The
Overview
An IoT platform processing millions of device events daily was struggling with unpredictable slowdowns and outages. Wishtree overhauled their scalability – deploying predictive monitoring, autoscaling clusters, and real-time alerts.
Problem
Statement
The client’s infrastructure could not handle growth. They needed a scalable, cost-efficient architecture with real-time visibility.
Highlights
Real-time alerts
65%
Less downtime
45%
Lower AWS costs
Real-time SRE dashboards
Scalable IoT infrastructure
Faster, safer releases
Agentic AI refers to autonomous, goal-driven software agents that act with
limited human input to optimize specific goals like pricing, forecast demand,
and detect fraud in real time.
About Client
An IoT platform serving industrial clients with real-time device data – sensors, trackers, and controllers sending millions of events daily. As customer adoption grew, the platform struggled to keep up.
- Unexpected usage spikes regularly caused system slowdowns and partial outages.
- Each outage required hours of emergency firefighting.
- The team over-provisioned resources to handle spikes, wasting cloud spend during normal traffic.
- No visibility into infrastructure health until something broke.
- Customers lost trust with each downtime incident.
- Scaling manually could not keep up with platform growth.
- Deployed predictive monitoring using historical data to forecast usage patterns and anticipate spikes before they happened.
- Implemented autoscaling Kubernetes clusters that automatically adjust resources in real time based on actual demand.
- Built real-time alerting with intelligent thresholds.
- Created custom real-time dashboards showing infrastructure health, traffic patterns, and resource utilization at a glance.
- Right-sized all cloud resources, eliminating waste from over-provisioning.
- Established SRE best practices with error budgets, SLIs, and SLOs to drive continuous improvement.
- Designed the architecture for horizontal scaling.
- Predictive models analyze historical traffic patterns, weather data, and customer behavior to forecast demand spikes 24-48 hours in advance.
- When a spike is predicted, the system proactively scales up resources before traffic hits.
- Autoscaling algorithms continuously optimize resource allocation.
- Anomaly detection monitors real-time metrics and alerts only on meaningful deviations.
Core Features
Predictive monitoring
Autoscaling Kubernetes clusters
Custom infrastructure dashboards
Cloud cost optimization
Horizontal scaling architecture
Impact
- 65% reduction in downtime
- 42% decrease in AWS spend
- Real-time dashboards
- Predictive alerts
- Usage spikes handled seamlessly
- Cloud waste eliminated
- Reliable platform performance
- Scalable foundation ready
Why Wishtree
Wishtree builds scalable, cost-efficient infrastructure for IoT and data-intensive platforms. We combine predictive intelligence, automation, and SRE best practices to deliver reliability without waste.
For this IoT client, we:
- Cut downtime by 65% with predictive monitoring and autoscaling
- Reduced AWS spend by 42% through continuous optimization
- Gave SRE teams real-time visibility with custom dashboards
- Eliminated reactive firefighting with proactive alerts