Logging
An index and topic collection covering log ingestion, log search, log aggregation, and log pipeline services. Logging platforms collect event records from applications, infrastructure, containers, network devices, and security tooling, then parse, index, route, and retain them for search, alerting, troubleshooting, audit, and analytics. This collection spans hosted SaaS log platforms (Splunk, Sumo Logic, Datadog Logs, Coralogix, Axiom, Logz.io, Better Stack Logs), open-source log stacks (Elasticsearch / OpenSearch, Loki, Graylog, OpenObserve, SigNoz), log pipeline and shipper tooling (Fluentd, Fluent Bit, Logstash, Vector, Cribl), and cloud-native log services (AWS CloudWatch Logs, Google Cloud Logging, Azure Log Analytics, OpenTelemetry Logs).
Index entry only — little beyond a description and a link, and nothing machine-readable enough for an agent to act on without a human reading the site first.
API Evangelist profiles Logging the way a machine reads it — 31 machine-readable artifacts, pulled from the provider's own public surface and indexed so a developer, an analyst, or an AI agent can evaluate it against every other provider on the network.
Every provider in the network is reduced to the same set of machine-readable artifacts — OpenAPI contracts, event specifications, GraphQL schemas, runnable collections, pricing and rate-limit signals, security posture, OAuth scopes, and the agent surfaces (MCP servers and skills) that let software drive the API on its own. We profile them because the interface is the part of a company you can actually inspect: it is a truer signal of what a provider does than any marketing page. From those artifacts we compute the Kin Score — Logging scores 8.5/100 (minimal), with a separate agent-readiness read of 0/100 (human only). The full breakdown is below, followed by every artifact we hold — each card links through to its machine-readable definition on apis.io.
Kin Score
This is the API Evangelist rating — a single, repeatable read computed from the artifacts on this page. Green fill is points earned; the red track is points possible, so every bar shows earned-versus-possible at a glance. Every facet and dimension name is a link: it opens that measurement's page on APIs.io, where the rating runs across the whole catalog — the exact checks that feed it, how every profiled provider distributes on it, and who is at the top of it.
Kin Score
How this is scored →scored 2026-10-03 · rubric v0.23.0
Put this on your own site. The badge is drawn live from Logging's current Kin Score — paste it once and it updates itself every time the score is recomputed. It follows your visitor's light or dark setting, and it links back here so anyone who sees it can read the full breakdown.
<!-- Kin Score · API Evangelist -->
<a href="https://providers.apievangelist.com/providers/logging/"
title="Logging on API Evangelist — API profile and Kin Score">
<img src="https://apis.io/badge/logging.svg"
alt="Logging Kin Score — API readiness rating by API Evangelist" width="150" height="150" loading="lazy">
</a>[](https://providers.apievangelist.com/providers/logging/)<!-- Kin Score · API Evangelist -->
<a href="https://providers.apievangelist.com/providers/logging/"
title="Logging on API Evangelist — API profile and Kin Score">
<img src="https://apis.io/badge/logging/card.svg"
alt="Logging Kin Score — API readiness rating by API Evangelist" width="340" height="120" loading="lazy">
</a>More shapes, themes and sizes → · Score as JSON · How badges work
How we profile Logging
Each block below is one kind of artifact we hold for Logging. For each we say what it is and why it earns a place in the profile, then list every one we've indexed — capped at two rows, scroll within the panel for the rest.
Features 8
The notable capabilities this provider advertises, captured as structured features so they can be searched and compared instead of read one landing page at a time.
Notable capabilities this provider offers.
Log Ingestion and Collection
Logging platforms collect log events from applications, hosts, containers, cloud services, and network devices via HTTP endpoints, syslog, agents, and shippers such as Fluent Bi...
Parsing and Enrichment
Incoming log lines are parsed into structured fields, enriched with metadata (host, service, environment, trace ID), and normalized so downstream search and analytics behave con...
Indexing and Full-Text Search
Platforms like Elasticsearch, OpenSearch, Splunk, Graylog, and OpenObserve index log content for fast keyword, field, and time-range queries against very large data sets.
Log Routing and Pipelines
Log pipeline tools like Cribl, Vector, Fluentd, Fluent Bit, and Logstash route, transform, filter, sample, and replicate log streams between sources, destinations, and storage t...
Retention, Tiering, and Archival
Logging services manage hot, warm, and cold retention policies, archive raw logs to object storage, and enforce retention windows for cost control and compliance.
Alerting and Detection on Logs
Log platforms expose alert rules, saved searches, and detection content that fire on patterns, thresholds, anomalies, or security signatures observed in log streams.
Live Tail and Troubleshooting
Engineers stream live logs, filter by service or request, and pivot from a log line into traces, metrics, and related events during incident response and debugging.
Log-Based Audit and Compliance
Immutable log capture, retention policies, and access controls support SOC 2, HIPAA, PCI, and other audit and compliance use cases driven by log evidence.
