WebLogic logs use a distinct timestamp format that makes temporal filtering challenging. A typical entry looks like:

####  
Here comes the actual log message content

We need three key elements for robust log monitoring:

1. Timestamp extraction and comparison
2. Continuous monitoring with retry logic
3. Pattern matching for the target string

Here's a production-ready script combining all requirements:

#!/bin/bash

TARGET_STRING="ERROR_WE_CARE_ABOUT"
LOG_FILE="/path/to/weblogic.log"
MAX_ATTEMPTS=10
ATTEMPT=0
FOUND=false

while [ $ATTEMPT -lt $MAX_ATTEMPTS ] && [ "$FOUND" = false ]; do
    NOW=$(date +%s)
    TEN_MIN_AGO=$((NOW - 600))
    
    # Process log entries from last 10 minutes
    while IFS= read -r line; do
        if [[ "$line" =~ ^####\<([^>]+)\> ]]; then
            log_date=$(date -d "${BASH_REMATCH[1]}" +%s 2>/dev/null)
            if [ -n "$log_date" ] && [ $log_date -ge $TEN_MIN_AGO ]; then
                current_entry="$line"
                continue
            fi
        fi
        
        if [ -n "$current_entry" ] && [[ "$line" == *"$TARGET_STRING"* ]]; then
            echo "Found matching entry:"
            echo "$current_entry"
            echo "$line"
            FOUND=true
            break
        fi
    done < "$LOG_FILE"
    
    if [ "$FOUND" = false ]; then
        echo "Pattern not found, retrying in 60 seconds..."
        sleep 60
        ((ATTEMPT++))
    fi
done

if [ "$FOUND" = false ]; then
    echo "Error: Target string not found after $MAX_ATTEMPTS attempts"
    exit 1
fi

For high-volume logs, consider these optimized approaches:

# Using awk for better performance
awk -v target="$TARGET_STRING" -v threshold=$(date -d '10 minutes ago' +%s) '
BEGIN { found=0 }
/^####]/)
    "date -d \"" parts[2] "\" +%s" | getline timestamp
    if (timestamp >= threshold) valid=1
    else valid=0
    next
}
valid && $0 ~ target { print; found=1; exit }
END { exit !found }
' "$LOG_FILE"

When dealing with EDT/EST timestamps, add conversion:

# Convert log timestamp to UTC for consistent comparison
LOG_TIME="Sep 21, 2018 1:56:20 PM EDT"
UTC_SECONDS=$(TZ=UTC date -d "$(echo "$LOG_TIME" | sed 's/EDT/EST5EDT/')" +%s)

• Add log rotation checks using ls -l or inode comparison
• Implement signal trapping for clean script termination
• Consider using tail -n with large number as initial optimization
• Add monitoring for script execution timeouts

WebLogic logs with their ####<timestamp> prefix format pose a particular challenge when you need to:

• Filter only recent entries (e.g., last 10 minutes)
• Search for specific patterns within that timeframe
• Implement retry logic when matches aren't found

Here's a robust approach combining date calculations and text processing:

#!/bin/bash

# Configuration
LOG_FILE="/path/to/weblogic.log"
SEARCH_STRING="ERROR"
RETRY_INTERVAL=60
MAX_RETRIES=5

# Calculate timestamp 10 minutes ago in WebLogic format
TEN_MIN_AGO=$(date -d "10 minutes ago" "+%b %d, %Y %-I:%M:%S %p %Z")

# Retry loop
for ((retry=1; retry<=MAX_RETRIES; retry++)); do
    # Extract and search recent entries
    awk -v search="$SEARCH_STRING" -v threshold="$TEN_MIN_AGO" '
    BEGIN {
        # Convert threshold to sortable timestamp
        cmd = "date -d \"" threshold "\" +%s"
        cmd | getline threshold_ts
        close(cmd)
    }
    /^####</ {
        # Extract timestamp part
        ts_str = substr($0, 6, index($0, ">")-6)
        # Convert to sortable timestamp
        cmd = "date -d \"" ts_str "\" +%s 2>/dev/null"
        cmd | getline ts
        close(cmd)
        current_entry_ts = ts
        valid_entry = (ts >= threshold_ts)
    }
    valid_entry && $0 ~ search {
        print
        found=1
    }
    END { exit !found }
    ' "$LOG_FILE"
    
    # Check if search was successful
    if [ $? -eq 0 ]; then
        exit 0
    fi
    
    # Wait before retrying
    if [ $retry -lt $MAX_RETRIES ]; then
        sleep $RETRY_INTERVAL
    fi
done

exit 1

This solution improves upon simpler approaches by:

1. Properly handling WebLogic's timestamp format
2. Using date commands for accurate time comparisons
3. Implementing configurable retry logic
4. Being efficient with large log files

For frequently updated logs, consider tailing the log and applying time filters:

tail -n 10000 "$LOG_FILE" | awk -v search="$SEARCH_STRING" -v threshold="$TEN_MIN_AGO" '
# Same AWK logic as above
'

When dealing with massive log files:

• First use grep to find potential matches, then apply time filtering
• Consider using tac (reverse cat) to process from the end backward
• For production systems, log rotation policies should be implemented