The Analog Incident Observatory Loft: Drawing Paper Orbits for Incidents That Keep Returning

Every ops team has that incident.

The one that keeps coming back.

Different day, slightly different symptoms, maybe a new error code or a different service in the blast radius—but underneath, it feels eerily familiar. You fix it, move on, and a few weeks later it’s back, like a planet completing its orbit.

This is where I like to imagine the “Analog Incident Observatory Loft”: a quiet, dedicated corner—physical or metaphorical—where you step away from dashboards and paging systems, grab a piece of paper, and literally draw the orbit of incidents that keep returning.

It’s a reminder that even in hyper-automated environments, sometimes the most powerful move is to stop, zoom out, and observe.

In this post, we’ll explore how treating incident trends like celestial orbits can transform incident management from noisy, reactive firefighting into predictable, proactive prevention.

From Firefighting to Astronomy: Why Trend Analysis Matters

Most organizations are stuck in reactive incident management:

• Something breaks.
• Alerts fire.
• People scramble.
• The issue is patched.
• Everyone collapses back into their backlog.

This is necessary—but not sufficient.

Trend analysis is what turns this cycle into something more strategic. Instead of seeing incidents as isolated explosions, you start viewing them as data points in a larger constellation.

Trend analysis means:

• Collecting incident data over time
• Visualizing patterns (frequency, severity, components, times of day/week)
• Asking “What keeps repeating?” instead of “What broke this time?”

When you do this consistently, your incident history stops being a graveyard and becomes a map.

In the “loft,” this might look like:

• A wall of sticky notes grouped by incident type
• A hand-drawn timeline of similar incidents
• A simple notebook with recurring symptom clusters and rough dates

It doesn’t have to be sophisticated. What matters is that you’re seeing trends instead of snapshots.

Drawing Paper Orbits: Visualizing Recurring Incidents

The idea of “drawing paper orbits” is intentionally low-tech.

Before you open a BI tool or build a dashboard, try this analog exercise:

1. List the last 10–20 significant incidents.
   Include date, affected systems, symptom, suspected cause, and resolution.

2. Circle the ones that feel familiar.
   The repeated alerts. The same flaky service. The “oh, this again” moments.

3. Group them into orbits.
   Think of each orbit as a recurring theme:

   • Latency spikes in a given region
   • Database connection saturation
   • Cache misconfigurations
   • Misrouted traffic during deploys

4. Draw the orbit.
   On paper, literally:

   • Write the core underlying issue in the center (e.g., “Database connection pool exhaustion”).
   • Place each related incident as a point on a circular orbit around it, dated.
   • Note the conditions: time, traffic levels, recent changes, impacted services.

5. Look for gravitational forces.
   Ask:

   • What common preconditions exist before each orbit completes?
   • Does a specific deploy type, traffic spike, or dependency issue appear repeatedly?
   • Are we seeing escalating severity, or just noise?

This simple exercise has one aim: make recurring incidents impossible to ignore. Paper forces focus. It slows your thinking to the pace of clarity.

Once you’ve done this, that recurring incident is no longer a surprise guest. It’s a known planet, following a trajectory.

Finding Root Causes in the Patterns

Trend analysis is only as valuable as the action it unlocks. The real power comes when you use discovered patterns to identify root causes instead of continually treating symptoms.

When you see the same orbit complete three, four, five times, you can start asking better questions:

• What’s the structural weakness that allows this to happen at all?
• Which assumptions about our architecture keep being disproven?
• Where are we relying on manual heroics instead of systemic fixes?

Common root causes uncovered by trend analysis include:

• Chronic capacity mis-sizing (e.g., instances routinely saturate at the same time every week)
• Single points of failure disguised by partial redundancy
• Flaky third-party dependencies without proper fallbacks
• Implicit knowledge that lives in one engineer’s head and nowhere else
• Misaligned alerts that trigger too late, too often, or not at all for the right signals

By systematically connecting recurring incidents to these root causes, you:

• Reduce the likelihood of incidents returning
• Turn ad-hoc fixes into structural improvements
• Shorten time-to-diagnosis because you’ve seen this orbit before

Over time, the goal is that each orbit you’ve drawn on paper eventually stops repeating—or at least appears less frequently and with less impact.

From Orbits to Continuity: Proactive Incident Response

When you know which incidents tend to repeat, you gain a powerful ability: anticipation.

