public-source review supports a distinct testable increment but does not establish world novelty, patentability, freedom to operate, market size, routine production adoption, or realized impact. The absence of a direct retained match is only a search result, not proof that no such system exists."}