Don’t Risk Your SaaS Business
with Traditional Enterprise
Monitoring Tools

Your SaaS is your business! You’ve got consumers demanding always-on/always-up performance, SLAs with businesses, and internal stakeholders who want to curb cloud infrastructure costs and tool spend. OpsCruise can help.

SaaS businesses face several operational challenges that require a

unique approach to observability

SLA Guarantees with Financial Implications
B2B SaaS companies working with large enterprises are all too familiar with the credits and penalties associated with outages and performance issues.
Rapid roll-out of
new services
SaaS businesses depend on users upgrading their subscriptions. SaaS businesses need a scalable and cost-efficient approach to ensure observability Day 1 for those new offerings, including those that call on 3rd party APIs outside of your control.
Inability to
Gross margins are closely monitored, so engineering can’t simply over-provision infrastructure resources. They must walk a fine line between demand, resource and performance.
Enterprise customers can go from 100 to 1000 users overnight. The SaaS vendor is expected to accommodate spikes without a hitch. Understanding the relationship between demand, resources and performance of the application is critical in avoiding false positives or missing false negatives.
Need to
Understand Users
SaaS leaders need to understand what features are popular, what devices/environments customers are using and where performance issues exist -- ultimately linking that intelligence to session termination or broader adoption.
Minimize Support
SaaS businesses need to get ahead of functional and performance issues before users notice and interpret them quickly; otherwise support personnel costs will escalate quickly and operating margins will suffer.


To support these operational demands, most SaaS businesses have embraced cloud native architectures consisting of microservices, 3rd party APIs, polyglot persistence, containers and serverless.


The complexity, ephemerality, dependencies and talent gap with cloud native architectures make them unwieldy to observe, diagnose and remediate. Traditional commercial monitoring tools born in a prior era are ill-suited to these demands.
Open source and IaaS monitoring tools (e.g. Prometheus, Grafana, FluentD, ELK, Jaeger, AWS Cloudwatch, Azure Monitor, etc.) and the data they collect are a necessary foundation, they aren’t sufficient to meet the demands of a dynamic SaaS business.


OpsCruise delivers a smart-layer on top of open telemetry which predicts degradations and automates causal analysis. For SaaS business, this ensures SLAs aren’t breached, optimizes cloud resource utilization and enables more services and customers without a commensurate increase in support staff. All at 1/3 of the cost of legacy proprietary monitoring tools.

Groundbreaking capabilities

Cruise Control AI/ML Engine

Open Observability Framework

Curated, embedded and supported open source & cloud monitoring stack unlike alternatives that only integrate with these tools.

Benefit: Future safe, Data ownership, Lower costs


Contextually unifies telemetry and config data into a native object model unlike alternatives that keep telemetry siloed.

Benefit: Real time full stack
understanding of App

Behavioral Profiling

Auto-learns normal behavior and predictively detects emerging problems unlike alternatives that use thresholds or simple statistical deviation.

Benefit: No more thresholds and catch degradations before impact


Trace flows between App components and cloud services unlike alternatives that require code changes.

Benefit: Real time visibility of dependencies across App services

Fishbone RCA

Uses AI reasoning encoding SME expertise into KB for auto diagnostics unlike alternatives that require engineer to explore graphs, charts and logfiles.

Benefit: Accelerates MTTR 10x Involves and fewer Dev & Ops staff


Alerts trigger remediation in Operators or external automation/ runbook unlike alternatives that don’t act on issues.

Benefit: Accelerates MTTR reducing DIY for routine problem scenarios