May and Might for Uncertainty

By the end of this lesson, you will be able to...

• Use might to write a careful incident hypothesis when the evidence is incomplete.

• Use may for possible behavior or consequence in a more formal technical sentence.

• Separate uncertainty language from capability, suggestion, and proof.

Idea in one sentence: Use may and might when the technical claim is possible, but not proven yet.

Core Insight

The last review lesson helped you separate capability from possibility:

The system can recover, but it could still lose logs.

Now we need a different kind of possibility.

Sometimes you are not proposing an option. Sometimes you are not stating a known capability. Sometimes you are looking at partial evidence and saying:

This may be true, but we do not know yet.

That is where may and might are useful.

The central practice line is:

The spike might be related to the deploy.

This sentence does not say the deploy caused the spike. It says the deploy is a plausible explanation.

That is a very important difference in technical work.

During an incident, a false certainty can send the team in the wrong direction. A careful hypothesis keeps the investigation open.

The first useful pattern is:

signal + might be related to + possible cause

Examples:

The spike might be related to the deploy.
The timeout increase might be related to the new cache path.
The login failures might be related to the token rotation.

Each sentence says: "This is possible, but we need more evidence."

The Small Situation

Imagine a product API again.

At 14:05, the team deploys a new version of the checkout service. At 14:08, the latency dashboard shows a spike. P95 latency jumps from 180 ms to 900 ms. Error rate also rises a little.

A teammate writes:

The deploy caused the spike.

That may become true later. Right now it is too strong.

The team has only a few facts:

• The deploy happened before the spike.
• The spike appears in the same service.
• Database CPU is normal.
• One region is worse than the others.
• The team has not rolled back yet.

The safer sentence is:

The spike might be related to the deploy.

Now the sentence matches the evidence.

It names a possible cause without pretending the investigation is finished.

That is the job of might in this lesson.

The Naive Idea

The naive idea is:

might = weak English

That is not right.

Might is weak only if the sentence hides the evidence.

Weak:

Something might be wrong.

Useful:

The latency spike might be related to the checkout deploy because it started three minutes after the rollout.

The second sentence is careful, but not empty. It gives a signal and a possible cause.

The naive opposite mistake is to sound certain too early:

The deploy caused the spike.

That sentence should wait until the team has stronger evidence, such as a rollback reducing the spike, logs pointing to the new path, or a comparison between old and new versions.

The trade-off is this:

Strong certainty is faster to read, but it can overclaim.
Uncertainty is safer, but it needs evidence to stay useful.

Good technical English does not make every sentence cautious. It makes the caution match the evidence.

May, Might, and Could

May, might, and could can all point to possibility.

They do not always do the same job.

Use could for an open option:

We could roll back the deploy.

The team is considering an action.

Use might for an uncertain explanation:

The spike might be related to the deploy.

The team is considering a cause.

Use may for possible behavior or consequence, often in more formal technical writing:

Requests may time out while the cache is warming.

That sentence often appears in release notes, runbooks, docs, or warnings. It says the behavior can happen, but not always.

Here is the contrast:

This is not a perfect probability scale. Do not treat may as exactly 60% and might as exactly 40%.

In technical work, the more useful question is:

Am I proposing an action, naming a possible cause, or warning about possible behavior?

A Worked Investigation Trace

Let us trace the incident update.

Starting facts:

14:05 - checkout service deploy starts
14:08 - p95 latency rises from 180 ms to 900 ms
14:09 - database CPU is normal
14:11 - errors are higher in eu-2 than eu-1
14:13 - no rollback has happened yet

First draft:

The deploy caused the spike.

This jumps from correlation to proof. The deploy and spike are close in time, but the team has not shown cause yet.

Second draft:

The spike might be related to the deploy.

This is better. It gives a hypothesis and leaves room for more evidence.

Third draft:

The spike might be related to the deploy because latency rose three minutes after rollout started, but we have not confirmed the cause yet.

