USD 100K Saved by Replacing Enterprise API Gateway During Prometheus Setup

Introduction

Sometimes the biggest wins in DevOps consulting come from discoveries you weren’t looking for. This case study shows how a standard Kubernetes monitoring implementation uncovered a six-figure waste that had been hiding in plain sight for years.

Client Background

A rapidly growing Saudi Arabia-based travel and hospitality company operates a modern microservices architecture running on Kubernetes. With multiple containerized applications serving their booking platform, customer portal, and internal management systems, they needed comprehensive observability to maintain service reliability during peak travel seasons.

The company engaged us to implement Prometheus monitoring across their production clusters. Their engineering team was experiencing blind spots during incidents—without proper metrics, they were troubleshooting issues reactively rather than preventing them proactively. They wanted industry-standard monitoring with real-time alerting and historical trend analysis.

The Discovery

Week one of the Prometheus implementation began with infrastructure discovery. To properly instrument monitoring, we needed to understand their complete service topology, network architecture, and traffic patterns. This is where we document every service, every endpoint, and every dependency.

While mapping their microservices communication flow, something caught our attention. An enterprise API gateway sat between their internal services—not at the edge facing customers, but internally, routing traffic between their own applications.

Initial Questions

The gateway configuration raised immediate red flags:

• Traffic volume: Fewer than 500 requests per minute across all routes
• Routing complexity: Simple path-based routing with no dynamic rules
• Advanced features: Rate limiting, OAuth integration, and API versioning—all disabled
• High availability: Configured for redundancy they never actually needed
• Vendor support: Enterprise SLA for services handling non-critical internal traffic

We asked the infrastructure team why they were using this particular solution. The answer was revealing: “It came with a consulting package three years ago. We set it up and it just… stayed.”

The Deep Dive

We pulled the license agreement and usage analytics:

What They Were Paying For

• License cost: USD 33,000 annually (USD 100,000 for 3-year renewal)
• Support tier: 24/7 enterprise support with 1-hour SLA
• Included features: 50+ advanced capabilities (authentication, transformation, caching, analytics, etc.)

What They Actually Used

• Core features: Basic HTTP routing and health checks
• Advanced features: None—most were never even configured
• Support tickets: Zero in the past 18 months
• Custom configurations: Less than 5% of available options

The Traffic Reality

We analyzed one week of gateway logs:

• Peak requests: 450 RPM during business hours
• Average latency: 12ms (well within any solution’s capability)
• Error rate: 0.02% (mostly client timeouts, not gateway issues)
• Payload size: Predominantly small JSON responses (<10KB)
• Endpoints: 8 internal services with straightforward routing

The History

The story emerged piece by piece. Three years ago, during a major infrastructure modernization, the company hired a large consulting firm. The firm recommended a suite of enterprise tools—monitoring, API management, service mesh, and more. The API gateway was part of that package.

At the time, the company was preparing for rapid growth. The consultants sold them on “enterprise-grade” infrastructure that would scale to millions of requests. They bought it all.

But the explosive growth never materialized. The company grew steadily—a good business outcome—but nowhere near the scale that justified enterprise licensing costs. Meanwhile, the gateway just kept running, the licenses kept renewing, and nobody questioned it.

It had become infrastructure wallpaper—present, functional, invisible, and expensive.

The Problem Pattern

This situation is more common than most companies realize:

Legacy Decisions That Persist

• Tools purchased for growth that never materialized
• Enterprise features paid for but never configured
• Consulting recommendations that became permanent infrastructure
• Automatic renewals that bypass technical review

The Cost of Not Asking “Why?”

• Budgets absorbed by unused capabilities
• Complexity maintained for no operational benefit
• Modern alternatives never evaluated
• Technical debt accumulating silently

Solution Implemented

The Conversation

We presented our findings to the infrastructure lead and CTO. The data was clear: they were paying USD 33,000 per year for functionality they could get for free. But changing infrastructure isn’t just about cost—it’s about risk.

Their concerns were valid:

• Will it handle our traffic? Yes—450 RPM is trivial for modern solutions
• What about when we scale? Open-source gateways handle millions of requests
• Can we migrate without downtime? We’ll run both in parallel during transition
• What if something breaks? Instant rollback capability built into the plan

We proposed a two-phase approach: complete the Prometheus implementation while simultaneously migrating the API gateway. Both projects would reinforce each other—better monitoring would give us confidence during the migration.

