Introduction

Every morning at 9 AM, our Security Engineering team would gather for our daily standup, and the conversation always started the same way: "How many CSPM alerts came in overnight?" The answer was consistently high, anywhere from 20-100+ alerts that needed our attention and analysis.

As a Security Engineer at Cyera, I recognized this as a common challenge in the security industry: distinguishing signal from noise in our security tooling. We were spending significant time investigating alerts that turned out to be benign configuration changes or expected business activity. Meanwhile, the genuine security events that required immediate attention were sometimes delayed in our response queue, which wasn't the level of security operations we wanted to maintain.

I remember thinking: "There has to be a better way. We're security engineers, not alert triagers." That frustration sparked an idea, what if I could build something that would intelligently filter these alerts and respond automatically to real threats? This is how I built my own solution: a FastAPI-based Security Event Gateway, which transformed our security operations from reactive alert triage to proactive automated threat response.

The Problem

Like many security teams, we were facing the classic CSPM challenge: alert fatigue. Cloud Security Posture Management tools are incredibly powerful for detecting potential security issues, but they often generate high volumes of alerts that require human analysis to distinguish between genuine threats and expected business activity.

Our situation was typical of fast-growing companies: 100+ alerts per week during peak periods, with what I estimated to be an 85% rate of alerts requiring no action after investigation. Each alert took 15+ minutes to properly triage, meaning we were spending 1-2 hours daily on alert investigation.

The timing challenge was another problem. With our engineering team primarily in Eastern time zones, routine alerts generated during off-hours would accumulate in our queue until the next business day. While we maintained appropriate escalation procedures for critical threats, the volume of routine alerts was creating operational overhead that we wanted to optimize.

The human impact was what concerned me most. My security engineering colleagues were spending significant time on repetitive alert triage instead of strategic security work. We'd investigate "critical" findings that turned out to be legitimate business activities such as data science teams accessing their own resources, automated backup processes triggering CloudTrail alerts, or expected configuration changes flagged as policy violations. This context switching was reducing our efficiency and job satisfaction.

Challenges

As I started sketching out the solution, I realized I was facing several technical and business challenges simultaneously. From a business perspective, I needed to prove that custom automation could deliver measurable ROI while positioning our team for fully autonomous security operations. I kept asking myself: "How do I build something that not only solves today's problem but proves we can scale this approach across all our security tools?"

The technical requirements were equally demanding: sub-100ms internal processing (because real-time response matters), intelligent false positive filtering based on our specific environment, 24/7 automated response to optimize our global operations, and a developer-friendly architecture that my team could actually maintain and extend.

I spent a lot of time thinking about the architectural decisions. Why FastAPI? Because I needed excellent async support and automatic documentation that would make onboarding other engineers easier. Why Google Pub/Sub? Because I wanted reliable message queuing without managing infrastructure. Why Cloud Run? Because the pay-per-use pricing model meant I could prove the concept without significant upfront costs. I remember thinking: "If this fails, at least it won't be because we spent too much money on infrastructure."

The Solution

I decided to build my own Security Engineering Event Gateway using modern cloud-native technologies. The core idea was simple: create a FastAPI service that could receive CSPM webhooks, intelligently process them, and trigger automated responses for real threats while filtering out false positives.

This PoC was designed to prove that the Event Gateway concept could scale into a solution that defines what our team could become: fully autonomous security. By gathering real performance data and measuring the impact, I could evaluate whether this approach was worth expanding into a comprehensive security automation platform.

Architecture Overview

Technical Implementation

I started with a focused proof-of-concept: CSPM Webhook Processing. The goal seemed simple: receive CSPM alerts, intelligently filter them, and automate responses for real threats. How hard could it be?

The Challenge That Humbled Me

My first major hurdle wasn't architectural: it was handling webhook format variations. I discovered that our CSPM tool sends webhooks with Content-Type: application/octet-stream instead of the more common application/json. This is actually not uncommon in enterprise security tools, but it caused FastAPI to reject every webhook with 422 errors.

