Zero Standing Privileges at Scale

Marqeta's privileged access requirements span five distinct scenarios, each with different users, time constraints, and compliance implications. The prior model did not address any of them cleanly. Britive needed to work across all five. 

Scenario: Marqeta engineers routinely need elevated access to AWS for deployments, production debugging, configuration changes, and incident investigation across two AWS organizations. 

Before: Engineers held elevated AWS permissions tied to Okta group membership. Sessions persisted for days regardless of task completion. Standing access was the default state. 

After: Engineers check out a scoped AWS IAM role through the Britive UI, Slack, or CLI. The role is granted on AWS IAM at the moment of checkout and removed when the session ends or the 12-hour maximum window expires. 

Why It Matters: In a payments infrastructure environment, scoping the exposure window of a compromised cloud credential to the active session duration significantly reduces the potential impact of a credential compromise. 

Scenario: Engineers on call in PagerDuty need immediate elevated access when an incident fires. In a payments platform that runs 24/7, access delays during incident response affect live transaction processing and SLA performance. 

Before: On-call engineers either held standing elevated access permanently or waited for manual approval during an active incident, introducing a delay at the point when fast access matters most. 

After: When an engineer receives a PagerDuty alert, their Britive checkout is automatically approved based on active on-call status. No manual approval step. Access is available in seconds. 

Why It Matters: Britive built this integration from scratch in four weeks to meet Marqeta's go-live requirements. It is now a standard platform capability available to all Britive customers. For a payments company where infrastructure incidents affect live card processing, removing the approval queue from incident response is operationally significant. 

Scenario: Marqeta's engineering and data teams need privileged access to Snowflake environments containing payment processing data, transaction records, and customer analytics, all of which fall within PCI-DSS scope. 

Before: Snowflake had no integration with the group membership-based access model. Access to sensitive data environments was managed separately, with no shared policy engine or audit trail. 

After: Britive manages JIT access to Snowflake natively under the same policy engine governing AWS access. An engineer or analyst checks out a scoped Snowflake role, completes the task, and access is revoked. The checkout logs in the same audit trail as every other platform. 

Why It Matters: A unified access record across payment infrastructure and data platforms directly addresses PCI-DSS and SOC 2 control requirements. One audit trail across AWS and Snowflake removes the need to correlate access evidence from two separate systems during audit reviews. 

Scenario: Privileged access at Marqeta extends beyond cloud infrastructure. Okta administrators managing identity configurations and Salesforce users with access to customer records require the same JIT governance applied to AWS. 

Before: Okta admin access and Salesforce elevated access operated outside the cloud-native access model. Privileged SaaS access lacked the same governance standards applied to infrastructure, creating coverage gaps that auditors flagged. 

After: Britive applies the same checkout, session enforcement, and audit model to Okta and Salesforce as to AWS. Privileged actions in identity management and CRM are time-bound, logged, and governed from a single control plane. 

Why It Matters: Consistent access governance across cloud and SaaS is a baseline expectation during compliance audits. A gap in Salesforce or Okta coverage creates audit findings even when cloud infrastructure access is well-controlled. A single policy engine covering both removes that inconsistency. 

Scenario: Marqeta has onboarded agentic AI identities, specifically Claude agents, into Britive in Phase 1 of its deployment. As AI agents take on tasks in production engineering workflows, their access requires the same governance applied to human engineers. 

Before: The common approach to AI agent access is static service accounts with persistent, broadly scoped permissions. As agents multiply across engineering workflows, that model creates the same standing access risks as human standing access, without the same oversight. 

After: Britive applies the same zero standing privilege architecture to AI agents as to human and machine identities. An agent gets a privilege created at runtime, scoped to the specific action it is executing, and removed when the action ends. One policy engine and one audit trail cover every identity type. 

Why It Matters: Marqeta is one of the first production deployments to govern agentic AI identity access under a JIT framework. The ability to apply least-privilege access enforcement to AI agents using the same policy model as human engineers is an architectural requirement as AI takes on more consequential tasks in cloud environments.