Enterprises typically spend 23 minutes identifying the cause of an incident. 8-10 operations' engineers representing various infrastructure stacks attempt to prove their innocence. That is a lot of wasted time and effort. With Intelligeni's Full Stack Observability and Intelligent QoS model, you can reduce the time and effort of resolving incidents by an order of magnitude. Further, the insights from Intelligeni's Knowledge Graph help your SRE teams enhance the resilience of your digital infrastructure.
Intelligent visibility and diagnostics combining everything from end-user to apps to compute to networks
Noise reduction and Intelligent RCA. Focus on signals that really impact Quality of Service.
Left shift with automated diagnostic and resolution actions. Solve incidents 10x faster.
Start with the complete topology of a service. Overlay logs, application traces, metrics, events, configuration changes across every element with how they impact the service. Intelligeni is even smart enough to identify observability gaps.
Intelligeni's Machine Learning models raise meaningful alerts based on anomalies across all telemetry, computes impact on health and fuses related alerts into consolidated scenarios for Ops engineers to work on.
Intelligeni's Augmented Diagnostics and Root Cause Identification models pull together and correlate patterns that have led up to an incident. Beyond making diagnosis easy, Intelligeni also recommends possible actions and the best resolvers.
A single collaborative interface to integrate data and actions across the full stack of managed systems. Our powerful agents model brings powerful out of the box integration and APIs allow you to build your own rapidly.
Observability helps you deal with the unknown-unknowns. Unlike monitors that are setup to watch for known failure scenarios, Observability kicks in when things go wrong. It is what enables you to diagnose a system or gauge what is happening within a system from what you are observing. Good observability is being able to identify that change in a firewall rule is causing one of your microservices to fail leading to sporadic errors. And doing so Fast.know more
Static Thresholds quite often do not work well in today's application environments. You either miss important signals or have to deal with spurious alerts. Managing such thresholds in an environment with thousands of Microservices each with their own computing stack is almost impossible. While thresholds apply to metrics and are challenging, so are filters applied to log messages. In fact they may just be a lot more tricky.know more
Modern application systems are noisy - they generate large amounts of telemetry. When a part of such a system fails, we often see numerous alerts generated by different monitors and log producers. Throwing all of these alerts at Ops Teams simply leads to Cognitive Overload and Alert Fatigue.know more
Intelligeni embeds a powerful Computational QoS Model that in many ways is the brain of Intelligeni. At the heart of this model is a Semantic Graph representation of a system's topology. This Semantic Graph is Intelligeni's understanding of an application system's Deployment Architecture.know more
Intelligeni helps you bring your best engineers together to diagnose and resolve issues and then augments their capability with complete visibility and accurate root cause analysis. The Explorer interface with its ChatOps capability is a single pane-of-glass for your resolution teams to work on. They can explore metrics, traces, logs and events across sources and monitoring tools; run diagnostic actions and trigger responses.know more
Intelligeni uses a SaaS based Core and an on-prem/hosted in your cloud Edge model. The Edge sits behind your firewalls and communicates with all your devices. It gathers data from managed devices and monitoring tools and executes diagnostic and remedial actions on them. The SaaS based core hosts data across your Edges and gives Ops engineers integrated visibility across Edges - especially useful in Hybrid and multi-cloud environments.know more