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Data Science AnalyticsTop 10 Best Application Performance Monitoring Services of 2026
Ranked picks for application performance monitoring services, comparing top vendors like New Relic and Smartronix by visibility, alerts, and coverage.
How we ranked these tools
Core product claims cross-referenced against official documentation, changelogs, and independent technical reviews.
Analyzed video reviews and hundreds of written evaluations to capture real-world user experiences with each tool.
AI persona simulations modeled how different user types would experience each tool across common use cases and workflows.
Final rankings reviewed and approved by our editorial team with authority to override AI-generated scores based on domain expertise.
Score: Features 40% · Ease 30% · Value 30%
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Accenture is the best bet when large enterprises need managed APM delivery across many services, whereas Deloitte fits if you want trace-driven performance ops with governance and consistent cross-team instrumentation.
Editor’s top 3 picks
Three quick recommendations before you dive into the full comparison below — each one leads on a different dimension.
Accenture
Operationalizing topology and dependency views into incident workflows with governed rollouts and validation.
Built for fits when large enterprises need managed observability delivery across many services..
Deloitte
Editor pickTrace-to-operations engagements that convert telemetry into agreed runbooks and change standards.
Built for fits when enterprises need trace-driven performance ops with governance and cross-team instrumentation consistency..
Slalom
Editor pickConsulting-led APM instrumentation and rollout planning that treats governance and operational handoff as deliverables.
Built for fits when teams need managed APM rollout across multiple services and ownership groups..
Comparison Table
Accenture
enterprise_vendorGlobal professional services firm offering APM implementation, optimization, and managed monitoring services.
Operationalizing topology and dependency views into incident workflows with governed rollouts and validation.
Accenture applies performance monitoring as an engineering service, so program delivery typically includes instrumentation planning, telemetry wiring, and operational runbooks aligned to business services. The work often emphasizes topology and dependency mapping to explain latency drivers across interacting components. Operational reporting is then anchored to service indicators and error rate patterns used by on-call teams.
A tradeoff is that monitoring outcomes depend on Accenture-led delivery and change management rather than fast self-serve setup. The best fit is an environment with multiple teams and heterogeneous stacks that needs consistent instrumentation, controlled rollout, and automated checks for regressions.
- +Service dependency mapping paired with performance engineering runbooks
- +Automation around monitoring rollout, validation, and operational handoffs
- +Enterprise-grade governance practices for multi-team observability programs
- +Cross-stack instrumentation guidance for consistent telemetry standards
- –Faster implementation depends on Accenture delivery cycles and coordination
- –Less suitable for teams wanting self-serve monitoring only
- –Tail latency insights may require more instrumentation work upfront
- –Governance and change controls can add process overhead
Platform engineering teams
Trace to dependency mapping for latency
Shorter root cause cycles
Site reliability teams
SLO monitoring tied to runbooks
More consistent error budgets
Show 2 more scenarios
Enterprise IT governance
Controlled instrumentation standards rollout
Lower telemetry drift
Governance-focused delivery helps keep instrumentation configuration consistent across teams and apps.
Application modernization teams
Performance baselining during migrations
Fewer migration surprises
Managed monitoring setup supports before and after comparisons to detect regressions during changes.
Best for: Fits when large enterprises need managed observability delivery across many services.
Deloitte
enterprise_vendorBig Four consultancy providing APM assessment, tool selection, and managed monitoring services.
Trace-to-operations engagements that convert telemetry into agreed runbooks and change standards.
Deloitte fits organizations that treat performance monitoring as an operating system rather than a dashboard set. Engagements typically combine instrumentation planning, telemetry correlation, and topology-oriented analysis to connect user impact with service behavior. The service delivery approach is most visible when teams need consistent standards across many services, teams, and deployment pipelines.
A tradeoff appears when monitoring needs are narrow and time-to-value must be immediate without assessment work. The fit improves when multiple teams own different parts of the stack and root cause analysis depends on shared trace context and agreed operational runbooks. Deloitte also works well when stakeholders require auditability and controlled changes to monitoring behavior.
