Cloud-native system for updating multi-client applications without downtime.

Abstract

A computer-implemented system for performing updates to a multi-client application without downtime, wherein the system includes: a client policy store configured to manage client-specific rollout and compliance policies; an update orchestrator configured to generate a client-specific rollout plan from a versioned dependency graph of application components; a version compatibility layer configured to enforce dual-mode compatibility between simultaneously active service and data versions; a data evolution engine configured to perform database schema changes using an expand-migrate contract procedure with versioned read views and a transactional outbox for dual-write with checkpoint-based backfill; a traffic shaper configured to perform programmable L4 / L7 routing, including session pinning, shadow mirroring, stepwise canary operation, and atomic client-specific cutover; and a telemetry and health manager configured to calculate client-specific service level indicators and to control phase progress and rollback decisions; where the coordinated cooperation of the update orchestrator, the version compatibility layer, the data evolution engine, the traffic shaper, and the telemetry and health manager updates one or more clients without interrupting ongoing sessions or violating data consistency requirements.

Description

AREA OF INVENTION

[0001] The invention relates to computer-implemented systems and methods for deploying and updating applications in distributed cloud environments. In particular, it relates to a cloud-native system and framework that enables orchestrated, client-aware updates without downtime for multi-client applications, including stateless services, stateful data stores, APLs, and real-time streaming components. BACKGROUND OF THE INVENTION

[0002] Multi-client Software-as-a-Service (SaaS) platforms consolidate multiple customer accounts onto shared compute, storage, and network resources. Conventional release strategies—such as in-place updates, rolling restarts, or coarse-grained blue-green deployments—often cause user-visible downtime, transient errors, session interruptions, or data inconsistencies during schema changes. These problems are exacerbated in multi-client environments due to differing service-level agreements (SLAs), maintenance windows, data residency requirements, and functional permissions, combined with the coupling between microservices and stateful data layers.

[0003] Existing countermeasures are only partially effective. While rolling updates reduce the scope of impact, they can disrupt long-lived connections. Feature flags decouple deployment from release but do not guarantee database schema security or API interface compatibility. Canary analytics typically focus on aggregated fault budgets and overlook client-side policies or geographic routing. Therefore, there is a need for an integrated, client-aware, cloud-native framework that formalizes version compatibility, ensures transactional safety during schema evolution, controls traffic while preserving sessions and state, and automates client-wise releases to enable true updates with zero downtime from each client's perspective.

[0004] The system provides a cloud-native framework that updates multi-client applications without user-visible downtime, while maintaining API compatibility, session continuity, and data consistency.

[0005] The system provides a client-aware update orchestrator that plans and executes client-wise rollouts based on guidelines such as business hours, SLA level, compliance requirements, and geography.

[0006] The system provides a data evolution engine that ensures security through an expand-migrate contract protocol with versioned read views and transactional dual-write.

[0007] The system provides a traffic shaper that performs programmable routing with session pinning, shadow mirroring, stepwise canary, and atomic client-specific cutover.

[0008] The system provides continuous verification through real-time telemetry, client-specific health indicators, and rollback barriers linked to service-level objectives (SLOs). SUMMARY OF THE INVENTION

[0009] In one aspect, the invention comprises a cloud-native system with: a client policy store that stores client-specific restrictions and rollout preferences; an update orchestrator that synthesizes a client-aware rollout plan from a versioned dependency graph; a version compatibility layer that performs semantic version negotiation between clients, APIs, and databases; a data evolution engine that executes an expand-migrate contract protocol with versioned read views and dual-write replication via a transactional outbox; a traffic shaper that controls L4 / L7 routing between concurrently active versions with session pinning and connection draining; a telemetry and health manager that calculates client-specific service health values ​​and controls phase transitions; and an audit and attestation module for verifying the origin of changes.

