What is BYOC (Bring Your Own Cloud) observability?

BYOC, or Bring Your Own Cloud, is a deployment model where an observability platform runs inside the customer's own cloud account rather than in the vendor's infrastructure. Your telemetry data, the logs, metrics, and traces that describe what your production systems are doing, never leaves your environment. The vendor provides the software, the query engine, the agents, and the management layer, but the data itself lives on storage and compute resources that you own and control.

This sits between two more familiar models. On one end is pure SaaS, where you ship your data to the vendor's infrastructure and they handle everything: storage, compute, operations, and scaling. On the other end is self-hosted open source, where you run something like Grafana, Prometheus, or the ELK stack on your own infrastructure and are responsible for all operational aspects. Vendors like Chronosphere, Observe Inc, and Cribl also operate in this space, offering various approaches to data routing and customer-controlled storage. BYOC aims for a middle ground: the data stays in your account (like self-hosted), but the vendor manages the platform (like SaaS).

The distinction matters because observability data is among the most sensitive telemetry a company produces. It contains request payloads, error messages, user identifiers, query parameters, and infrastructure details. For organizations in regulated industries or those with strict data governance policies, sending this data to a third party introduces compliance complexity that BYOC can eliminate.

What are the advantages of BYOC observability?

Data sovereignty is the most straightforward advantage. When your observability data lives in your own cloud account, you maintain full control over where it is stored, who can access it, and how long it is retained. For organizations subject to regulations like FedRAMP, SOC 2, HIPAA, or GDPR, this simplifies the compliance picture considerably. Instead of auditing a vendor's data handling practices and relying on their compliance certifications, you apply your own security controls, encryption policies, and access rules to the underlying storage.

This matters particularly for organizations that have invested in hardening their cloud environments. If you have already built VPC configurations, encryption-at-rest policies, access logging, and network security controls that satisfy your compliance requirements, BYOC observability inherits all of those controls automatically. The observability data is just another dataset in your already-governed environment.

Cost alignment is the second major advantage, and for many organizations it is the deciding factor. Cloud providers offer significant discounts through committed-use agreements: AWS Enterprise Discount Programs (EDPs), Reserved Instances, and Savings Plans; GCP Committed Use Discounts; and Azure Reserved Capacity. Many organizations have already committed to substantial cloud spend and have capacity available. When your observability platform runs in your own account, its storage and compute consumption counts toward those commitments.

One engineering leader noted that their organization had significant committed cloud spend that was not fully utilized, and running observability infrastructure in their own account would effectively make the incremental cost near zero. In contrast, a SaaS observability subscription is a separate line item that does not benefit from existing cloud commitments. For organizations spending millions on cloud infrastructure, this alignment can represent substantial savings.

Eliminating data egress costs is a related but distinct benefit. Traditional SaaS observability requires you to ship your telemetry out of your cloud environment to the vendor's infrastructure. Cloud providers charge for outbound data transfer, and at observability scale, those egress costs can be meaningful. With BYOC, the data stays in your account, and the processing happens on compute resources within the same cloud environment. There is no egress charge because the data never leaves.

BYOC also enables architectural patterns that are difficult or impossible with SaaS. When your data lives in open formats on your own storage, you can access it with tools beyond the observability vendor's interface. Run ad hoc analysis with your data science tools. Feed it into machine learning pipelines for anomaly detection. Join it with business data in your data warehouse. Use multiple query engines for different use cases. The data is yours, in a format you control, accessible to any authorized tool in your environment. Firetiger supports a BYOC-style approach where telemetry data stays in the customer's own object storage (S3, GCS), with Firetiger's agents querying it in place rather than requiring data to be shipped to a vendor-managed backend.

What are the trade-offs of BYOC vs. SaaS observability?

The primary trade-off is operational responsibility. With SaaS observability, the vendor handles everything: infrastructure provisioning, scaling, upgrades, incident response for the platform itself, and capacity planning. You are a consumer of a service. With BYOC, the infrastructure runs in your account, which means your team has some degree of operational responsibility even when the vendor manages the software.

The degree of that responsibility varies significantly by vendor. Some BYOC offerings are "vendor-managed BYOC," where the vendor deploys and operates the platform in your account through a management plane, handling upgrades, scaling, and troubleshooting. You provide the cloud account and the access; they handle the day-to-day operations. Other BYOC models push more operational work to the customer, resembling self-hosted software with a support contract. The difference between these models is substantial, and understanding exactly who is responsible for what is critical when evaluating BYOC options.

The vendor-managed model is generally considered the sweet spot. One team evaluating deployment options said they would be willing to pay the equivalent of an engineer's salary for a fully managed BYOC solution rather than self-host an open-source stack. The reasoning was clear: the cost of an engineer's time to maintain an observability platform, handle upgrades, debug issues, and manage capacity far exceeds the cost of a managed service, but the data sovereignty and cost alignment benefits of BYOC were too valuable to give up for pure SaaS.

Total cost of ownership (TCO) requires careful analysis. BYOC eliminates the SaaS subscription but introduces infrastructure costs: the compute and storage in your cloud account, plus any operational overhead. For organizations with existing committed cloud spend, the infrastructure cost may be largely absorbed. For those without, the infrastructure cost needs to be compared against SaaS pricing. The calculus also depends on data volume: at low volumes, SaaS is simpler and often cheaper; at high volumes, the cost advantages of BYOC become more pronounced because object storage scales more favorably than per-gigabyte SaaS pricing.

Feature parity is another consideration. SaaS observability platforms benefit from being operated at scale across many customers, which drives rapid iteration on features, query performance, and integrations. BYOC deployments may lag behind in feature releases, depending on how the vendor manages updates across deployment models. Some vendors maintain feature parity; others prioritize their SaaS offering. Understanding the vendor's roadmap and update cadence for BYOC deployments is important.

Migration complexity should not be overlooked. Moving from a SaaS observability platform to a BYOC model involves more than a configuration change. You need to provision cloud infrastructure, configure networking and security, set up data ingestion pipelines, and often run both systems in parallel during a transition period. OpenTelemetry makes the instrumentation side of this migration easier (your collector can dual-write to both the old and new backends), but the infrastructure and operational setup still requires planning and effort.

Finally, consider the long-term trajectory. The observability industry is moving toward more open, customer-controlled architectures. Data lakes, open table formats like Apache Iceberg, and vendor-neutral instrumentation through OpenTelemetry all point in the direction of more customer control over observability data. BYOC aligns with this trajectory. Organizations that adopt BYOC today are building toward an architecture that preserves flexibility and avoids the lock-in that has historically characterized the observability market.

Where to start

• Inventory your cloud commitments: Check whether you have reserved instances, savings plans, or enterprise discount programs that could offset infrastructure costs.
• Assess your compliance requirements: Determine whether FedRAMP, SOC 2, HIPAA, or data residency requirements make BYOC necessary or merely beneficial.
• Evaluate vendor-managed BYOC options: Look for platforms that run in your account but handle all operations, upgrades, and scaling -- giving you data sovereignty without the ops burden.
• Start with a proof of concept: Deploy a BYOC solution alongside your current SaaS platform to compare cost, performance, and operational overhead.