Infrastructure Audit Methodology

Before recommending alternatives, we conducted a comprehensive audit:

Phase 1: Usage Analysis (Week 2)

• Pulled 30 days of access logs from the enterprise gateway
• Analyzed traffic patterns, peak loads, and error rates
• Identified all routing rules and their actual usage
• Documented every configured feature and its utilization
• Interviewed developers about their actual requirements

Phase 2: Requirements Extraction (Week 3)

• Mapped 8 internal services and their interdependencies
• Identified critical vs. non-critical traffic flows
• Defined minimum acceptable latency (50ms P99)
• Established reliability requirements (99.9% uptime)
• Listed must-have features vs. nice-to-have capabilities

Phase 3: Alternative Evaluation (Week 3)

We evaluated three open-source API gateways:

1. Kong Gateway - Feature-rich but heavier than needed
2. Traefik - Kubernetes-native, good fit for their stack
3. NGINX Ingress - Lightweight, proven, widely adopted

Winner: We selected a lightweight solution optimized for Kubernetes that matched their simple routing needs without unnecessary complexity.

API Gateway Migration

Migration Architecture

The migration followed a blue-green deployment pattern with canary testing:

Week 4: Parallel Deployment
├── Enterprise Gateway (100% traffic)
├── New Gateway (0% traffic, shadow mode)
└── Monitoring both with Prometheus

Week 5: Canary Testing
├── Enterprise Gateway (95% traffic)
├── New Gateway (5% traffic - non-critical services)
└── Performance comparison & validation

Week 6: Full Migration
├── Enterprise Gateway (10% traffic - rollback ready)
├── New Gateway (90% traffic)
└── Final cutover & decommission

Technical Implementation

1. Kubernetes Deployment

   • Deployed new gateway as DaemonSet for consistent routing
   • Configured Kubernetes Service with cluster IP
   • Set up health checks and readiness probes
   • Implemented resource limits based on actual usage patterns

2. Service Discovery Integration

   • Connected to Kubernetes API for automatic service discovery
   • Configured endpoints watching for dynamic pod updates
   • Implemented DNS-based service resolution
   • Tested failover when pods were rescheduled

3. Routing Configuration

   • Migrated 8 routing rules to simple path-based routing
   • Configured health check endpoints for each backend service
   • Set up connection pooling and timeout configurations
   • Implemented retry logic for transient failures

4. Monitoring Integration

   • Exported metrics to Prometheus (request rate, latency, errors)
   • Created Grafana dashboards comparing old vs. new gateway
   • Set up alerts for latency anomalies and error spikes
   • Configured logging to centralized ELK stack

Performance Validation

Before shifting production traffic, we ran comprehensive tests:

• Load testing: Simulated 2x peak traffic (900 RPM) - passed
• Latency testing: P99 latency remained under 15ms - better than old gateway
• Failure testing: Killed pods during traffic - seamless failover
• Rollback testing: Switched back to enterprise gateway - zero downtime

Gradual Traffic Shift

Week 5 was all about confidence building:

• Day 1-2: Migrated internal dev/test service (low risk)
• Day 3: Added customer notification service (medium traffic)
• Day 4-5: Monitoring period - no anomalies detected
• Day 6-7: Migrated booking API and customer portal services

Each shift was validated with:

• Side-by-side latency comparison
• Error rate monitoring
• Customer impact assessment
• Team confidence checkpoints

Cutover and Decommission

By Week 6, the new gateway handled 90% of traffic with better performance than the enterprise solution. The engineering team had full confidence in the migration.

Final steps:

• Migrated remaining 10% traffic
• Ran both gateways in parallel for 48 hours (safety window)
• Decommissioned enterprise gateway after validation period
• Cancelled license renewal saving USD 33,000 annually

Prometheus Implementation

The original monitoring project proceeded alongside the gateway migration:

• Cluster-wide metrics collection
• Custom service metrics instrumentation
• Grafana dashboards for visualization
• AlertManager integration for notifications

Results and Business Impact

Financial Impact

USD 100,000 saved over 3 years by eliminating unnecessary enterprise licensing while maintaining identical functionality.

Detailed Cost Breakdown:

Cost Category	Before	After	Annual Savings
Gateway License	USD 33,000	USD 0	USD 33,000
Enterprise Support	Included	Community	USD 0
Infrastructure	3 VMs (dedicated)	Kubernetes pods (shared)	~USD 2,400
Total Annual	USD 35,400	USD 2,400	USD 33,000
3-Year Total	USD 106,200	USD 7,200	USD 99,000

The savings went directly to the company’s infrastructure optimization budget, funding other improvements.

Performance Improvements

Contrary to the common assumption that enterprise = better performance, the new gateway actually performed better:

Latency Comparison (30-day average after migration)

• P50 latency: 8ms (previously 12ms) - 33% improvement
• P95 latency: 14ms (previously 18ms) - 22% improvement
• P99 latency: 23ms (previously 45ms) - 49% improvement

Why the improvement?