[0010] In another aspect, the invention discloses an operational process for performing updates without downtime in a multi-client environment by generating a client-specific rollout plan, pre-provisioning capacity for the target version, executing additive database changes, activating dual-mode compatibility at the API edge, initiating shadow traffic, performing an atomic client-specific cutover, and validating success using client-specific SLOs; in case of threshold violations, a rollback is performed automatically. DETAILED DESCRIPTION OF THE INVENTION

[0011] A cloud-native system enables zero-downtime updates for multi-client applications by combining client-aware rollout planning, semantic versioning, secure database schema evolution, programmable traffic shaping, and continuous verification. A client policy store provides an update orchestrator with specifications from which client-specific rollout plans are generated. A data evolution engine executes an expand-migrate contract protocol with dual-write and versioned read views. A traffic shaper implements shadow mirroring, session pinning, incremental canary operation, and atomic, client-specific cutover. Telemetry calculates client-specific SLOs, which control phase progression and trigger rollbacks. The system performs upgrades without interrupting running sessions or compromising data consistency.

[0012] The system operates on a distributed computing foundation consisting of containerized microservices, data stores, message brokers, and API gateways. The components communicate via secure channels and can be deployed across multiple availability zones and regions. The system is technology-agnostic with regard to orchestration, service mesh, or database, provided these support parallel versioning, explicit connection draining, and atomic routing updates. Client policy store

[0013] The client policy store captures metadata for each client, including SLA level, maintenance windows, compliance guardrails (e.g., no cross-border data movement), functional permissions, rollout preferences (such as canary share and shadow duration), risk tolerance, and custom health indicators. Policies are versioned and cryptographically signed to ensure provenance. A rules engine determines one effective policy per client, which is then consumed by the update orchestrator. Update Orchestrator

[0014] The orchestrator creates a dependency graph that maps services, data stores, and configuration artifacts. It extends this graph to client-specific rollout subgraphs, parameterized based on the effective client policy. The orchestrator generates a phased plan with preflight checks, capacity preparations, database expansion tasks, service provisioning tasks, traffic shaping, shadow and canary phases, and contraction tasks, and monitors execution using telemetry signals. Version compatibility layer

[0015] The version compatibility layer enforces semantic and syntactic compatibility between concurrently active versions. It defines a version contract encompassing API schemas, event schemas, and database schemas. A negotiation protocol between clients and API gateways selects a compatible version pair. During transition phases, the layer supports dual-mode operation by translating messages into a canonical intermediate representation to prevent breaking changes. Data Evolution Engine

[0016] The data evolution engine implements an Expand-Migrate-Contract (EMC) protocol: Expand: additive schema changes are applied online; read access continues via versioned views to isolate clients from partially evolved states. Migrate: dual-write strategies write updates in parallel to old and new structures via a transactional outbox; background processes perform backfills in idempotent steps with progress-marked checkpoints. Contract: after verification, obsolete fields and paths are removed; safeguards prevent premature contraction as long as older clients are active; online schema modification techniques minimize lockout times. Traffic Shaper

[0017] The traffic shaper programs data layer components for session pinning and session persistence, shadow mirroring to the target version without affecting responses, incremental canary operation according to client policy, and an atomic, client-specific cutover via an intent that updates the routing table as a single transaction. Long-lived connections are terminated with time-limited grace periods and backpressure control to prevent request loss. Telemetry and Health Manager

[0018] This module captures signals such as success rate, tail latency (upper percentile), error codes, saturation / utilization, queue depth, garbage collection pauses, database replication delay, and business KPIs. It calculates client-specific and global service-level indicators (SLIs) and applies target SLOs defined in the policies. Health states control the transition between rollout phases and trigger automatic rollbacks when necessary. Audit and certification module

[0019] All change requests, approvals, policies, and implemented state transitions are recorded in immutable logs with cryptographic digest values. The module supports export for regulatory audits and post-incident analyses and provides verifiable evidence of the change origin for each client. System for updates without downtime

