Inzichten en analyse van logs

Monitoring en troubleshooting van AWS

John Q. Martin

Principal Consultant

Logs Insights-querystructuur

Logs Insights-querystructuur met de velden filter, stats, sort en limit met pipe-gekoppelde commando's

Querytalen: dezelfde query, drie manieren

CloudWatch Logs Insights QL

fields @timestamp, @message, level
| filter level = "ERROR"
| filter @timestamp > ago(1h)
| sort @timestamp desc
| limit 20

OpenSearch PPL

source = `/aws/lambda/my-function`
| where level = 'ERROR' and @timestamp > ago(1h)
| fields @timestamp, @message, level
| sort - @timestamp
| head 20

Querytalen: OpenSearch SQL

OpenSearch SQL

SELECT `@timestamp`, `@message`, level
FROM `/aws/lambda/my-function`
WHERE level = 'ERROR'
  AND `@timestamp` > ago(1h)
ORDER BY `@timestamp` DESC
LIMIT 20

Standaard SELECT / FROM / WHERE-syntaxis
Voegt JOINs toe over loggroepen
Kies wat bij je team past

Scenario 1: Foutpieken vinden

fields @timestamp, @message, level
| filter level = "ERROR"
| stats count() as error_count by bin(5m)
| sort @timestamp desc

Uitgebreid: groepeer op fouttype

fields @timestamp, error_type, error_message
| filter level = "ERROR"
| stats count() as count by error_type, bin(5m)
| sort count desc

Scenario 2: Trage API-eindpunten

fields @timestamp, endpoint, response_time, status_code
| filter response_time > 1000
| stats avg(response_time) as avg_time,
        max(response_time) as max_time,
        count() as slow_requests
        by endpoint
| sort avg_time desc

Inzoomen

fields @timestamp, endpoint, response_time, user_id, request_id
| filter endpoint = "/api/users" and response_time > 1000
| sort response_time desc
| limit 20

Scenario 3: Mislukte authenticatie

fields @timestamp, user_id, ip_address, action
| filter action = "login_failed"
| stats count() as failed_attempts by user_id, ip_address
| sort failed_attempts desc
| limit 50

Tijdgebaseerde analyse

fields @timestamp, user_id, ip_address
| filter action = "login_failed"
| stats count() as attempts by ip_address, bin(1h)
| filter attempts > 10
| sort attempts desc

Scenarios 4 & 5: Database-timeouts en geheugenlekken

Database-timeouts

fields @timestamp, @message
| filter @message like /database/ and @message like /timeout|error|failed/
| parse @message "timeout after * seconds" as timeout_duration
| stats count() as timeout_count,
        avg(timeout_duration) as avg_timeout
        by bin(5m)

Geheugenlekken opsporen

fields @timestamp, memory_used_mb, heap_size_mb
| stats avg(memory_used_mb) as avg_memory,
        max(memory_used_mb) as max_memory
        by bin(1h)
| sort @timestamp asc

Scenario 6: Request-tracing

fields @timestamp, @message, request_id, service, action
| filter request_id = "abc123def456"
| sort @timestamp asc

Trace over meerdere services

fields @timestamp, service, action, duration_ms, status
| filter request_id = "abc123def456"
| sort @timestamp asc
| display @timestamp, service, action, duration_ms, status

Geavanceerd: parse en Regex

Ongeformatteerde logs parsen

fields @timestamp, @message
| parse @message "[*] User * failed to access resource * from IP *"
    as level, user, resource, ip

Regex-parsing

| parse @message /Request completed in (?<duration>\d+)ms with status (?<status>\d+)/

Geavanceerd: berekende velden

fields @timestamp, requests, errors
| fields error_rate = (errors / requests) * 100

fields @timestamp, status_code
| fields status_category =
    case(status_code < 300, "success",
         status_code < 500, "client_error",
         status_code >= 500, "server_error")
| stats count() as request_count by status_category

Query-optimalisatie

Vier regels voor queryoptimalisatie: stel een tijdsfilter in vóór aggregatie, beperk resultaten en geef de voorkeur aan aggregaties

Anomaliedetectie en correlatie

Statistische anomaliedetectie

Bepaal baseline: gemiddelde en stddev over 7 dagen
Vergelijk huidige periode met de baseline
Markeer waarden > 2 standaarddeviaties als afwijkend

Correlatie van foutpercentages

fields @timestamp, level
| stats count() as total_requests,
        sum(case(level = "ERROR", 1, 0)) as errors
        by bin(5m)
| fields error_rate = (errors / total_requests) * 100

Samenvatting

CloudWatch Logs Insights: interactieve queryservice, geen infrastructuur nodig
Drie querytalen: Logs Insights QL, OpenSearch PPL, OpenSearch SQL
Zes troubleshootingscenario's: foutpieken, trage eindpunten, mislukte auth, DB-timeouts, geheugenlekken, request-tracing
Geavanceerd: parse voor ongestructureerde tekst, bin() voor tijdreeksen, pct() voor percentielen
Correlatie en anomaliedetectie: analyse van foutpercentages, statistische baselinevergelijking
Van onderzoek naar automatisering: metriekfilters en alarmen sluiten de lus

Laten we oefenen!