- +Consultancy delivery adds standards for instrumentation and operational runbooks
- +Cross-telemetry correlation supports trace-led root cause workflows
- +Dependency and topology analysis helps target performance bottlenecks across services
- +Governance-focused administration fits multi-team monitoring change control
- –Faster self-serve monitoring teams may find onboarding slower than product-only options
- –Trace coverage depends on instrumentation quality across owned services
- –Advanced workflows can require ongoing analyst involvement to interpret findings
Site reliability engineering teams
Trace-led root cause for incidents
Faster, repeatable diagnosis
Platform engineering organizations
Topology and dependency visibility
Targeted bottleneck remediation
Show 2 more scenarios
Enterprise operations and compliance
Controlled monitoring change management
Reduced operational risk
Governance-led administration supports auditable configuration patterns across teams.
Cloud migration teams
Post-migration performance validation
Confidence in release readiness
Operational correlation and trace context checks help verify throughput and latency behavior changes.
Best for: Fits when enterprises need trace-driven performance ops with governance and cross-team instrumentation consistency.
Slalom
enterprise_vendorGlobal consulting firm providing APM strategy, tool selection, and implementation services.
Consulting-led APM instrumentation and rollout planning that treats governance and operational handoff as deliverables.
Slalom’s value shows up in integration depth across monitoring data sources, where instrumentation choices and deployment constraints drive the plan. Operational reporting and alerting workflows are treated as governance outputs, not just UI screens. The approach fits organizations that need consistent request and dependency views across services while managing change risk.
A tradeoff is that the consulting involvement can slow early experimentation compared with self-serve monitoring setups. Slalom fits best when new instrumentation or multi-team rollout is already on the critical path, such as after an architecture change or a service dependency refactor.
- +Implementation planning reduces instrumentation drift across services
- +Alerting workflows align with operational ownership and handoff
- +Integration work supports consistent visibility across environments
- +Engagement model fits teams needing rollout and change control
- –Self-serve speed is weaker for quick proof-of-concept work
- –Great outcomes depend on active collaboration during rollout
- –Advanced configuration may take longer than UI-only monitoring
- –Visibility outcomes vary with chosen instrumentation scope
Platform engineering teams
Standardize monitoring across services
Fewer blind spots during changes
SRE teams
Tune alerting for reliability work
Less noisy paging
Show 2 more scenarios
Enterprise IT governance
Coordinate monitoring across environments
Consistent audit-ready operations
Slalom structures environment onboarding so teams get comparable reporting and escalation paths.
Software delivery leaders
Instrumentation after architecture refactors
Faster root cause during regressions
Slalom supports instrumentation scope decisions tied to service dependency mapping and rollout sequencing.
Best for: Fits when teams need managed APM rollout across multiple services and ownership groups.
Capgemini
enterprise_vendorGlobal IT services firm delivering APM implementation and performance engineering services.
Enterprise rollout governance that coordinates topology mapping, instrumentation consistency, and operations handoffs across environments.
Capgemini delivers application performance monitoring through a services-led approach that combines monitoring deployment with enterprise operations integration.
Core work typically includes dependency discovery across application tiers and instrumentation guidance to keep signals consistent across services.
Governance and automation emphasis favors organizations that need controlled rollouts, standard dashboards, and runbook-aligned incident workflows.
- +Delivery model includes monitoring rollout governance and environment alignment
- +Integration work focuses on multi-tier dependencies across application services
- +Automation support fits change-managed operations workflows and runbooks
- +Tailored instrumentation guidance for consistent coverage across teams
- –Managed delivery model can add lead time versus self-serve setup
- –Deep configuration requires governance discipline across owners and environments
- –Out-of-the-box experience depends on what monitoring stack gets deployed
- –Advanced debugging workflows may require coordinated trace and log collection
Best for: Fits when enterprises need governed monitoring rollouts and integration with existing operations processes.
Cognizant
enterprise_vendorIT services provider offering APM consulting, implementation, and managed monitoring.
Cognizant-managed alert and incident workflow tuning that maps monitoring outputs to operational runbooks.
Cognizant delivers application performance monitoring through its managed observability services, with emphasis on end-to-end service health and operational workflows. Monitoring coverage typically spans server-side application metrics, distributed request analysis, and correlated operational context for troubleshooting.
Strong integration depth appears in how Cognizant connects monitoring telemetry to enterprise operating processes and governance expectations. Teams evaluate Cognizant when they want ongoing enablement plus tuning help rather than self-serve setup alone.