This is stronger as an incident update. It names the signal and the uncertainty.

Now add a possible next action:

The spike might be related to the deploy because latency rose three minutes after rollout started. We could roll back eu-2 first to test whether latency drops.

Notice the two different modals:

• might names the uncertain cause;
• could opens a possible action.

That is the step this lesson adds to the track. You can now write a hypothesis and a next action without making either one sound like proof.

Check: In the last update, why is might better than caused?

Think first, then reveal.

Answer: The team has timing evidence, but not proof. Might be related to states a plausible cause without closing the investigation too early.

Let the Evidence Move the Modal

The modal should change as the investigation changes.

At the start, the team has only timing evidence. The deploy happened, then the spike happened. That is enough for a hypothesis, not enough for proof.

Good early update:

The spike might be related to the deploy because it started three minutes after rollout.

Next, the team compares regions. The spike is high in eu-2, where the new version has 100% traffic. It is lower in eu-1, where the rollout is only 10%. That makes the hypothesis stronger, but still not final.

Better update:

The spike might be related to the deploy. It is strongest in eu-2, where the new version has all traffic.

Then the team rolls back eu-2. Latency drops within two minutes. Logs show the new cache path was slower than expected.

Now the language can become stronger:

The spike was caused by the new cache path in the deploy.

This is the movement:

The point is not to stay uncertain forever. The point is to avoid claiming certainty before the evidence earns it.

This is especially important in incident channels. People act on your words. If you say caused, someone may stop investigating other paths. If you say might be related, the team can test the hypothesis without treating it as proven.

So the practical rule is:

Use might while evidence is incomplete.
Use caused only after the evidence explains the symptom better than the alternatives.

That rule protects both accuracy and collaboration.

A Useful Incident Update Shape

A good uncertainty update often has three pieces:

1. the signal;
2. the possible cause;
3. the next check.

For example:

The spike might be related to the deploy because it started three minutes after rollout. We could roll back eu-2 first and compare latency.

The first sentence is the hypothesis. The second sentence is the test.

This shape is better than a vague maybe:

Something might be wrong with the deploy.

That sentence does not give the reader a useful signal or a next action.

It is also better than premature certainty:

The deploy caused the spike, so we should roll back everything.

That may be correct later. At the start, it jumps too far.

The careful version still moves the work forward:

The spike might be related to the deploy because it started three minutes after rollout. We could roll back eu-2 first and compare latency.

This is not weak. It is disciplined.

It says what you see, what you suspect, and how the team can learn more.

When May Sounds Better

Might is very natural in incident hypotheses:

The spike might be related to the deploy.

May often sounds a little more formal. It is useful when you describe possible behavior in docs, release notes, warnings, or runbooks:

Requests may time out while the cache is warming.
Users may see stale results for up to one minute.
The worker may retry the job if the first attempt times out.

These sentences do not mean the behavior always happens. They warn that it is possible.

Use may when the reader needs to know about allowed or possible behavior.

Use might when you are investigating and the cause is still uncertain.

Compare:

Runbook:
Requests may time out while the cache is warming.

Incident update:
The timeout spike might be related to cache warming.

The runbook describes a known possible behavior. The incident update gives a hypothesis about the current symptom.

Common Confusions

Confusion: Might Means I Have No Evidence

Why it is tempting:

Might sounds uncertain.

Better model:

Might should often come with a signal.

Weak:
The spike might be related to something.

Better:
The spike might be related to the deploy because it started three minutes after rollout.

The second sentence is uncertain, but evidence-based.

Confusion: May and Can Are the Same

Why it is tempting:

Both can describe something possible.

Better model:

Can often states capability. May often warns about possible behavior.

Capability:
The system can recover traffic after a region failure.

Possible behavior:
Requests may time out while the cache is warming.

The first sentence is about what the system is able to do. The second is about what might happen under a condition.

