Middleware is an AI-based full stack observability platform designed to help development and operations teams monitor, troubleshoot, and optimize cloud infrastructure and applications. By consolidating metrics, logs, traces, and events into a unified timeline and leveraging AI to analyze this data, Middleware enables faster debugging and deeper insights into both infrastructure and application performance.
The platform supports a wide range of observability functions, including infrastructure monitoring, application performance monitoring (APM), Kubernetes monitoring, synthetic monitoring, real user monitoring (RUM), custom dashboards, and robust alerting. Middleware’s key differentiators include:
- Single-command installation to immediately collect and unify observability data.
- AI-powered anomaly and error detection to surface issues quickly.
- GPT-4-based error resolution, providing contextual recommendations to resolve incidents.
- Scalability for any technology stack and environment, aiming to make observability both accessible and cost-effective for teams of all sizes.
What Technology Powers Middleware’s Observability Platform?
Middleware integrates AI and large language models (such as GPT-4) into its observability stack to automate anomaly detection and error analysis. This allows the platform to not only aggregate vast amounts of telemetry data but also provide actionable insights and suggested resolutions, reducing manual investigation time for engineering teams. Its unified timeline approach gives users a complete, contextual view of system health, accelerating root cause analysis.
Who Uses Middleware?
Middleware primarily serves B2B organizations running modern cloud-native or hybrid infrastructures. Typical users include DevOps teams, site reliability engineers, and platform engineering groups tasked with maintaining uptime, performance, and reliability of distributed systems. The platform is designed to be adopted quickly by technical teams seeking to reduce operational overhead and improve incident response times.
Who Are Middleware’s Competitors?
Middleware operates in the rapidly evolving cloud observability and AIOps market. Notable competitors and alternatives include:
- Grafana Cloud – A popular open-source observability stack, with managed cloud offerings for monitoring and visualization.
- Google Cloud Observability – Google’s suite of managed observability tools for GCP-based environments.
- Datadog – A unified observability platform known for its integrations and comprehensive monitoring.
- ServiceNow (Lightstep) – Distributed tracing and performance management for large-scale cloud services.
- Dynatrace – AI-driven observability and automation across cloud and hybrid environments.
- Cisco Cloud Observability – Tailored for Kubernetes and large-scale cloud deployments.
- Chronosphere – Cloud-native observability platform for high-scale environments.
- Oracle Cloud Observability – Monitoring and optimization for Oracle and multi-cloud environments.
- SolarWinds Hybrid Cloud Observability – Multi-cloud monitoring and visibility.
- groundcover – Cloud-native observability platform with deep Kubernetes support.
- AppDynamics, New Relic, Splunk, and Sumo Logic – Well-established platforms offering full-stack observability, analytics, and monitoring.
These platforms vary in their focus, scale, and approach to AI-driven insights, but all address the need for unified observability across complex, distributed environments.
Use PromptLoop to Uncover Company Data
Looking for more company insights like this? PromptLoop helps you go deeper, providing unique data points and analysis on companies like Middleware and many others. Automate your research and find the information that matters most. Discover how PromptLoop can accelerate your market intelligence. Get A Free Demo to learn more.