Autonomous Application Performance

Dynamic, orchestrated cloud applications are creating a new set of operational & performance challenges ill-suited to legacy monitoring tools. OpsCruise imagines a world of autonomous operations and has innovated a fundamentally different approach.

current industry Challenges

Cloud applications require a new approach to observability

Layers of Abstraction and Dependencies
Cloud environments have complex and tiered layers of dependencies including application middleware,  orchestration and infrastructure. Further, many apps have dependencies on 3rd party services which they do not control.
Too Much Data
Numerous open source and commercial tools are good at aggregating metrics, logs and traces. Unfortunately, developers and admins in Ops/SRE teams are on their own to make sense across the thousands of different signals arriving every second.
Lack of Visibility
The scale, complexity and transience introduced by containers and their orchestration requires real-time visibility into the application, such as the ability to drill down from application components to the infrastructure for insights into performance and health.
Too Many Blind Spots
Cloud applications have a highly variable structure given the ephemeral nature of containers and the use of autoscaling to handle variable workloads. This dynamic nature of the application and layers of abstraction introduce many blind spots.
Existing Tools Are Incompatible
Most commercial monitoring solutions are intrusive, expensive and incompatible with today’s cloud-native applications and platforms that are built on the CNCF stack. They rely on proprietary agents on every host or necessitate changes in app code.
Growing Talent Gap
The agility needed in cloud operations has created a move to Site Reliability Engineering (SRE) which requires more software engineering talent. While top web-scale companies have such skills in their engineering ranks, most enterprises do not and are failing to keep pace with deployments.

key capabilities

OpsCruise features address real pain

Automated, real-time discovery and visibility to every service component and its dependencies

For the data to be relevant and actionable, a context must be placed around the data ingested and how it is processed. OpsCruise delivers this context through one unified full-stack topology overview. See every service component and all its dependencies, including 3rd party cloud services, and get a shared understanding across teams and tools.

Identify new connections AND INTERACTIONS
Instantaneously see unwanted or unexpected dependencies and cross-region, zone, or datacenter interactions in your environment.

Visualize the Full stack and Service Performance
Understand how your application components are related to one another and dependent upon Kubernetes and the underlying infrastructure to optimize your deployments. Also, quickly observe the overall health and performance of services.

Decentralized Team Views
OpsCruise helps you decentralize knowledge without creating another data silo. With the flexible user interface you can create specific views for any cross-section of your stack.


Predict Service Degradations
OpsCruise combines operational data and applies contextual machine learning to your historical and streaming data so that you can predict imminent outages and thereby prevent them from ever occurring.

Narrows inspection sCOPE
Identify interacting services with associated changes in error rate, latency, and traffic pattern across your entire architecture so you know where to focus when analyzing an incident. This cuts down your war room efforts in terms of time and staff involved.

Topology Time Travel
You've alway been able to see your historical metrics, but in a dynamic environment, it's equally important to be able to rewind your topology. Track all changes in your stack, no matter whether they are infrastructural, configurations or deployments. See how those changes have impacted your business metrics over time.


OpsCruise can automatically surface issues related to the cause from behavioral and dependency analysis so Ops/SRE teams aren’t deluged with a cascade of individual alerts when problems occur.

Causation over Correlation
In dynamic cloud IT environments. correlation that looks for events that occur around the same time or area is insufficient. OpsCruise leverages the knowledge of the application structure through topology walks that can pinpoint problem sources far down the dependency chain.

Continuous and Automated
OpsCruise’s automatic root cause analysis constantly looks for root causes and the impact of potential problems across the application environment. Emerging problems are reported with their impact on the dependency chain and root cause(s) in real-time.

Detects Change Impact
OpsCruise tracks all changes in demand, configuration, topology and deployments, and helps you trace the source of problems back to their temporal root cause or enable a roll-back using the Time Travel feature.

Classifying and Categorizing problems and providing prescriptive actions and recommendations for correction

reactive to proactive monitoring
Stay ahead of potential problems by creating an automation profile in advance to act on a known response triggered from your infrastructure so you can relate a business KPI problem to specific services.

say no to escalationS
Combine our infrastructure and workload monitoring capabilities with our IT Automation framework to enable your Ops team automatically handle and resolve event alerts in seconds without any manual intervention.

fail safe actions
Set up failsafe actions by mapping multiple automation profiles with different triggers and combining them with our alerting strategies. For example, you can set up a workflow to reboot your entire system when service restart fails.


Frictionless and secure experience

Deployment Ease
No agents, No Kubernetes (K8s) sidecars - traditional monitoring systems require proprietary agents to be deployed in every host or sidecars to be included in every container orchestrated by Kubernetes. OpsCruise leverages open source instrumentation/frameworks.

no app changes
No code changes or instrumentation are required in your applications. OpsCruise harnesses eBPF tracing and other networking techniques to automatically capture L4/L7 data from the network stack in the operating system and correlate it with namespaces, tags, and environment characteristics from your private/public cloud infrastructure, Kubernetes and Docker.

OpsCruise was architected from Day 1 to be native to K8s, open standards and open source monitoring tools (e.g., Prometheus, FluentD, Jaeger, Grafana, etc.). While OpsCruise can support traditional VM/physical hosts, it is K8s and container-centric in its design, visualization and workflow.

In line with open standards and best practices, OpsCruise does not need to be the long-term store for your metrics, logs and traces. Modern enterprises are centrally collecting this data once for multiple use cases beyond monitoring, including security analytics, chargeback, capacity planning and user experience management. OpsCruise selectively analyzes this data in real-time for trending, fault isolation and causal analysis.

Low overhead
OpsCruise operates with negligible resource overhead so you can safely deploy in any production environment without impacting your application. OpsCruise captures flow data statistics without being in the data path. The OpsCruise service operates an extremely efficient processing machine-learning pipeline that provides aggregate views as well as behavior profiles of every component in the application estate.

works with your existing tools
OpsCruise integrates with your existing monitoring, ticketing and incident management tools.