- +Managed onboarding and ongoing tuning reduce instrumentation churn
- +Operational correlation supports faster trace to incident workflow handoffs
- +Enterprise change management fits regulated release governance
- +Automation for alert lifecycle aligns with SRE runbooks
- –Deep configuration work can be required before high-fidelity visibility
- –Agent and integration options may increase deployment coordination overhead
- –UI-first analysis workflows can lag behind tool-led troubleshooting styles
- –Extensibility depends on agreed integration scope and telemetry contracts
Best for: Fits when enterprises need managed APM operations with governance-aligned incident workflows.
HCLTech
enterprise_vendorGlobal technology company offering APM implementation and managed monitoring services.
Topology oriented dependency mapping built to connect traces to application service relationships for faster root-cause workflows.
HCLTech brings managed application performance monitoring tied to enterprise delivery programs, combining monitoring with operational governance. Its monitoring coverage focuses on server and application signals, with distributed tracing and topology oriented views designed to support root-cause analysis.
Automation and integration are emphasized through agent and telemetry workflows, plus API-driven interactions that fit existing platform operating models. Reporting and alerting are structured around service health metrics like latency percentiles, error rate, and saturation-style indicators for ongoing performance visibility.
- +Operational governance aligned monitoring reports for enterprise delivery teams
- +Distributed tracing and dependency mapping support faster incident scoping
- +Automation and integration workflows fit existing CI and telemetry pipelines
- +Latency and error monitoring metrics map cleanly to service health dashboards
- –More implementation planning needed for consistent instrumentation coverage
- –Topology and trace views can require tuning to stay readable at scale
Best for: Fits when large enterprises need managed APM operations with controlled rollout and integration into existing platform workflows.
Atos
enterprise_vendorIT services company offering APM implementation and managed monitoring services.
Dependency-focused investigation that links cross-component performance signals within operational troubleshooting workflows.
Atos brings application performance monitoring to enterprise environments with an emphasis on managed operations and integration into larger IT service management workflows. Its monitoring capabilities cover server-side performance signals such as request throughput, response time, and error rate, with analysis geared toward production troubleshooting.
Atos also supports trace-driven investigations in distributed systems when instrumentation and correlation are set up across services. The result is clearer dependency-focused debugging, when the deployment has consistent tagging and retention aligned to incident workflows.
- +Managed operations support for production monitoring workflows
- +Correlation across services helps diagnose cross-component performance issues
- +Enterprise-grade governance for access control and auditability
- +Monitoring coverage spans throughput, latency, and error rate signals
- –Distributed tracing depth depends on instrumentation standards across teams
- –Automation and API surface for high-volume customization is limited
Best for: Fits when enterprises need managed monitoring operations and strong governance across shared production services.
DXC Technology
enterprise_vendorIT services provider delivering APM implementation and managed monitoring operations.
Managed orchestration of monitoring configuration and rollout across multi-team production environments.
DXC Technology delivers application performance monitoring as part of an enterprise services and managed observability approach rather than a single self-serve monitoring UI. Core capabilities center on instrumenting distributed applications, tracking runtime health, and correlating performance symptoms across services and infrastructure.
Administration and governance are typically delivered through DXC implementation work, including configuration guidance for retention, alerting rules, and environment rollouts. Integration depth tends to be strongest when DXC can align monitoring with existing DXC-managed operations workflows.
- +Enterprise implementation support for monitoring rollout across complex app estates
- +Cross-environment performance correlation for faster impact scoping during incidents
- +Customizable alerting and thresholds aligned to operational runbooks
- +Instrumentation guidance for distributed workloads spanning multiple platforms
- –Less effective for teams that expect fully self-serve setup and tuning
- –Operational governance depends on DXC-led configuration for consistent standards
- –Advanced topology and dependency views require disciplined service mapping
- –Agent and integration choices can raise engineering overhead in heterogeneous estates
Best for: Fits when enterprises need managed monitoring integration and runbook-aligned governance.
EPAM Systems
enterprise_vendorDigital platform engineering firm offering APM implementation and observability consulting.
Consulting-led observability delivery that bundles instrumentation, dependency mapping, and remediation playbooks into one operational workflow.
