Common Pain Points
Cloud Services
Cloud Managed Services & Modern Monitoring
In modern IT and multi-cloud environments, applications have become unprecedentedly complex. Operations teams (SRE & DevOps) no longer face a shortage of data. They receive too much data with no way to correlate it. Our modern monitoring solution unifies all telemetry into a single platform for actionable insights.
Something broke. Where do we even start looking?
Faced with massive log volumes, it is impossible to tell whether the issue is in the API, frontend, backend code, or database.
There are latency issues, but not reflected in the dashboard.
Traditional monitoring only checks server uptime. It cannot reflect actual end-user latency or frustration.
Fragmented tooling is driving up operations costs.
Enterprises use an average of 10–30 different open-source or standalone monitoring tools (Zabbix, Prometheus, ELK, etc.), creating scattered data views and making root cause analysis slow and difficult.
We rely on manual monitoring.
Without intelligent alerting, teams react only after customer complaints, unable to build a proactive defense for performance and security.
Full-Stack Observability on a Unified Data Model
Our modern monitoring solution consolidates all telemetry data (Metrics, Logs, Traces) into a single platform.
Infrastructure & Network Monitoring
Unified View Across Hybrid Environments
Monitor CPU, memory, disk, and network metrics in real time from a single dashboard, whether on-premises, public cloud (IaaS/PaaS), or containerized environments (Kubernetes/Serverless).
Visual Network Topology
Monitor network latency and packet loss in real time, identify performance bottlenecks, and reduce blind spots in cross-region or multi-cloud environments.
Application Performance Monitoring & Distributed Tracing (APM)
Deep Code-Level Tracing
Use Flame Graphs and Waterfall charts to precisely trace each microservice API call path and execution time, including database query latency and package execution time.
Continuous Performance Profiling
Automatically correlate frontend metrics (e.g., response time) with backend data (throughput and error rates) to significantly reduce Mean Time to Detect (MTTD) and Mean Time to Resolve (MTTR).
Real User Monitoring （RUM）
Full User Journey Recording
Record every click and page transition made by users on web or mobile apps.
User Frustration Detection
Intelligently detect dead clicks and rage clicks. Support Session Replay so development teams can see exactly what happened at the moment of failure.
Log Management & Security
Real-Time Log Search at Scale
Support collection and real-time querying of hundreds of millions of log entries per minute, with automatic anomaly log filtering.
Integrated Cloud Security Posture Management
Combine observability data with security threat detection to identify attacks like SSRF URL manipulation in real time, with specific blocking recommendations or remediation steps
AIOps & Proactive Alerts
Machine Learning Anomaly Detection
The system automatically learns normal resource baselines and proactively alerts (via Email or SNS) when sudden traffic spikes or error rate surges are detected.
Automated Root Cause Analysis
AI engine automatically correlates error events to pinpoint the exact source of latency or outages.
Data-driven Intelligent Operations
Reduce IT Operations Cost
Replace fragmented open-source tools with a single platform, reducing licensing and management overhead, hence cutting overall IT costs by up to 30%.
Accelerate Troubleshooting
Reduce the time spent correlating logs across systems from hours to minutes, saving up to 90% of troubleshooting time.
Ensure SLA & Customer Satisfaction
Proactively detect and fix issues before they impact end users, ensuring peak digital product performance and reliability.
Structured PoC & Onboarding Process
Requirements Discovery & Current State Assessment
Understand your infrastructure (e.g., EKS/EC2), frontend/backend languages, database architecture, and current monitoring pain points.
Requirements Discovery & Current State Assessment
Define PoC Success Criteria
For specific modules (APM, RUM, Log Management), define clear test scenarios and expected outcomes.Define PoC Success Criteria
Environment Deployment & Data Ingestion
Assist with monitoring agent installation, log collection setup, dashboard configuration, and automated alert rules.
Environment Deployment & Data Ingestion
Outcome Validation & Optimization Recommendations
Review monitoring outcomes against actual data; deliver architecture optimization recommendations and full knowledge transfer.
Outcome Validation & Optimization Recommendations
