a464e550c9
Full-stack implementation of the Cyberyan full-stack trial task. Backend (Django 5 / DRF) - Normalised PostgreSQL model (Profile, Company, School, Skill, Experience, Education) as the source of truth, with GIN + trigram indexes. - Self-healing CSV reader: the supplied export carries an injected watermark column, missing columns, rows split by broken quoting and a duplicated header. A signature-scored Needleman-Wunsch alignment reconstructs 284 clean records out of 336 physical rows; only 10 rows parse correctly without it. - Pluggable search layer (Strategy): Elasticsearch by default, PostgreSQL full-text search as a fallback selected by a single environment variable. - Keyword search with per-field boosts, fuzziness and phrase boosting, six faceted filters (OR within a filter, AND across filters), an experience range, four sort orders, highlighting and facet aggregations. - JWT auth with rotation + blacklist, three roles, PII masking, scoped rate limits, a single error envelope, OpenAPI schema and health probes. Frontend (React 18 / TypeScript / Vite) - Debounced search with type-ahead, faceted filter panel, result cards, profile drawer, URL-synced search state, automatic token refresh. - Highlight snippets rendered without dangerouslySetInnerHTML. Infrastructure - Hardened multi-stage images (non-root, read-only rootfs, healthchecks). - docker-compose for the full stack plus dev and production overlays. - ELK: structured JSON logs shipped asynchronously to Logstash, routed per event type, with a composable index template and a Kibana setup script. Quality - 61 backend tests (85% coverage), ruff/black/bandit/mypy, ESLint + tsc, GitHub Actions running lint, tests and both image builds. - Persian documentation: README plus architecture, search, API, data, security and operations guides. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01GnFo6fNaHCTAkJbfcdkqtG
86 lines
3.0 KiB
Plaintext
86 lines
3.0 KiB
Plaintext
# =============================================================================
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# Application log pipeline.
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#
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# Django emits one JSON object per log record and ships it over TCP with
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# `python-logstash-async` (asynchronous, buffered - a Logstash outage never
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# blocks a request thread). Because the payload is already structured there is
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# no grok parsing here: the pipeline only enriches, classifies and routes.
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# =============================================================================
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input {
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tcp {
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port => 5959
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codec => json_lines
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tags => ["django"]
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}
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}
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filter {
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# Fields Logstash adds itself and that carry no information for us.
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mutate {
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remove_field => ["port", "@version"]
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}
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# The application already stamps an ISO-8601 timestamp; trust it so the log
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# line is filed under the moment it happened, not the moment it arrived.
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date {
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match => ["@timestamp", "ISO8601"]
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target => "@timestamp"
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tag_on_failure => ["_timestamp_parse_failure"]
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}
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# Route by event type. `event` is set by the application through `extra=`.
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if [event] == "search_executed" {
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mutate { add_field => { "[@metadata][stream]" => "search" } }
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# A slow search is worth alerting on; pre-computing the flag keeps the
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# Kibana query simple.
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if [took_ms] and [took_ms] > 500 {
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mutate { add_tag => ["slow_search"] }
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}
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if [result_count] == 0 {
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mutate { add_tag => ["zero_results"] }
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}
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} else if [event] in ["login_succeeded", "login_failed", "logout", "user_registered"] {
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mutate { add_field => { "[@metadata][stream]" => "audit" } }
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} else if [level] in ["ERROR", "CRITICAL"] {
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mutate { add_field => { "[@metadata][stream]" => "error" } }
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} else {
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mutate { add_field => { "[@metadata][stream]" => "app" } }
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}
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# Never let a stray contact detail reach the log store.
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mutate {
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remove_field => ["password", "authorization", "emails", "phone_numbers"]
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}
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}
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output {
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elasticsearch {
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# Credentials, when the cluster has security enabled, travel inside the
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# URL (see docker-compose.prod.yml) so this single pipeline file works
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# both with and without authentication.
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hosts => ["${ELASTICSEARCH_HOSTS:http://elasticsearch:9200}"]
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# One index per stream per day keeps retention policies simple and makes
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# "delete everything older than 30 days" a single index deletion.
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index => "app-logs-%{[@metadata][stream]}-%{+YYYY.MM.dd}"
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# Composable index template (Elasticsearch 8 style): pins the types of the
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# fields Kibana filters and aggregates on instead of letting dynamic
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# mapping guess them.
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manage_template => true
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template_api => "composable"
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template_name => "app-logs"
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template => "/usr/share/logstash/templates/app-logs.json"
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template_overwrite => true
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action => "index"
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}
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# Anything that fails to parse is still visible in `docker compose logs`.
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if "_jsonparsefailure" in [tags] or "_timestamp_parse_failure" in [tags] {
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stdout { codec => rubydebug }
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}
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}
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