I remember staring at the logs thinking: "This should be working. The JSON looks fine, the endpoint is correct... what am I missing?" It took me some debugging to realize that FastAPI's automatic JSON parsing was failing because of the content type. This taught me an important lesson about webhook integration: always validate the actual format first, regardless of documentation.

# Problem
@router.post("/cspm")  # This failed!
async def cspm_webhook(payload: dict = Body(...)):
    # Never reached due to content-type issues
    pass

# Solution
@router.api_route("/cspm", methods=["POST"])
async def cspm_webhook_handler(request: Request):
    # Read raw body and parse manually
    body = await request.body()
    try:
        payload = json.loads(body.decode())
    except json.JSONDecodeError:
        raise HTTPException(status_code=400, detail="Invalid JSON")
    
    # Now we can process the webhook
    return await process_cspm_event(payload)

The CSPM Event Processor

My PoC focuses on two types of CSPM events:

1. Threat Detections: Active security threats and suspicious activity
2. Configuration Findings: Misconfigurations and policy violations

Here's how I process these events:

async def process_event(self, 
                        payload: Dict[str, Any])
                        -> Dict[str, Any]:
                        
        # Parse the CSPM event 
        # (either threat detection or config finding)
        event_type = payload.get("category", "").lower()
        
        if "threat" in event_type or "config" in event_type:
            event = cspmThreatDetectionEvent.parse_obj(payload)
        else:
            event = cspmConfigurationFindingEvent.parse_obj(payload)
        
        # Extract key information
        cloud_info = {
            "cloud_provider": event.resource.cloud_provider,
            "cloud_account_id": event.resource.cloud_account_id,
            "resource_name": event.resource.name,
            "resource_type": event.resource.type,
            "region": event.resource.region or "unknown"
        }
        
        # Execute my security playbook
        await self._execute_security_playbook(
            event_id=event.id,
            title=event.title,
            description=event.description,
            severity=event.severity,
            cloud_info=cloud_info,
            payload=payload
        )
        
        return {"status": "processed", "event_id": event.id}

The Playbook

This is where the real magic happens. My PoC implements an intelligent security playbook that handles both threat detections and configuration findings. I wanted to build something that could make the same decisions I would make, but faster and more consistently:

async def _execute_security_playbook(
    self, event_id: str, title: str, description: str, 
    severity: str, cloud_info: Dict[str, str], payload: Dict[str, Any]
):
    """Execute my automated security response playbook."""
    
    # Step 1: Check Asset Exceptions (configuration management)
    is_exception = await self._check_cloud_asset_exceptions(cloud_info)
    
    if is_exception:
        # Auto-archive if it's a known exception
        await self._archive_threat_in_cspm(event_id)
        return {"status": "archived", "reason": "known_exception"}
    
    # Step 2: Follow analyst playbook for real findings
    actions = [
        {
            "type": "send_slack_notification",
            "status": "in_progress",
            "description": "Sending Slack notification to user"
        },
        {
            "type": "create_jira_ticket",
            "status": "pending", 
            "description": "Creating JIRA ticket for tracking"
        }
    ]
    
    # Step 3: Send notification to the user
    console_link = payload.get(
        "console_link",
        f"https://console.example.com/
        threats?selectedDetectionId={event_id}"
    )
    
    event_details = {
        "cloud_provider": cloud_info["cloud_provider"],
        "account_id": cloud_info["cloud_account_id"], 
        "resource_name": cloud_info["resource_name"],
        "resource_type": cloud_info["resource_type"],
        "region": cloud_info["region"],
        "console_link": console_link
    }
    
    # Send Slack notification informing user of misconfiguration/threat
    await self.slack_notifier.post_security_event(
        event_id=event_id,
        source="Security Tool",
        severity=severity,
        title=title,
        description=description,
        details=event_details,
        actions=actions
    )
    
    # Step 4: Create JIRA ticket for status tracking
    await self._create_jira_ticket(event_id, title, description, severity)

The Results

After deploying my Event Gateway PoC, the transformation was measurable and immediate. I'll be honest, I was nervous about whether this would actually work in production. But the data exceeded my expectations. Here's what I presented to leadership:

SecEng Event Gateway: 2-Week Performance Analysis

• Time Savings: ~2 weeks of analyst time saved through automation
• Financial Impact: $1,000 saved in 2 weeks, projected $2.1k/month, $25k/year if trend holds
• Event Processing: 120 cloud security events processed with 90% noise reduction
• Performance: Gateway internal processing <100ms; total E2E ~3.6s (remainder is downstream I/O to Slack/BigQuery)
• Infrastructure Cost: $0.51/day for the entire platform
• Reliability: 100% uptime since deployment

Impact

Before: Our team spent 2+ hours each morning triaging overnight alerts. The volume of routine alerts was creating operational overhead, with engineers spending significant time on repetitive investigation work instead of strategic security initiatives.

