Elastic Certified Observability Engineer flashcards
Elastic Certified Observability Engineer · Build recall with a focused review session.
32 cards. Read the term and the definition here. The deck at the top of this page is optional.
- Data stream naming
- Data streams follow .ds-<type>-<dataset>-<date>-<generation> for backing indices. The stream name itself is <type>-<dataset>-<namespace>, and writes always go to the newest backing index.
- Component template purpose
- A component template stores reusable settings, mappings, or aliases. One or more component templates are referenced by a composable index template, which is then matched to indices by index_patterns.
- Ingest pipeline on_failure
- An on_failure processor list runs when a processor throws an error. It can set a field, remove the document, or route it elsewhere, preventing the whole bulk request from failing.
- Standalone versus Fleet Agent
- A Fleet-managed Agent receives policy from Fleet Server and appears in the Fleet UI. A standalone Agent reads a local elastic-agent.yml, is upgraded manually, and is invisible to Fleet.
- ILM versus SLM
- Index lifecycle management moves indices between data tiers and deletes them. Snapshot lifecycle management creates and expires repository snapshots on a schedule. They are separate policies serving different purposes.
- Data tier allocation setting
- index.routing.allocation.include._tier_preference selects a data tier such as data_hot or data_warm. Elasticsearch allocates shards to nodes with the matching data role, falling back to the next tier in the list.
- ECS log fields
- Elastic Common Schema standardizes field names across sources: event.dataset identifies the source, log.level the severity, host.name the origin, and message the raw text.
- Log rate indicator
- The Logs UI rate chart counts documents per time interval and compares the selected range with the preceding equivalent range, so a spike is a change in document volume, not severity.
- Log categorization field
- Categorization groups similar messages into patterns using machine learning. The assigned pattern is stored in ml.category, enabling aggregation and filtering by message shape instead of exact text.
- Grok versus dissect
- Dissect splits fixed-delimiter strings and is faster. Grok applies regular-expression patterns and handles variable formats. Use dissect when the log layout is stable, grok otherwise.
- Multiline log handling
- Stack traces span multiple lines and must be joined before indexing. Elastic Agent integrations accept multiline settings, and Logstash provides a multiline codec, so each event maps to one document.
- Date processor requirement
- The date processor parses a source field using listed formats and writes the result to a target field. Set the target to @timestamp, otherwise Elasticsearch assigns ingest time and ordering breaks.
- Cross-cluster search syntax
- Query a remote cluster by prefixing the index pattern with the cluster alias, as in remote1:logs-*. The remote cluster must be registered in the local cluster settings before queries resolve.
- Logs anomaly detection partitioning
- Anomaly detection jobs on logs often use partition_field_name set to host.name or event.dataset, creating a separate model per entity so each host's normal rate is learned independently.
- TSDB index mode
- Time series data streams set index.mode to time_series and declare routing_path dimensions. They downsample older data and use synthetic _source, so stored fields are reconstructed rather than returned verbatim.
- Agent policy composition
- A Fleet agent policy references one or more integrations. Each integration contributes inputs and datasets, and the namespace determines the suffix of the resulting data stream name.
- Enrollment token versus service token
- Enrollment tokens let Agents enroll into a policy and can expire. Service tokens authenticate Fleet Server and other components to Elasticsearch and are not used for agent enrollment.
- System integration metricsets
- The system integration collects cpu, memory, diskio, filesystem, load, network, process, and process_summary metricsets. Documents carry host.name and host.ip to identify the source host.
- Agent status values
- Fleet reports Healthy, Unhealthy, Offline, Updating, and Unenrolled. An agent stuck in Updating after a policy change usually cannot reach Fleet Server over the network.
- Metric alert rule anatomy
- An Infrastructure threshold rule queries metrics-* with a KQL filter, applies an aggregation such as average over a lookback window, and fires when the value crosses the threshold.
- Monitoring index names
- Stack monitoring stores Elasticsearch metrics in .monitoring-es-*, Logstash metrics in .monitoring-logstash-*, and Kibana metrics in .monitoring-kibana-*, collected by Metricbeat or internal collectors.
- Metricbeat module activation
- Metricbeat modules are enabled in modules.d or via elastic-agent integration inputs. Each module defines metricsets, periods, and hosts, and writes to a dataset-specific data stream.
- Trace and transaction relationship
- A trace groups all transactions sharing trace.id. Each transaction has its own span.id and duration, and child spans reference it through parent.id, forming the trace tree.
- APM Server data path
- APM agents send events to APM Server, which validates and writes them to traces-apm-* data streams. APM Server runs as the apm integration in Fleet or as a standalone binary.
- Service map dependencies
- Service map edges come from span.destination.service.resource together with span.subtype and span.type. Missing destination fields mean downstream dependencies do not appear on the map.
- Transaction sample rate
- transaction_sample_rate sets the fraction of transactions sampled. Sampled traces retain all spans, while unsampled transactions store only summary metrics, reducing storage and agent overhead.
- Span self time
- span.self_time is the time spent in a span excluding child spans. Breakdown metrics aggregate self time by span type such as db, http, or app to show where latency originates.
- RUM transaction types
- The Elastic APM JavaScript agent reports Real User Monitoring data. Page loads produce transaction.type page-load, and interactions produce user-interaction, both tied to the browser session.
- Synthetics monitor types
- Browser monitors run Playwright scripts in a real browser. Lightweight monitors check HTTP, TCP, or ICMP endpoints without a browser, suiting availability checks where rendering is irrelevant.
- SLO budgeting methods
- An SLO defines a target such as 99.9% over a window. The occurrences method counts good versus total events, while timeslices divides the window into intervals and counts good intervals.
- Uptime TLS certificate fields
- Uptime monitors record TLS certificate expiry in fields under tls. Alerts on certificate expiration compare those fields against a threshold, warning before the certificate actually lapses.
- APM agent central configuration
- Fleet or Kibana can push settings such as transaction_sample_rate to APM agents through APM Server central configuration, so agents need not be restarted or reconfigured locally.