The alert fires and the first twenty minutes go to finding the problem rather than fixing it. Your on-call engineer is paging through dashboards, cross-referencing recent deploys, and forming hypotheses while the incident keeps running. Tsuga scans hundreds of dimensions the moment a spike appears and surfaces a plain-language explanation before anyone opens the alert, so your team starts with a direction instead of a search.
Teams don't cut logs because they want to. They cut logs because their vendor made keeping them dangerous. Short retention windows, expensive fields and opaque pricing all push engineers toward the same decision, so the incentives run backwards.
Engineers spend their time staring at dashboards waiting for things to break, then taking the heat when they do. Observability bills grow three times in a year, which forces teams to shrink retention and sample logs. They miss the one event that mattered.
Here is how those compromises show up in incident response.
When something goes wrong, the first 20 minutes of every incident get swallowed by manual work. The person on call is not fixing the problem yet. They are still looking for it.
How Tsuga helps
Automated root cause analysis scans hundreds of dimensions the moment a spike is detected and surfaces a plain-language explanation before your team opens the alert. The 20-minute investigation phase becomes a 10-second read.
Tsuga deploys automated root cause analysis, anomaly detection, and deployment regression detection inside your own AWS, Azure, or Google Cloud account via infrastructure as code in under two hours. Your telemetry stays in your cloud, under your KMS keys, in your own object storage.
Because we do not resell infrastructure or profit from data bloat, the incentives line up differently.
Traditional platforms ingest your telemetry into their cloud, then charge you for accessing your own data. Storage and compute hit their bill, marked up and passed on to you. With Tsuga, the engine runs on your own instances and writes to your own object storage. Those costs hit your cloud bill directly. We charge for the software layer we manage.
Telemetry contains source code, business logic, customer PII, and now LLM prompts. Shipping that to a third-party cloud creates real data sovereignty and residency risks. Tsuga deploys entirely inside your VPC. Your KMS keys encrypt the data. Your object storage holds it. Our control plane connects via mutual TLS to manage the software layer remotely, but it never ingests data directly.
Tsuga is software and a service, not just SaaS. Every account gets a named field engineer for the lifetime of the relationship, plus direct access to the CTO. That engineer works inside your environment to optimize pipelines, retention policies, and access patterns. Because we do not profit from your infrastructure spend, their incentive is to make you run more efficiently, not to sell you more storage.
The system scans hundreds of dimensions the moment a spike appears, isolates the smallest subset of signals that explains the behavior, and surfaces a plain-language explanation with the relevant log and trace context attached.
The system learns historical patterns per service, endpoint, and environment. It alerts only when behavior genuinely deviates from the learned baseline, and flags newly appearing errors that have no prior baseline the first time they show up.
Tsuga watches every code deployment and continuously compares post-deploy telemetry against the pre-deploy baseline. It isolates regressions to the specific service version that introduced them and gives on-call engineers enough context to decide immediately whether to roll back.
The architecture handles the query volumes that autonomous agents generate when they investigate incidents, without rate limits or per-query charges. Your agents stay inside your cloud perimeter and all operational context remains under your control.
Team ownership, RBAC, audit logs, and cost attribution are native features. As application performance management usage grows across your organization, governance scales with it. No retrofitted access controls or surprise billing lines.
Your telemetry lives in your own object storage in open formats. You can read, move, or build on your own data without any vendor, and connect it to your BI tools or agent frameworks via MCPs, CLIs, and APIs.
Because storage and compute run on your own infrastructure, costs scale sublinearly as telemetry volume grows. There is no penalty for retaining data longer or querying it more frequently.
Tsuga is purpose-built for a specific set of constraints. If your situation does not match them, we will tell you upfront.
Traditional alerting tells you that a metric crossed a threshold. It does not tell you why. Tsuga's automated root cause analysis identifies the specific dimensions, services, or deployments that explain the behavior and presents that explanation alongside the relevant logs and traces.
If your observability bill is growing faster than your infrastructure, or if telemetry leaving your cloud is a risk you cannot take, Tsuga is built for your constraints.
