Add JVM log analyzer tool
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# jvm-log-analyzer
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`jvm-log-analyzer` is a read-only Python CLI for reviewing local JVM and Java application logs. It summarizes common Java exceptions, stack trace fragments, JVM failure symptoms, database issues, network/TLS problems, HTTP 5xx entries, and repeated application warning/error patterns that require operator review.
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The tool is intended for Linux infrastructure, SRE, and application support workflows where a collected log file needs a quick first-pass operational summary. It does not modify logs or system state.
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## When To Use
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- During incident response when a JVM application log needs a fast exception and symptom summary.
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- During application support handoff when stack traces, HTTP 5xx entries, or database failures need to be attached as evidence.
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- After a restart, deployment, certificate change, database incident, or capacity event when local log extracts are available.
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- When predictable text, Markdown, or JSON output is useful for local review.
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## What It Does
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- Reads one local JVM or Java application log supplied with `--file`.
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- Detects configured critical and warning JVM/application patterns.
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- Extracts timestamps, log levels, thread names, logger/class names, exception types, raw samples, and short stack trace fragments where practical.
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- Aggregates top finding groups, exception types, and operational symptoms.
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- Produces text, Markdown, or JSON output.
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## What It Does Not Do
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- It does not read remote systems or live journal streams.
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- It does not modify logs, services, application files, JVM flags, certificates, or database state.
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- It does not query APM, ELK, SIEM, Zabbix, ticketing systems, or application APIs.
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- It does not find root cause automatically.
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- It does not prove an application defect.
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- It does not classify every vendor-specific Java framework or application message.
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## Supported Input Types
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- Java / JVM application logs.
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- Spring Boot style logs.
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- Tomcat-style application logs.
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- Generic application logs containing Java exceptions and stack traces.
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UTF-8 text input is expected. Invalid byte sequences are replaced during read so review can continue. Empty, missing, unreadable, or non-file paths are rejected with exit code `2`.
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## Supported JVM/Application Patterns
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Critical patterns:
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- `OutOfMemoryError`
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- `Java heap space`
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- `GC overhead limit exceeded`
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- `StackOverflowError`
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- `NoClassDefFoundError`
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- `ClassNotFoundException`
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- `ExceptionInInitializerError`
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- `SSLHandshakeException`
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- `CertificateExpiredException`
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- `SQLException`
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- `SQLRecoverableException`
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- `CommunicationsException`
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- `database unavailable`
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- `connection pool exhausted`
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- `HTTP 500`
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- `HTTP 502`
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- `HTTP 503`
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- `HTTP 504`
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- `FATAL`
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Warning patterns:
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- `NullPointerException`
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- `IllegalArgumentException`
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- `IllegalStateException`
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- `SocketTimeoutException`
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- `ConnectException`
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- `TimeoutException`
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- `connection refused`
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- `connection reset`
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- `Broken pipe`
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- `WARN`
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- `ERROR`
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- `retrying`
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- `slow query`
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- `deadlock detected`
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By default matching is case-sensitive. Use `--ignore-case` for case-insensitive matching across configured patterns.
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## Stack Trace Handling
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The scanner detects practical multiline Java stack traces using common starts such as:
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- Fully qualified Java exception lines, such as `java.lang.NullPointerException`.
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- `Exception in thread "main"`.
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- `Caused by:`.
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- Application exceptions ending in `Exception` or `Error`.
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Following stack frames are grouped when they look like Java frames:
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- Lines starting with whitespace followed by `at `.
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- Lines starting with `Caused by:`.
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- Lines containing `... N more`.
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Stack traces are associated with the detected exception type where possible. Text and Markdown output include only short sample lines by default. Use `--include-stacktraces` to include capped multiline stack trace fragments.
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## Timestamp Handling
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The scanner attempts to parse:
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- `2026-05-11 10:15:30`
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- `2026-05-11T10:15:30`
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- `2026-05-11 10:15:30,123`
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- `2026-05-11 10:15:30.123`
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- `May 11 10:15:30`
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Timestamp parsing is best-effort. Lines with unparseable timestamps are still analyzed. When `--since` or `--until` is used, lines without parseable timestamps are retained by default so potentially important findings are not silently discarded.
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## Severity Model
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Overall status is conservative:
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- `OK` - no JVM/application findings.
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- `WARNING` - warning-level findings exist but no critical findings exist.