EPAM Systems delivers application performance monitoring through consulting-led observability delivery that pairs instrumentation work with operational ownership. Core capabilities include end-to-end performance visibility across services, with tracing and topology-style dependency views used to connect latency, errors, and request patterns to the components producing them.
EPAM also supports operational integration needs such as instrumenting codebases, wiring telemetry pipelines, and producing runbooks that link alerts to remediation steps. Governance and control depth come from enterprise rollout practices that align monitoring coverage with app and infrastructure change management.
- +Strong integration delivery for multi-service telemetry rollouts
- +Clear focus on operational runbooks tied to performance alerting
- +Topology and dependency mapping help speed root cause workflows
- +Enterprise governance practices for instrumentation coverage and change control
- –Requires implementation effort for instrumentation and pipeline wiring
- –Out-of-the-box UI depth can lag specialized monitoring vendors
- –Tail latency investigations depend on consistent tagging discipline
- –Automation coverage varies by engagement scope and delivery model
Best for: Fits when large enterprises need managed instrumentation plus performance triage runbooks across complex services.
NTT Data
enterprise_vendorGlobal IT services firm offering APM consulting, implementation, and managed services.
Service dependency mapping driven by distributed telemetry to visualize request paths across connected services.
NTT Data is an application performance monitoring choice for enterprises that need managed observability work alongside monitoring operations. Core capabilities center on distributed tracing and service dependency mapping to show where latency and errors originate across connected services.
Instrumentation and telemetry workflows are designed for integration into existing estates that include multiple cloud and on-prem domains. Governance controls for teams, change workflows, and operational reporting are aimed at reducing time-to-diagnose for production incidents.
- +Managed implementation support for tracing, topology views, and operational runbooks
- +Service dependency mapping helps pinpoint cross-service latency and error origins
- +Integration-focused telemetry onboarding for hybrid environments
- +Operational reporting supports incident follow-up across teams
- –Greater effort than pure self-serve tooling for instrumentation rollout
- –Trace context propagation depth depends on how applications are instrumented
- –Customization of dashboards and alert logic can require vendor-guided tuning
- –Advanced workflows may lag teams expecting highly productized automation
Best for: Fits when enterprises want managed APM operations with distributed tracing, topology mapping, and governance for production troubleshooting.
Conclusion
After evaluating 10 data science analytics, Accenture stands out as our overall top pick — it scored highest across our combined criteria of features, ease of use, and value, which is why it sits at #1 in the rankings above.
Use the comparison table and detailed reviews above to validate the fit against your own requirements before committing to a tool.
How to Choose the Right application performance monitoring
Application performance monitoring is where teams turn production telemetry into actionable visibility for request throughput, response time, error rate, and incident scoping. This buyer’s guide covers Accenture, Deloitte, Slalom, Capgemini, Cognizant, HCLTech, Atos, DXC Technology, EPAM Systems, and NTT Data.
The provider cards emphasize governance-driven rollout and operational handoff as differentiators, especially for enterprise delivery models. Each review frames how monitoring outputs connect to incident workflows, dependency views, and runbook standards across multi-service estates.
Application performance monitoring that connects telemetry to dependency-aware troubleshooting
Application performance monitoring measures application performance signals and correlates them across services so issues can be diagnosed by request flow, component impact, and failure patterns. The category focus is production-facing visibility that supports performance engineering work and incident operations.
Accenture centers on operationalizing topology and dependency views into incident workflows with governed rollouts and validation, which shifts APM from dashboards to controlled operational processes. Deloitte emphasizes trace-driven performance ops that converts telemetry into agreed runbooks and change standards so cross-team instrumentation stays consistent.
APM capabilities that change incident outcomes
Application performance monitoring becomes operational when topology and dependency views connect directly to incident workflows. Accenture translates dependency views into incident processes with governed rollouts and validation, which reduces the gap between telemetry and action.
In enterprise rollouts, trace-led runbooks and standards matter as much as visibility. Deloitte emphasizes trace-to-operations engagements that convert telemetry into agreed runbooks and change standards so teams share consistent instrumentation and operational expectations.
Governed rollouts tied to operational validation
Accenture focuses on operationalizing topology and dependency views into incident workflows using governed rollouts and validation. Capgemini adds enterprise rollout governance that coordinates topology mapping, instrumentation consistency, and operations handoffs across environments.