Proactive incident response means using trend insights to:

• Predict high-risk windows (e.g., peak traffic times, major release days)
• Pre-stage mitigations like extra capacity, dark launches, or canary rolls
• Adjust playbooks so on-call engineers know, “If you see X, it’s probably Y”

This has a direct effect on business continuity:

• Fewer surprise outages
• Shorter and less severe disruptions
• More predictable operational behavior

Instead of “We’ll fix it when it breaks,” you move toward “We’ll prepare because it’s likely to break in this specific way—and here’s how we’ll absorb it.”

Building Network Resilience: More Than Just Uptime

Incidents often orbit around the network—the connective tissue of your systems.

Network resilience isn’t a single feature; it’s the combination of:

• Redundancy – Multiple paths, instances, or providers so traffic has alternatives.
• Low latency – Efficient routing to avoid slowdowns that cascade into timeouts, retries, and overload.
• Intelligent failover – Automated routing decisions when a path or region degrades, not just hard-fails.
• Proactive monitoring – Detecting anomalies before they bloom into full-blown downtime.

Trend analysis on network-related incidents might reveal:

• Persistent issues in a specific region or ISP
• Latency spikes tied to certain workloads or customer cohorts
• Failover logic that technically exists but misbehaves under real load

Once identified, you can:

• Add or adjust redundant paths
• Tune failover thresholds and policies
• Implement synthetic checks from key geographies
• Optimize routing strategies for both resilience and latency

The key idea: every network incident isn’t just a scare—it’s a data point in understanding how resilient your topology really is.

Integrated Incident Response: From Noise to Flow

As your systems grow, the sheer process of handling incidents can become an incident of its own.

This is where integrated incident response platforms shine. They help streamline:

• On-call management – Rotations, schedules, and escalation chains
• Notifications – Multi-channel alerting (SMS, email, chat, voice) with clear routing
• Communication – War rooms, status pages, internal updates, and stakeholder comms

When these capabilities live in one place, your response shifts from chaotic improvisation to repeatable choreography.

Tie this back to trend analysis:

• You can track which teams are repeatedly pulled into similar incidents.
• You can see which playbooks are most used—or missing.
• You can evaluate MTTA (Mean Time to Acknowledge) and MTTR (Mean Time to Resolve) by incident type.

Your observatory view now includes not only systems but also human workflows.

Push-Button Response: Automating the First Moves

Once you’ve identified recurring orbits and the best ways to stabilize them, you can start to automate the opening moves.

Automated, push-button incident response solutions can:

• Trigger predefined runbooks when certain patterns of alerts appear
• Auto-scale resources or shift traffic when thresholds are breached
• Open incident channels, assign roles, and notify the right people instantly

This accelerates:

• Detection – Correlated alerts fire as a known pattern, not as independent noise
• Escalation – The right team is engaged automatically
• Resolution – First-line mitigations are executed without hesitation or confusion

Importantly, automation doesn’t replace human judgment; it buys you time. It clears away repetitive, low-level tasks so humans can focus on diagnosis and strategy—on understanding why this orbit exists at all and how to change its trajectory.

Bringing It All Together in Your Own Loft

You don’t need a literal attic full of whiteboards and star charts—though that sounds nice.

To create your own Analog Incident Observatory Loft:

1. Make incident review a habit, not an afterthought.
   Schedule regular sessions to review recent incidents with a focus on recurrence.

2. Use paper first, tools second.
   Draw orbits. Cluster incidents by theme. Let the patterns emerge visually before you encode them into dashboards.

3. Name your recurring incidents.
   “The Tuesday Latency Orbit.” “The East-Region DNS Eclipse.” Shared names make trends social and memorable.

4. Tie patterns to root-cause work.
   Every recurring orbit should have a documented plan: mitigate now, eliminate later.

5. Invest in resilience and automation where it hurts most.
   Strengthen network resilience, refine failover, improve monitoring, and automate known mitigations.

6. Feed everything back into your incident platform.
   Turn insights into runbooks, alerts, playbooks, and routing rules.

Conclusion: Changing the Gravity of Your Incidents

Incidents that keep returning are not just annoyances; they’re signals. They’re telling you where your systems—and your processes—are out of alignment.

By stepping into your own Analog Incident Observatory Loft and drawing the orbits of those incidents, you:

• Move from reactive firefighting to deliberate prevention
• Use trend analysis to spot and eliminate root causes
• Improve business continuity by anticipating disruption
• Build network resilience that can absorb shocks gracefully
• Leverage integrated platforms and push-button automation to handle the rest with speed and clarity

You can’t stop every star from exploding. But you can understand the sky well enough that, when something does go wrong, it’s no longer a surprise—it’s a known object, on a known path, with a known response.

That’s the power of treating your incidents not as random chaos, but as orbits you can observe, map, and ultimately reshape.