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- `CRITICAL` - one or more critical findings exist.
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Critical status is driven by JVM memory failures, fatal JVM symptoms, selected class loading errors, TLS/certificate failures, database unavailable or pool exhaustion symptoms, and HTTP 5xx volume at or above the configured threshold.
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Warning status is driven by non-fatal exceptions, `WARN`/`ERROR` entries, timeout/retry patterns, connection refused/reset symptoms, slow query findings, and deadlock patterns.
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HTTP 5xx findings are warnings until their total reaches `--http-critical-threshold`, which defaults to `5`. The report summarizes findings that require review; it does not claim root cause.
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## Usage
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```bash
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cd infra-run/scripts/python/jvm-log-analyzer
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python3 jvm_log_analyzer.py --file examples/sample-jvm-app.log
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python3 jvm_log_analyzer.py --file examples/sample-jvm-app.log --format markdown
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python3 jvm_log_analyzer.py --file examples/sample-jvm-app.log --format markdown --output jvm-report.md
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python3 jvm_log_analyzer.py --file examples/sample-jvm-app.log --format json
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python3 jvm_log_analyzer.py --file examples/sample-jvm-app.log --top 10
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python3 jvm_log_analyzer.py --file examples/sample-jvm-app.log --max-samples 5
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python3 jvm_log_analyzer.py --file examples/sample-jvm-app.log --include-stacktraces
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python3 jvm_log_analyzer.py --file examples/sample-jvm-app.log --since "2026-05-11 10:00:00"
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python3 jvm_log_analyzer.py --file examples/sample-jvm-app.log --until "2026-05-11 12:00:00"
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python3 jvm_log_analyzer.py --file examples/sample-jvm-app.log --http-critical-threshold 2
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```
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## Output Formats
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- `text` - default terminal-oriented report.
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- `markdown` - incident or application support ticket attachment format.
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- `json` - structured output for local automation.
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Use `--output <path>` to write the rendered report to a separate file. Without `--output`, the report is printed to stdout. The tool rejects an output path that resolves to the input log file.
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## Exit Codes
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- `0` - OK, no JVM/application findings.
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- `1` - JVM/application findings detected.
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- `2` - Invalid input, unreadable file, bad argument, output write failure, or runtime error.
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## Example Text Output
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```text
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JVM Log Analyzer
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================
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Overall status: CRITICAL
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Findings require review; logs alone do not prove root cause.
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[CRITICAL] OutOfMemoryError
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Occurrences: 1
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Symptom: jvm_memory
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First seen: UNKNOWN
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Last seen: UNKNOWN
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Stack traces linked: 1
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Samples:
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- Exception in thread "main" java.lang.OutOfMemoryError: Java heap space
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Operational Summary
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-------------------
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Overall status: CRITICAL
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Total lines scanned: 33
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Total findings: 27
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Total stack traces detected: 4
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Critical finding groups: 11
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Warning finding groups: 8
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HTTP 5xx count: 3
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Parsed timestamps count: 21
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Unknown timestamps count: 12
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```
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## Markdown Workflow
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Generate a Markdown report from a collected JVM application log and attach it to the incident or application support ticket as supporting evidence:
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```bash
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python3 jvm_log_analyzer.py \
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--file examples/sample-jvm-app.log \
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--format markdown \
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--include-stacktraces \
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--output jvm-report.md
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```
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Review the report before attaching it. A `WARNING` or `CRITICAL` result should be reviewed with application health checks, JVM memory telemetry, database status, certificate state, recent deployments, and the relevant application owner.
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## Operational Limitations
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- Pattern matching is intentionally simple and predictable.
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- A single log line can match multiple findings, such as `ERROR`, `HTTP 503`, and a Java exception.
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- Case-sensitive default matching can miss lowercase variants unless `--ignore-case` is used.
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- Stack trace grouping is practical, not a complete Java parser.
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- Timestamp parsing is best-effort; unparseable lines are retained during time filtering.
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- HTTP 5xx counts are raw log counts, not request rates or customer impact.
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- Large log files are read into memory; collect scoped extracts for very large incidents.
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## Safety Notes
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- The tool only reads the input log and optionally writes a separate report.
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- It does not require elevated privileges unless the chosen log path requires them.
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- Do not include secrets, customer data, private hostnames, tokens, or unsanitized production details in portfolio examples.
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- Treat findings as prompts for operator review, not automated remediation instructions.
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