Real-Time Analytics & Data Pipeline

Built a real-time analytics system with live dashboards, business intelligence, and automated alerting for a high-traffic platform.

ClientCraftiGames (Internal)

Duration4 months

Sub-second

Dashboard Query Speed

20+

Live Dashboards

2+ Years

Data Retained

100+

Alerts Configured

What We Delivered

Streaming analytics system processing events in real time

20+ custom Grafana dashboards for live visibility

Automated alerting with 100+ configured rules

2+ years of historical data with fast query performance

Problem

With a large user base generating massive amounts of data, the team needed to understand what was happening right now, not hours ago. The old batch-processing approach meant decisions were always based on stale numbers, and the operations team couldn't spot problems until users started complaining.

Solution

We built a streaming analytics system that processes events as they happen and feeds them into live dashboards. The team can see user activity, server health, revenue, and operational metrics in real time. Automated alerts catch unusual patterns before they turn into incidents.

Technology Used

ClickHouseApache KafkaGrafanaPrometheusPythonRedisKubernetesDocker

Impact

The whole team can see what's happening on the platform in real time

Problems get flagged automatically before users notice them

Business decisions are now backed by live data instead of weekly reports

Anyone on the team can pull up a dashboard, no more waiting on someone to run a report

Replaced manual weekly reporting with real-time dashboards, saving 15+ hours per week

Mean time to detect incidents dropped from hours to minutes

Architecture Highlights

ClickHouse for fast analytics queries across large datasets

Events stream in continuously so dashboards are always up to date

Custom Grafana dashboards tailored to what the team actually needs to monitor

Automated alerts that notify the team via Slack when something looks off

Lessons Learned

Choosing the right database for analytics makes queries that used to take minutes run in seconds

Dashboards only get used if the people who need them help design them

When you're storing years of data, you need automated cleanup rules or costs spiral

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