Trace-to-runbook operational standardization
Deloitte converts trace telemetry into agreed runbooks and change standards to keep instrumentation and operations consistent across teams. Cognizant maps monitoring outputs to operational runbooks through managed alert and incident workflow tuning.
Managed instrumentation planning to prevent cross-service drift
Slalom treats governance and operational handoff as deliverables during APM instrumentation and rollout planning across multiple services. EPAM Systems bundles instrumentation, dependency mapping, and remediation playbooks into a single operational workflow.
Dependency-aware troubleshooting across multi-service production
HCLTech uses topology-oriented dependency mapping to connect traces to application service relationships for faster root-cause workflows. NTT Data drives service dependency mapping from distributed telemetry to visualize request paths across connected services.
Operational orchestration when multiple teams own production
DXC Technology provides managed orchestration of monitoring configuration and rollout across multi-team production environments. Atos emphasizes dependency-focused investigation that links cross-component performance signals within operational troubleshooting workflows.
A decision framework for selecting an APM service delivery model
Choosing application performance monitoring services depends on how telemetry needs to be turned into repeatable incident actions. Providers like Accenture and Capgemini emphasize governed rollouts and environment alignment, which fits when change management and validation must be part of the monitoring program.
It also depends on how instrumentation standards get enforced across services. Deloitte and Slalom prioritize trace-led operational runbooks and rollout planning as governance deliverables, while Cognizant and HCLTech focus more on operational correlation and topology-based scoping for faster incident diagnosis.
Match the delivery model to rollout governance requirements
If monitoring must be introduced with validation and operational handoffs across environments, Accenture and Capgemini fit the governed rollout emphasis. If production ownership requires a provider to orchestrate standards and configuration across many teams, DXC Technology aligns to multi-team rollout orchestration.
Decide whether incident outcomes rely on trace-driven runbook standards
If cross-team instrumentation consistency must translate into agreed runbooks and change standards, Deloitte is built for trace-to-operations engagement. If incident workflows need managed tuning to map monitoring outputs to runbooks, Cognizant focuses on alert and incident workflow tuning tied to operational correlation.
Evaluate whether dependency views are deliverables in day-to-day troubleshooting
If topology and dependency views must stay readable and actionable at scale, HCLTech emphasizes tuning-aware topology and trace-to-service relationships for scoping. If request-path visualization across connected services must be production-ready through managed implementation, NTT Data emphasizes service dependency mapping from distributed telemetry.
Choose the provider that prevents instrumentation drift across owned services
For multi-service estates where drift breaks incident workflows, Slalom treats governance and operational handoff as deliverables during APM rollout planning. For complex service portfolios where remediation playbooks must be tied to performance alerting, EPAM Systems bundles remediation playbooks with instrumentation and dependency mapping.
Confirm the expected speed of onboarding versus self-serve experimentation
Enterprise delivery cycles can add lead time for governed rollouts like Accenture and Slalom, which can reduce self-serve speed for proof-of-concept work. Managed operations approaches like Atos and DXC Technology can also depend on multi-team configuration alignment before high-fidelity visibility is consistent.
Who benefits from managed APM that turns telemetry into operations
Large enterprises that operate many services benefit when APM is delivered as a governed program with operational handoffs and validation. Accenture is a strong match for managed observability delivery across many services where topology and dependency views must drive incident workflows.
Enterprises that require instrumentation standards across cross-team ownership benefit when trace telemetry becomes agreed runbooks and change standards. Deloitte fits when trace-led performance ops must be standardized so operational workflows stay consistent across teams and services.
Enterprises running multi-service production with shared operational ownership
Accenture and Capgemini emphasize governed rollouts and environment alignment so dependency-aware troubleshooting can carry into operational handoffs across environments.
Organizations standardizing cross-team instrumentation and change practices
Deloitte focuses on trace-to-operations engagements that convert telemetry into agreed runbooks and change standards, which reduces variation in how services get instrumented and operated.
Teams that want managed alert and incident workflows tied to monitoring outputs
Cognizant provides managed onboarding and ongoing tuning that maps monitoring outputs to operational runbooks, which helps incident actions remain consistent as signals evolve.
Enterprises prioritizing dependency mapping for faster incident scoping
HCLTech connects traces to application service relationships using topology-oriented dependency mapping, which supports faster root-cause workflows during high-impact incidents.