Confusion: Could and Might Are Interchangeable

Why it is tempting:

Both can feel like "maybe."

Better model:

Use could when the team is considering an action. Use might when the team is considering an explanation.

Action:
We could roll back eu-2 first.

Explanation:
The spike might be related to the deploy.

Confusion: Might Means Wait and Do Nothing

Why it is tempting:

Might sounds less decisive than caused.

Better model:

Might should keep the investigation honest, not passive. A good might sentence often points to the next check.

Passive:
The spike might be related to the deploy.

Actionable:
The spike might be related to the deploy, so we could roll back eu-2 first and compare latency.

The second sentence is still uncertain. It is also useful. It gives the team a small test that can make the next update more certain.

Trade-offs and Limits

The trade-off with may and might is caution versus clarity.

They help you avoid overclaiming:

The spike might be related to the deploy.

That is safer than blaming the deploy too early.

But too much uncertainty can become noise:

Too vague:
The issue might be related to something in the system.

That sentence protects the writer, but it does not help the reader.

Useful uncertainty names a signal, a possible cause, or a condition:

The spike might be related to the deploy because latency rose three minutes after rollout.
Requests may time out while the cache is warming.

There is also a limit: might does not replace investigation. It buys time for evidence. After the team confirms the cause, update the language:

Early:
The spike might be related to the deploy.

After evidence:
The spike was caused by the new cache path.

The modal should change when the evidence changes.

It should also change when the evidence rejects the hypothesis. If rollback does not reduce latency, say that the spike is probably not related to the deploy and move to the next signal.

Practice

Choose the best sentence for each situation.

1. The team sees a latency spike three minutes after a deploy, but has not confirmed cause.

The spike might be related to the deploy.
The deploy caused the spike.

Best: might, because the evidence is incomplete.

1. The runbook warns about behavior during cache warmup.

Requests may time out while the cache is warming.
Requests caused timeouts while the cache is warming.

Best: may, because the runbook describes possible behavior.

1. The team is considering an action.

We could roll back eu-2 first.
The rollback might be eu-2 first.

Best: could, because the team is proposing an action.

Now rewrite these overconfident updates:

1. The deploy caused the spike.
2. Cache warming is causing all timeouts.
3. The new worker broke the queue.

Model answers:

1. The spike might be related to the deploy because it started three minutes after rollout.
2. The timeouts might be related to cache warming, but we need to compare warm and warm-cache requests.
3. The queue delay might be related to the new worker because only jobs handled by that version are slow.

Each rewrite keeps the investigation open and adds a reason.

Daily Practice Lines

Repeat these three lines during the day:

The spike might be related to the deploy.
The system can recover, but it could still lose logs.
The client cannot retry without a request id.

Then change one piece:

spike -> timeout increase -> login failure -> queue delay
deploy -> cache change -> token rotation -> new worker
related to -> caused by only after evidence confirms it

Keep the practice small. You are training this question:

Do I have proof, or only a plausible explanation?

The next lesson adds a stronger modal:

Every request must include an idempotency key.

That is not uncertainty. That is a requirement.

Resources

• [ARTICLE] Cambridge Dictionary Grammar: May, might and could - Use this for the grammar distinction, then apply it to incident hypotheses.
• [ARTICLE] Google SRE Book: Managing Incidents - Use this for the operational context where hypotheses should stay separate from confirmed causes.
• [ARTICLE] Microsoft Writing Style Guide - Use this to keep uncertainty statements clear instead of vague.

Key Takeaways

• Might is useful for uncertain incident hypotheses: The spike might be related to the deploy.
• May is useful for possible behavior in more formal technical writing: Requests may time out while the cache is warming.
• Could usually opens an option when the subject is the team: We could roll back eu-2 first.
• Good uncertainty names a signal or condition. It does not hide behind vague wording.
• Change the modal when the evidence changes: might be related can become was caused by after confirmation.