When evaluating observability platforms, engineering organizations rarely start from scratch. Teams have established tooling and workflows, whether in SaaS platforms such as Datadog and Dynatrace or self-hosted, open source stacks. Historically, moving to a new platform has been a large undertaking that teams need to balance with their roadmap priorities.
To make adopting Cortex XCOR straightforward, we have dramatically simplified the migration process from legacy SaaS vendors. In this effort, we are delivering three complementary capabilities:
- Cortex XDOT Collector: Our distribution of OpenTelemetry, designed as a drop-in replacement for proprietary SaaS agents.
- Expanded integration framework: Turnkey connections for third-party systems, accelerated by internal AI tooling.
- AI-driven migration tooling: Automated asset translation, verification, and centralized project tracking.
In this article, we’ll walk through each of these capabilities and explain how they make the transition to Cortex XCOR quick and seamless.
Cortex XDOT Collector: Replacing Proprietary Agents with Open Standards.
Proprietary SaaS agents trap organizations in vendor lock-in through custom configurations and non-standard telemetry formats. As a result, most engineering leaders prefer an observability provider that supports open standards. However, while transitioning to open standards eliminates vendor lock-in, pure open-source collection introduces its own hurdles: it typically requires full code reinstrumentation, offers only a subset of enterprise capabilities, and creates immense operational complexity to set up and maintain at scale. Engineering teams often face months of tedious rewrites and fragile setups that delay platform modernization.
Cortex XCOR Distribution of OpenTelemetry (XDOT) Collector resolves this trade-off. Designed as a simple-to-install drop-in replacement for proprietary SaaS agents, Cortex XDOT Collector provides an easier path to OpenTelemetry without forcing teams through complex re-instrumentation. Under the hood, it relies entirely on standard OpenTelemetry YAML configurations and fully leverages OpenTelemetry semantics. By swapping agents directly without requiring application code changes, teams eliminate the months-long re-instrumentation cycle that typically stalls platform cutovers.
This architecture provides the operational simplicity and functionality expected of a vendor-managed agent while preserving long-term flexibility. Standardizing telemetry around OpenTelemetry semantics within Cortex XCOR also enables engineering teams to correlate insights across logs, events, metrics, and traces. By maintaining consistent data models across all telemetry types, teams eliminate the friction of manually mapping disparate data signals during active investigations.
At launch, Cortex XDOT Collector supports Windows, Linux, and Container environments, and the OSS repository is available here.
Integrations: Accelerating Data Ingestion From Third-Party Systems.
Engineering teams need immediate visibility into infrastructure and application components. To accelerate data collection and visualization, Cortex XCOR is introducing new integration capabilities.
The Integrations Hub is a centralized interface within Cortex XCOR designed to streamline data collection. It provides a single screen where engineers can discover, configure, and deploy out-of-the-box integrations and pre-configured operational dashboards with one-click installation.
From this screen, teams can adopt both SaaS and Collector Integrations:
- SaaS integrations: Server-side integrations that pull telemetry directly from external SaaS platforms, such as Salesforce and MongoDB Atlas, into Cortex XCOR over API connections.
- Collector integrations: Client-side integrations that operate directly within Cortex XDOT Collector to gather telemetry from local infrastructure and services, such as Kubernetes, Envoy, and Istio.
Cortex XCOR collector integrations are based on the OSS OTel Collector receivers. When necessary, Cortex XDOT Collector extends the receivers to provide the full telemetry that legacy integrations provide. Doing so ensures all metrics are present in Cortex XCOR post migration. To support the broader ecosystem, Cortex XCOR feeds developments created for collector integrations back into the OpenTelemetry open-source community, helping drive continuous industry innovation.
While Cortex XCOR launches with an extensive suite of out-of-the-box integrations, we are also introducing the Integrations Factory—an internal delivery model powered by AI tooling. The Integrations Factory enables our internal teams to build, test, and release new technology integrations in days rather than months. As a result, we can help our customers onboard new data sources whenever their tech stacks evolve. This rapid delivery model ensures data ingestion never blocks cutover timelines, letting teams mirror their legacy telemetry coverage in Cortex XCOR on day one.
Migration Tooling: Automating Asset Translation, Validation, and Project Management.
Transitioning off an existing SaaS vendor involves converting extensive operational logic, including queries, monitoring dashboards, alert configurations, and service level objectives (SLOs). Rebuilding these assets manually consumes valuable engineering capacity and introduces human error.
Historically, we’ve had success moving some of the largest, most complex observability workloads onto Cortex XCOR without engineering disruption. We’ve invested further in this area to provide deeper automation. By replacing manual syntax rewrites and visual checks with programmatic execution, these capabilities collapse the overall migration timeline.
Automated asset conversion programmatically migrates existing queries, dashboards, monitors, and SLOs from legacy vendor formats into Cortex XCOR-compatible structures. This programmatic approach removes the need for engineers to rewrite queries or rebuild dashboard layouts line by line. Converting assets is only useful if the translated results are accurate. Our validation engine executes automated checks across translated configurations to ensure everything works as expected.
The engine applies AI-assisted analysis to detect conversion gaps and highlight potentially risky visualization panels. It generates side-by-side visual comparisons between the source asset and the converted Cortex XCOR asset, establishing visual trust and verifying data parity. During Palo Alto Networks' internal migration onto Cortex XCOR, this automated validation tooling accelerated transition off legacy platforms by 66% while requiring little-to-no manual effort from engineering teams.
Managing a multi-team platform transition requires clear project governance. The centralized Migration Hub serves as a single source of truth for all stakeholders, displaying a real-time status table that tracks migration velocity and asset state across the organization.
Through the hub, platform leads can assign specific engineers to validate assets, use in-app commenting to resolve data discrepancies, and lock verified configurations. Locking verified assets prevents subsequent conversion scripts from overwriting manual adjustments, removing redundant project management overhead.
Streamlining Platform Migration for the AI Era.
Transitioning to a modern observability platform does not require months of manual configuration or vendor lock-in. By combining an OpenTelemetry-native collector, rapid AI-driven integration generation, and automated asset translation and validation, Cortex XCOR delivers an efficient path off legacy SaaS tools while giving engineering teams full control over their telemetry infrastructure.