Splunk Observability Cloud
Splunk Observability Cloud is a comprehensive, real-time monitoring and observability platform designed to help organizations gain full visibility into their cloud-native environments, infrastructure, applications, and services. It combines metrics, logs, and traces into a unified solution, providing seamless end-to-end visibility across complex architectures. With its powerful analytics, AI-driven insights, and customizable dashboards, Splunk Observability Cloud helps teams quickly identify and resolve performance issues, reduce downtime, and improve system reliability. It supports a wide range of integrations and provides real-time, high-resolution data for proactive monitoring. This enables IT and DevOps teams to detect anomalies, optimize performance, and ensure the health and efficiency of their cloud and hybrid environments.
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Edge Delta
Edge Delta is a new way to do observability that helps developers and operations teams monitor datasets and create telemetry pipelines. We process your log data as it's created and give you the freedom to route it anywhere.
Our primary differentiator is our distributed architecture. We are the only observability provider that pushes data processing upstream to the infrastructure level, enabling users to process their logs and metrics as soon as they’re created at the source.
We combine our distributed approach with a column-oriented backend to help users store and analyze massive data volumes without impacting performance or cost.
By using Edge Delta, customers can reduce observability costs without sacrificing visibility. Additionally, they can surface insights and trigger alerts before data leaves their environment.
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Sift
Sift is a unified observability platform purpose-built for modern, mission-critical hardware systems that provides engineers with infrastructure and tooling to ingest, store, normalize, and explore high-frequency, high-cardinality telemetry and event data from design, validation, manufacturing, and operations in a single source of truth rather than fragmented dashboards and scripts; it centralizes diverse data types, aligns signals across subsystems, and structures information for fast search, visual review, and traceability so teams can detect anomalies, perform root-cause analysis, automate verification and validation, and debug hardware with real-time precision. It supports automated data review, no-code visualization and querying of massive datasets, continuous anomaly detection, and integration with engineering workflows, including CI/CD pipelines and tooling, while enabling telemetry governance, collaboration, reporting, and knowledge capture across siloed teams.
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BigPanda
Aggregate data from all observability, monitoring, change and topology tools. BigPanda’s Open Box Machine Learning will correlate the data into a small number of actionable insights so incidents are detected in real-time, as they form, before they escalate into outages. Accelerate incident and outage resolution by automatically identifying the probable root cause of problems. BigPanda identifies both root cause changes and infrastructure-related root causes. Resolve incidents and outages faster. BigPanda automates and streamlines the incident response lifecycle across incident triage, ticketing, notifications, and war room creation. Accelerate remediation by integrating BigPanda with enterprise runbook automation tools. Applications and cloud services are the lifeblood of every company. When there’s an outage, everyone is impacted. BigPanda cements AIOps market leadership with $190M in funding, $1.2B valuation.
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