Real-Time Telemetry and Analytics
At 10:01, everything looks fine. By 10:03, it’s not. The issue isn’t that something suddenly broke — it’s that the business realized it too late.
Real-time telemetry and analytics are not about reports. They are about seeing what is happening now, not yesterday. This is where businesses either lose money — or prevent losses.
Without real-time analytics:
- incidents are detected too late;
- losses grow unnoticed;
- decisions rely on outdated data;
- there is no operational control.
What the System Looks Like Inside
Telemetry is not a single service. It is a continuous data pipeline flowing through multiple layers:
- data sources (devices, services, applications);
- transport layer (streaming, message queues);
- processing layer (real-time analytics);
- storage;
- visualization.
A weakness in any layer breaks the entire chain.
Where Data Gets Lost
The most common issue is not analytics — it’s delivery.
- missing events;
- duplicates;
- delays;
- inconsistency.
If your data is unreliable, your analytics is useless.
Why “Almost Real-Time” Is a Problem
Many systems operate with minute-level delays. That may be acceptable for reporting — but not for operations.
In high-load systems, even small delays lead to:
- loss of control;
- accumulated errors;
- slow response.
Stream Processing
The key is not just collecting data — but processing it on the fly.
- filtering;
- aggregation;
- anomaly detection;
- trigger-based actions.
This turns data into immediate action.
Fault Tolerance Is Mandatory
A telemetry system cannot afford to fail.
- redundant data streams;
- message retries;
- horizontal scaling;
- failure handling.
If you lose data, you lose visibility.
Architecture That Works
- event-driven architecture;
- message brokers (Kafka, MQTT);
- stream processing;
- layered design;
- microservices.
This approach supports millions of events per second.
Technology Stack
- Node.js (NestJS) — ingestion layer;
- Kafka — data streaming;
- Redis — fast processing;
- PostgreSQL — storage;
- ClickHouse — analytics;
- Docker / Kubernetes — scaling.
Business Impact
- instant issue detection;
- reduced financial losses;
- real-time control;
- faster decision-making.
Real-time analytics is not about data. It’s about business reaction speed.
Need a Real-Time Telemetry System?
We design systems that process events in real time and provide full operational control.