Table of Contents
- 1. Use Structured Logging, Not String Blobs
- 2. Use Log Levels Correctly
- 3. Log the Right Events
- 4. Never Log PII or Secrets
- 5. Attach Context to Every Entry
- 6. Use Remote Logging in Production
- 7. Control Volume: Sample, Batch, Compress
- 8. Correlate Logs with Crashes and Sessions
- 9. Plan Retention and Alerting
- 10. Standardize Across Platforms
- 11. Common Logging Mistakes
- 12. FAQ
1. Use Structured Logging, Not String Blobs
A log entry like "payment failed for user" is readable by a human and useless to everything else. Structured logging attaches machine-readable key-value pairs to every entry, so you can filter, group, and aggregate later:
log.error("payment_failed", {
gateway: "stripe",
error_code: "card_declined",
amount_cents: 4900,
retry_count: 2
})Six months from now, "show me all payment_failed events where error_code=card_declined on app version 3.2" is a ten-second query instead of a regex archaeology project. Pick stable event names (snake_case verbs work well), agree on a small set of common keys, and treat the log schema like an API — because your future debugging sessions are its consumers.
2. Use Log Levels Correctly
Log levels only help if the whole team applies them the same way. A workable contract:
| Level | Use for | In production |
|---|---|---|
| debug | Developer detail: state dumps, timing, branch decisions | Off or heavily sampled |
| info | Business events: signup completed, sync finished, purchase made | On, sampled if high-volume |
| warn | Something recovered but shouldn't happen: retry succeeded, cache miss fallback, deprecated path hit | Always on |
| error | An operation failed and the user felt it (or will) | Always on, always alertable |
The most common failure mode is level inflation: everything is error, so nothing is. If an "error" doesn't deserve a look from a human, it's a warn.
3. Log the Right Events
You can't log everything, and you shouldn't. The events that pay for themselves in nearly every debugging session:
- App lifecycle: cold start, foreground/background transitions, termination — with startup duration.
- Screen/navigation transitions: the backbone of reconstructing what a user did.
- Network failures: endpoint, status code, latency, retry count. Successful calls can be sampled; failures never.
- State transitions in money paths: auth, checkout, sync, upload — every step, both directions.
- Handled exceptions: every catch block that swallows an exception should log it. Silent catches are where bugs go to hide.
- Permission and configuration changes: notifications denied, offline mode, feature flags evaluated.
Skip per-frame events, raw render loops, and anything that fires more than a few times per second — that belongs in performance tooling, not logs.
4. Never Log PII or Secrets
Logs are stored personal data under GDPR and CCPA. The block list is non-negotiable: passwords, auth tokens, API keys, session cookies, full request/response headers, card numbers, health data, precise location, emails, and phone numbers.
Enforce it structurally, not by hoping:
- Identify users by an internal ID, never by email or name.
- Redact at the logging wrapper level — a deny-list of key names (
token,password,authorization) that masks values before anything leaves the device. - Never log full request bodies by default; log the fields you chose on purpose.
- Make "no PII in logs" a code-review checklist item for any new log statement.
One leaked token in a log line shared to a Slack channel is a security incident. Redaction at the source is cheap; cleanup is not.
5. Attach Context to Every Entry
A log line without context answers "what happened" but not "to whom, where, and under what conditions." Attach automatically, once, in your logging layer: session ID, anonymous user/device ID, app version and build number, OS version, device model, network type, and free memory/disk if cheap to read.
Version context alone is decisive: the difference between "errors are up" and "errors are up only on 3.2.1 builds on Android 15" is the difference between a war room and a one-line hotfix.
6. Use Remote Logging in Production
console.log, print, and Logcat all share one property: their output dies on the user's device. The moment you ship, local-only logging is write-only memory. Remote logging ships entries to a service where you can search them — which is the entire point of having them.
Route your existing calls through a wrapper that writes locally in debug builds and remotely in release builds. Platform-specific setup guides:
- React Native logging in production
- Flutter logging and crash reporting
- Android remote logging
- Real-time logging for iOS
Or start with the platform-agnostic overview on our mobile logging page.