Scroll within the panel for all 8 ·
Semantic Vocabularies 1
JSON-LD contexts give the data shared meaning across APIs. We profile them because semantics are what let a machine reconcile 'customer' here with 'customer' somewhere else.
JSON-LD contexts and semantic vocabularies used across these APIs.
Logging Context
JSON-LDJSON Schema 2
Standalone JSON Schema definitions describe the data models behind the API. We profile them so the shapes are validatable on their own — useful long after a single request is forgotten.
Standalone JSON Schema definitions for this provider's data models.
JSON Structure 2
JSON Structure captures the data shapes in a form built for tooling — a complement to JSON Schema that keeps the model machine-legible.
JSON Structure definitions describing this provider's data shapes.
Logging Log Event Structure
JSON STRUCTURELogging Log Stream Structure
JSON STRUCTUREExamples 2
Real request and response payloads are what turn a spec from abstract into obvious — and they're one of the twelve things an agent needs to call an API correctly on the first try.
Example request and response payloads for these APIs.
Logging Log Event Example
EXAMPLELogging Log Stream Example
EXAMPLEUse Cases 8
What developers actually build with this provider — captured so the catalogue answers 'what is this for', not just 'what does this expose'.
What developers build with this provider.
Application Troubleshooting and Debugging
Engineers search application and request logs across services to diagnose errors, latency spikes, and failed deployments in production environments.
Centralized Log Aggregation Across Clouds
Organizations aggregate logs from AWS CloudWatch, Google Cloud Logging, Azure Log Analytics, Kubernetes clusters, and on-prem systems into a single search and analytics surface.
Security and SIEM Use Cases
Security teams ingest authentication, network, endpoint, and audit logs into platforms like Splunk, Sumo Logic, Graylog, and QRadar to drive detections, investigations, and thre...
Cost Control Through Log Pipelines
Teams use Cribl, Vector, and Fluent Bit to reduce, sample, route, and reshape log volume before it lands in expensive indexing tiers, optimizing cost per useful log.
Compliance and Audit Trail Retention
Regulated organizations retain structured logs for prescribed windows, with tamper-evident storage and access controls, to demonstrate compliance during audits.
OpenTelemetry-Native Logging
Modern stacks emit logs from applications as OpenTelemetry log records, correlate them with traces and metrics, and ship them through OTLP into back-ends like Axiom, OpenObserve...
Kubernetes and Container Log Collection
Cluster operators run Fluent Bit, Fluentd, or Vector as DaemonSets to collect container logs and forward them into Loki, Elasticsearch, OpenSearch, or hosted log services.
Business and Product Analytics on Logs
Product and platform teams query structured event logs to build dashboards, funnels, and KPIs without standing up a separate analytics pipeline.
Scroll within the panel for all 8 ·
Integrations 8
Pre-built integrations with other platforms tell you where this provider already fits in a stack.
Pre-built integrations with other platforms and tools.
Splunk
Enterprise log search, indexing, and SIEM platform widely used for IT operations and security operations on high-volume log data.
Datadog Logs
Hosted log management integrated with Datadog metrics and APM, with log-to-metric pipelines, archives, and detection rules.
Elasticsearch / OpenSearch
Open-source distributed search engines that power many log stacks, including ELK and the OpenSearch project, for indexing and querying logs at scale.
Grafana Loki
Horizontally scalable, label-based log aggregation system designed to pair with Prometheus metrics and Grafana dashboards.
OpenTelemetry Logs
Open standard for emitting and transporting log records over OTLP, with collector pipelines that fan out to many logging back-ends.
Fluent Bit and Fluentd
Lightweight and feature-rich open-source log shippers used across Kubernetes, edge, and server fleets to collect and forward logs.
Vector
High-performance open-source observability data pipeline that collects, transforms, and routes logs, metrics, and traces.
Cribl Stream
Vendor-neutral observability pipeline that reduces, shapes, routes, and replays log and event data between sources and destinations.
Scroll within the panel for all 8 ·
Resources
Every other property we hold for Logging — documentation, portals, status pages, policies, and corporate surface — grouped by the job it does, following the integrator's arc from getting started to running in production.
Get Started 1
Portal, sign-up, and the first successful call
Build 1
SDKs, sample code, and the tooling you integrate with
← All providers · Data indexed from github.com/api-evangelist/logging · machine-readable index on apis.io
This is an independent, third-party profile of Logging, published by API Evangelist. We do not operate, host, resell, or support these APIs, and we are not affiliated with or endorsed by the company unless stated above. Everything here is built from publicly available information — the company's own site, developer portal, documentation, public repositories, and the specifications it publishes for public use. Nothing is obtained by breaching a system, defeating an access control, or using credentials.
The Kin Score and Agent Readiness rating are independently calculated assessments of a company's public API artifacts, scored against a published rubric. They are not certifications, endorsements, security assessments, or audits.
Corrections, re-scores, and removal are free — no partnership or purchase required, and you do not need to justify the request. A removed company is recorded as unrated, never scored zero for having asked. Acknowledgement within one business day; removal within two.
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