[0020] In operation, the system executes a controlled sequence for each client or client cohort, beginning with plan synthesis—determining the effective client policy, extending the dependency graph, and creating a phased plan with explicit safeguards and SLO thresholds—followed by pre-provisioning capacity for the target version, including stateless replicas and, where necessary, read replicas for stateful backends, with pre-warmed caches and pre-configured settings. The system then applies additive database changes online and enables versioned read views that simultaneously project legacy and new schemas; it deploys APIs and services with dual-write / dual-read capabilities and, if necessary,Compatibility translation; mirrors a limited portion of client traffic to the target version and verifies response invariants by observing telemetry and business KPIs; progressively forwards increasing portions of the client's live traffic to the target version, secured by health gates; and—after a stability period and version negotiation convergence—removes legacy structures under database safeguards and decommissions replaced service replicas. FAILURE TREATMENT AND ROLLBACK

[0021] If client-specific SLO thresholds are exceeded, the orchestrator performs a rollback for the affected client by atomically reprogramming the routes to the previously stable version; sessions are preserved, dual-write to new structures is disabled, and any partially generated migration artifacts are quarantined for later cleanup. A global rollback can be triggered if correlated client failures exceed the acceptable impact range. SECURITY AND COMPLIANCE

[0022] The system enforces client-side isolation at the data and network levels. Policy-compliant deployment prevents cross-border data movement. The audit and attestation module provides verifiable evidence of all changes. TECHNICAL EFFECTS

[0023] The invention brings about technical improvements, including the elimination of user-visible downtime through atomic routing updates and session retention, the reduction of error spikes and tail latencies through health-driven progress control, transactional data consistency during schema evolution, and better resource utilization by limiting the impact area to client cohorts. PREFERRED FORM OF EXECUTION OF THE INVENTION

[0024] A preferred implementation uses containerized microservices, a programmable L7 gateway with support for shadow mirroring, a relational database with online schema changes and versioned views, an event bus with "exactly once" semantics for migration processes, and infrastructure APLS that enable atomic updates of routing tables. Alternative implementations using other orchestration and data layer technologies are also included.

Claims

[1] A computer-implemented system for performing updates of a multi-client application without downtime, wherein the system comprises: a client policy store configured to manage client-specific rollout and compliance policies; an update orchestrator configured to generate a client-specific rollout plan from a versioned dependency graph of application components; a version compatibility layer configured to enforce dual-mode compatibility between simultaneously active service and data versions; a data evolution engine configured to perform database schema changes using an expand-migrate contract procedure with versioned read views and a transactional outbox for dual-write with checkpoint-based backfill; a traffic shaper configured to perform programmable L4 / L7 routing, including session pinning, shadow mirroring, stepwise canary operation, and atomic client-specific cutover; and a telemetry and health manager configured to calculate client-specific service level indicators and to control phase progress and rollback decisions; where the coordinated cooperation of the update orchestrator, the version compatibility layer, the data evolution engine, the traffic shaper, and the telemetry and health manager updates one or more clients without interrupting ongoing sessions or violating data consistency requirements. [2] System according to claim 1, wherein the update orchestrator extends a global dependency graph to client-specific rollout-directed acyclic graphs parameterized by maintenance windows, SLA levels, data residency requirements and blast radius budgets, and wherein the update orchestrator dynamically sizes client cohorts based on historical fault budgets and real-time saturation metrics to limit risk during the update. [3] System according to claim 1, wherein the version compatibility layer provides a negotiation protocol that publishes versioning capabilities of clients and services, and wherein the data evolution engine, in response to negotiation results, enforces interlocking safeguards that prevent contraction of legacy schema elements until a threshold proportion of active clients has negotiated to a compatible version, thereby ensuring version compatibility during migration. [4] System according to claim 1, wherein the traffic shaper defines a client-specific routing intent as a single atomic transaction across a plurality of distributed L4 / L7 proxies, wherein the atomic transaction includes connection draining with time-limited grace intervals, session stickiness maintenance, and shadow response equivalence checks within limited tolerances of deviation, which allow the transition from shadow to canary up to full cutover for the client. [5] System according to claim 1, further comprising an audit and attestation module that cryptographically links the effective client-specific policy, the plan generated by the orchestrator, telemetry thresholds and realized state transitions to tamper-proof records, wherein the records are exportable for regulatory audits and serve as evidence of the origin of changes for each client updated within the system without downtime.