Enterprises needing provider-led orchestration across multi-team configuration
DXC Technology coordinates monitoring configuration and rollout across multi-team production environments, which supports governance when many owners must align instrumentation and operational standards.
Common buying mistakes in application performance monitoring services
Buying mistakes happen when APM selection targets dashboards instead of incident workflows and operational standards. Accenture and Deloitte both connect telemetry to incident actions through governed rollouts and trace-to-runbook conversions, and ignoring that focus increases the chance of telemetry that cannot be operationalized.
Another mistake is underestimating the dependence on instrumentation quality and consistent standards across services. Multiple managed providers warn that trace depth and dependency views depend on how applications get instrumented, which can limit visibility when coverage is uneven.
Treating dependency views as a UI feature instead of an incident workflow input
Accenture operationalizes topology and dependency views into incident workflows using validation and governed rollouts. If dependency mapping remains only a visualization layer, incident teams lose the operational handoff that Accenture designs for.
Expecting self-serve onboarding speed from a provider built around governed delivery
Capgemini and Slalom emphasize enterprise rollout governance and instrumentation planning as deliverables, which can add lead time for rapid proof-of-concept work. Teams that need quick experimentation should plan for onboarding coordination rather than assuming immediate operational readiness.
Assuming trace-to-operations runbooks will work without instrumentation consistency
Deloitte ties outcomes to trace coverage quality across owned services, which means uneven instrumentation will reduce trace-led workflows. Cognizant also links managed incident workflows to the quality of monitoring outputs, so inconsistent instrumentation undermines runbook reliability.
Buying managed APM without provisioning a governance process for multi-team tuning
HCLTech notes that topology and trace views can require tuning to stay readable at scale, which needs governance discipline across owners. DXC Technology likewise depends on provider-led configuration alignment to keep standards consistent across multi-team environments.
Under-scoping the work needed to wire telemetry pipelines and remediation workflows
EPAM Systems expects implementation effort for instrumentation and pipeline wiring and bundles remediation playbooks into the operational workflow. If the organization plans only partial wiring, remediation playbooks will not align to performance alerting and incident triage.
How We Selected and Ranked These Providers
We evaluated Accenture, Deloitte, Slalom, Capgemini, Cognizant, HCLTech, Atos, DXC Technology, EPAM Systems, and NTT Data on feature coverage and delivery fit for application performance monitoring outcomes. Features drove 40% of the ranking because providers must connect dependency and topology views to operational workflows rather than only report telemetry.
Ease and value each drove 30% because governed rollout delivery adds coordination work that impacts time-to-usable visibility. Accenture ranked highest because it pairs service dependency mapping with performance engineering runbooks and automation around monitoring rollout, validation, and operational handoffs.
Frequently Asked Questions About application performance monitoring
How do Accenture and New Relic differ in getting performance visibility from application telemetry into actionable incident workflows?
Which providers in the top list focus on trace-driven performance operations with strong governance across teams?
How does HCLTech handle distributed tracing and topology oriented dependency mapping to support root-cause analysis?
What breaks if trace context propagation and instrumentation consistency are not implemented across services in Atos and NTT Data deployments?
How do Slalom and Capgemini approach onboarding and implementation as part of an APM rollout program?
When should enterprises choose DXC Technology over a more direct instrumentation approach for application performance monitoring administration?
How do Cognizant and DXC Technology integrate monitoring outputs into existing runbooks and operations workflows?
Which providers offer administration controls and audit-ready governance patterns for monitoring data and changes?
What data migration or telemetry wiring effort is typically required when adopting EPAM Systems and NTT Data in mixed cloud and on-prem estates?
How do Accenture and Atos differ in the way they convert service dependency views into troubleshooting workflows?
Tools reviewed
Primary sources checked during evaluation.
Referenced in the comparison table and product reviews above.
- Data Science AnalyticsTop 10 Best App Analytics Services of 2026
- Cybersecurity Information SecurityTop 10 Best Application Performance Management Services of 2026
- Digital Transformation In IndustryTop 10 Best Application Maintenance Services of 2026
- AI In IndustryTop 10 Best Application Optimization Services of 2026
- Cybersecurity Information SecurityTop 10 Best Application Penetration Testing Services of 2026
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