After: The 90% noise reduction transformed our daily operations. Instead of processing 200+ alerts, analysts now review fewer than 20 pre-filtered, actionable events. Automated responses now handle routine events in under 30 seconds. Most importantly, we freed up ~2 weeks of analyst time in just the first month, allowing the team to focus on strategic security initiatives rather than alert triage.

Key Realizations

Looking back, starting small and focused was crucial, I didn't try to solve every security automation problem at once. I kept reminding myself: "Perfect is the enemy of good. Get something working first, then make it better." Focusing on our biggest pain point (CSPM false positives) allowed me to prove the concept quickly, learn from real production data, build confidence with the team, and iterate based on actual usage.

The real-time webhook approach was a game-changer that I didn't fully appreciate until I saw it in action. Unlike traditional approaches that poll APIs every few minutes, my webhook-based approach provides instant notifications when threats occur, no polling delays or API rate limiting issues, lower infrastructure costs (no constant API calls), and a better user experience with immediate Slack alerts. I remember the first time I saw a real threat get processed and responded to in under 30 seconds, it felt like magic.

Building with FastAPI and Python was a strategic choice that paid off. It gave me proper testing with pytest and comprehensive test coverage, version control with Git and proper code review processes, CI/CD integration with automated deployments, easy debugging with structured logging and error handling, and team knowledge sharing since everyone on the team knows Python. I thought: "If I get hit by a bus tomorrow, someone else should be able to maintain this."

The Future

The PoC proved that custom security automation can deliver measurable business value while positioning our team for fully autonomous operations. Based on this success, I'm expanding the Event Gateway to handle additional security tools and use cases.

My immediate focus is on EDR integration for automated endpoint threat containment, IAM integration for identity-based threat response, and VM integration. Each integration follows the same pattern: intelligent filtering, automated response for high-severity events, and comprehensive audit trails.

The broader vision is creating a unified security automation platform that can handle any security tool's webhooks, apply consistent business logic for threat assessment, and execute appropriate response playbooks; all while maintaining the sub-100ms internal processing performance that makes real-time response possible.

Note: These roadmap items are subject to change based on business priorities and threat landscape evolution.

Lessons Learned

Building my Event Gateway taught me valuable lessons about security automation; some through success, others through frustration. What worked really well was starting with the biggest pain point (CSPM false positives gave immediate ROI), real-time webhooks (much faster and more reliable than polling-based approaches), comprehensive testing (my regression test suite prevented production issues), structured logging (made debugging and monitoring much easier), and modular architecture (easy to add new integrations without breaking existing ones).

The challenges I overcame were humbling. Webhook format issues (CSPM's application/octet-stream content type caught me off guard), route registration conflicts (FastAPI's auto-discovery conflicted with my manual routes in ways I didn't expect), error handling (generic 422 errors provided no debugging information initially, I learned to hate these), and false positive tuning (required more iterative refinement based on real production data than I anticipated).

If I were starting over, I'd do several things differently: start with webhook format validation (test content types and parsing early, would have saved me hours), add more comprehensive metrics (better visibility into automation effectiveness), and implement gradual rollout (deploy new playbooks to staging environments first). The biggest lesson? Always assume the vendor's documentation is incomplete.

Why Build vs Buy?

After proving the concept with measurable results, it's worth comparing this custom approach to traditional SOAR platforms I evaluated.

Cost Considerations: Enterprise SOAR platforms typically cost $50,000-200,000+ annually, while my Event Gateway runs on $0.51/day ($186/year). For our specific use case and team size, the custom solution provided better cost efficiency. When factoring in the $25k/year in analyst time savings, the ROI was compelling for our situation.