The enterprise gateway was overengineered with features they didn’t use. Each request passed through:

• Authentication middleware (disabled but still in the chain)
• Rate limiting checks (configured but not enforced)
• Analytics processing (data collected but never reviewed)
• Request transformation (no transformations configured)

The new gateway had a simpler request path with only the features they actually used.

Reliability Metrics

• Uptime: 99.98% (no change from enterprise solution)
• Failed requests: 0.01% error rate (previously 0.02%)
• Incident count: Zero gateway-related incidents in 6 months post-migration

Operational Improvements

Configuration Simplicity

Before and after configuration complexity:

• Enterprise gateway: 2,847 lines of YAML configuration
• New gateway: 243 lines of YAML configuration
• Reduction: 91% fewer lines to maintain

This dramatically reduced:

• Onboarding time for new engineers
• Risk of configuration drift
• Time to understand and modify routing rules
• Troubleshooting complexity during incidents

Team Productivity

Post-migration survey of the 5-person infrastructure team:

• Time spent on gateway maintenance: Reduced from 4 hours/week to 30 minutes/week
• Confidence in making changes: Increased from 3/5 to 4.5/5
• Documentation burden: Reduced from “extensive” to “minimal”
• Troubleshooting speed: 2x faster with simpler config and better logs

Skills Development

An unexpected benefit: the team gained expertise in Kubernetes-native tooling rather than vendor-specific platforms. This knowledge transferred to other infrastructure components and made the team more versatile.

Cultural Shift

The biggest impact was psychological. The engineering team started questioning other legacy decisions:

Within 3 months of the gateway migration:

• Identified 3 other underutilized enterprise tools
• Initiated review of USD 45,000 in annual SaaS subscriptions
• Established quarterly “infrastructure audit” practice
• Created internal documentation for cost-benefit analysis

New Decision-Making Framework

The CTO implemented a simple rule for all future tool selections:

1. What problem are we solving? (Document actual requirements)
2. What’s the simplest solution? (Start with open source)
3. How will we measure success? (Define metrics before purchase)
4. What’s the exit cost? (Ensure we can change our minds)

This framework prevented future “infrastructure wallpaper” accumulation.

Prometheus Monitoring Success

The original project also delivered significant value:

Visibility Improvements

• Mean time to detect (MTTD): Reduced from 15 minutes to 2 minutes
• Mean time to resolve (MTTR): Reduced from 45 minutes to 20 minutes
• Proactive alerts: 23 alerts configured catching issues before user impact
• Dashboard usage: Engineering team checks dashboards 40+ times daily

Incident Prevention

In the first 3 months after Prometheus deployment:

• Prevented 7 potential outages through proactive alerts
• Identified 3 resource leaks before they caused problems
• Caught 2 configuration errors during deployment
• Detected anomalous traffic patterns indicating API misuse

ROI Analysis

Investment vs. Return

Item	Cost
Consulting engagement (6 weeks)	USD 24,000
Migration effort (internal team time)	USD 8,000
Total Investment	USD 32,000
First-year savings	USD 33,000
Three-year savings	USD 99,000
ROI (1 year)	103%
ROI (3 years)	309%
Payback period	11 months

Beyond the direct cost savings, the improved monitoring prevented estimated USD 50,000 in potential downtime costs during the peak travel season.

The Broader Lesson

This engagement changed how we approach every project. What started as a Prometheus deployment became a model for value-driven consulting:

New Standard Practice

Every DevOps transformation or monitoring engagement now includes:

1. Complete infrastructure audit
2. License and subscription review
3. Alternative evaluation
4. Cost optimization recommendations

Why It Matters

Often the infrastructure audit saves more money than the original project costs. Teams are too busy keeping things running to step back and ask “Is this still necessary?”

Technical Details

API Gateway Comparison

Requirement	Enterprise Gateway	Open Source Solution
Basic routing	✅ Overconfigured	✅ Purpose-built
Load balancing	✅ Complex setup	✅ Simple config
Service discovery	✅ Vendor-specific	✅ Kubernetes-native
Cost (3 years)	USD 100,000	USD 0
Configuration	2000+ lines	200 lines

Prometheus Metrics

The monitoring implementation now tracks:

• API gateway request rates and latencies
• Service mesh communication patterns
• Resource utilization across clusters
• Cost attribution by namespace

Conclusion

The best consulting isn’t just delivering what was asked for—it’s finding what wasn’t.

A straightforward Prometheus implementation uncovered USD 100,000 in unnecessary spending. The enterprise API gateway had been renewed for years without anyone questioning whether it still made sense.

The lesson: infrastructure should justify itself. Every tool, every license, every complexity should answer “Why?” with something better than “We’ve always done it this way.”

Ready to optimize your infrastructure? Our DevOps consulting services include comprehensive infrastructure audits that often uncover significant cost savings. Contact us to review your stack.