7. Control Volume: Sample, Batch, Compress
Mobile logging runs on hardware you don't own, batteries you don't charge, and data plans you don't pay for. Respect that:
- Batch uploads — queue entries and flush periodically or on app background, never one HTTP request per line.
- Compress payloads and prefer Wi-Fi for large flushes.
- Sample high-volume events — 1–10% of routine info events usually preserves the signal; keep 100% of warns and errors.
- Cap local queues so an offline device doesn't grow an unbounded log file.
- Support remote verbosity control so you can turn debug logging on for one user cohort while investigating, then off again.
8. Correlate Logs with Crashes and Sessions
A crash report tells you where the app died. The logs tell you why. If they live in separate tools with no shared session ID, you'll spend debugging time copy-pasting timestamps between browser tabs.
The best-practice setup is a shared session identifier across logs, events, and crash reports, so every crash arrives with the full timeline that preceded it: the screens visited, the network calls that failed, the warnings that fired. This is the single biggest debugging-speed multiplier on this list — and it's the reason Logtrics ships logging, crash reporting, and session timelines in one SDK rather than as separate products.
9. Plan Retention and Alerting
Two questions decide whether logs help you during an incident: how far back can you look, and who finds out when something breaks?
- Retention: keep at least one full release cycle of logs — 30 days is a floor, 90+ days lets you compare against the previous quarter's release. (Logtrics paid plans retain 365 days.)
- Alerting: error spikes, new error signatures, and regressions should reach Slack or email within minutes. A dashboard nobody watches is not alerting.
- Ownership: every alert channel needs an owner, or alert fatigue sets in and the channel gets muted.
10. Standardize Across Platforms
If your iOS app logs checkout_failed and your Android app logs PaymentError, every cross-platform investigation starts with a translation exercise. Define one event vocabulary and one set of context keys, and enforce them in a shared logging spec — or use a cross-platform SDK that does it for you across iOS, Android, React Native, and Flutter.
Consistency is also what makes dashboards and alerts portable: one query, four platforms, one answer.
11. Common Logging Mistakes to Avoid
Logging only when things break
If the first log line fires at the error, you have a symptom with no history. Baseline info/warn logging is what gives errors their context.
Treating logging as a launch-week task
Retrofitting logs after a production fire means debugging that fire blind. Instrument as you build; it's a few minutes per feature.
Swallowing exceptions silently
Every empty catch block is a future "works on my machine." Log the exception with context even when you recover gracefully.
One giant log file, no levels, no structure
Volume without structure is noise you pay to store. Structure and levels are what turn logs into a queryable dataset.
12. Frequently Asked Questions
What are the most important logging best practices for mobile apps?
The essentials: use structured logs instead of free-text strings, apply log levels consistently (debug, info, warn, error), never log PII or secrets, attach context like session ID and app version to every entry, send logs to a remote logging service in production, control volume with sampling and batching, and correlate logs with crash reports so every crash comes with the events that led up to it.
What should you never log in a mobile app?
Never log passwords, auth tokens, API keys, full request headers, payment details, health data, precise location, or any personally identifiable information such as emails and phone numbers. Regulations like GDPR and CCPA treat logs as stored personal data, so redact or hash identifiers before a log entry leaves the device.
How much logging is too much in production?
Log every warning and error, key lifecycle events, and failed network calls — but sample high-frequency debug and info events. Unbounded logging drains battery, consumes user bandwidth, and buries the entries that matter. Batch uploads, compress payloads, and raise verbosity remotely only when investigating a specific issue.
Do logging best practices differ between iOS, Android, React Native, and Flutter?
The principles are identical — structure, levels, redaction, context, correlation. What differs is the plumbing: os_log/Logger on iOS, Logcat and Timber-style wrappers on Android, and the fact that console.log and debugPrint output disappears in release builds of React Native and Flutter. A cross-platform logging SDK keeps the schema consistent so one dashboard serves every platform.
Put These Best Practices on Autopilot
Logtrics gives you structured remote logging, automatic session context, PII-safe defaults, crash correlation, and Slack alerts in one SDK for iOS, Android, React Native, and Flutter. Free up to 1M events/month — set up in about 15 minutes.