Customization & Performance: Commercial platforms offer comprehensive features but sometimes include complexity we didn't need. My solution achieves sub-100ms internal processing with full control over business logic, optimized specifically for our environment and use cases. The ability to integrate with any tool that supports webhooks gave us flexibility.

Development Approach: While visual workflow builders in commercial SOAR platforms are excellent for many organizations, our team preferred clean Python code with proper testing, version control, and CI/CD. This approach aligned well with our existing development practices and made adding new integrations straightforward.

Getting Started

If you're a Engineer, Manager, or Architect considering a similar approach, think beyond the technical implementation. The real value lies in transforming your team's operational model from reactive alert triage to proactive threat hunting and strategic security initiatives.

Start with Business Impact: Identify your highest-cost manual processes. For us, it was CSPM alert investigation consuming significant analyst time. Calculate the financial impact and ROI potential, even a 50% reduction in routine alert processing can deliver immediate value.

Prove the Concept with Data: Build a simple PoC that measures everything from day one. Track processing times, false positive rates, time saved per analyst, and infrastructure costs. Present these metrics to leadership in terms they understand: analyst time freed up for strategic work, cost per event processed, and reliability metrics.

Design for Scale: Choose technologies that can grow with your automation ambitions. Real-time webhooks scale better than polling, cloud-native infrastructure adapts to demand, and clean code with proper testing enables rapid iteration. The goal isn't just solving today's problem, it's building the foundation for fully autonomous security operations.

Think Platform, Not Point Solutions: Each integration should follow consistent patterns for authentication, logging, error handling, and response workflows. This modular approach makes adding new security tools straightforward and maintains operational consistency across your entire security stack.

Conclusion

Six months ago, our security team was facing the common challenge of alert fatigue from our security tooling. We were spending significant time on alert triage rather than strategic security initiatives. Today, we have an intelligent Event Gateway that automates the routine analysis and allows our team to focus on high-value security work.

What I Achieved

• Transformed our daily routine: From 2+ hours of alert triage to 15 minutes of strategic review
• Eliminated alert fatigue: 95.85% noise reduction and 90% reduction in false positive investigation time
• Optimized global operations: 24/7 automated response for routine events
• Accelerated response times: Automated responses now handle routine events in under 30 seconds
• Saved significant costs: 99.9% cost reduction compared to enterprise SOAR platforms (~$10/month vs $50K+)
• Improved team morale: Engineers focused on strategic security work instead of repetitive tasks

The Bigger Picture

My Event Gateway demonstrates that small security teams have multiple paths to achieve world-class automation. While enterprise SOAR platforms serve many organizations well, custom solutions can be highly effective when you have specific requirements and development capabilities. With modern cloud technologies and thoughtful architecture, teams can build solutions perfectly tailored to their unique environments.

What makes this even more compelling is how modern development practices and cloud-native technologies are making it easier than ever to build custom solutions that perfectly fit your organization's needs. Complex integrations that once required months of development can now be prototyped in days with the right architectural choices and tooling.

The future of security operations isn't about having humans manually triage every alert; it's about building intelligent systems that can distinguish real threats from noise, respond faster than any human could, and free up engineers or analysts to focus on the strategic work that actually requires human judgment. Every security team can become a development team, building exactly the automation they need to complement existing security tools.

If you're facing similar challenges with security alert fatigue, I encourage you to consider building your own solution. The learning curve is worth it, and you'll end up with something perfectly tailored to your organization's needs. My journey from alert fatigue to autonomous security response shows that with the right approach, small teams can achieve enterprise-grade security automation without enterprise-grade budgets.

Key takeaways: Start with your biggest pain point (don't try to automate everything at once), real-time webhooks beat polling (faster, more reliable, and cost-effective), custom solutions can complement commercial tools (when you control the logic, you can optimize for your specific needs), developer-friendly approaches scale better (clean code, proper testing, and version control matter), and measure everything (track metrics to prove ROI and identify areas for improvement).

Interested in learning more about my security automation approach? Connect with me on LinkedIn.