Logit.io
Platform

Distributed Tracing

Unlock the Full Potential of Your Applications & Services with Distributed Tracing from Logit.io.

apm · opentelemetry
OTLPJaegerservice mapspan search
api
checkout
payments
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Trace · checkout.completep95 84ms
gateway
42ms
checkout
28ms
payments
19ms
inventory
14ms
notify
9ms
+ 1.02M spans this month
! 1 slow payment span
+ service map healthy

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Experience the benefits of end-to-end tracing, including collecting and examining timing and code-level context for all distributed traces, across the entire stack, with Logit.io's platform for distributed tracing. Centralizing and ingesting traces via Logit.io allows users to pinpoint performance bottlenecks and events within distributed architectures. Our platform allows for the effortless management of trace ingestion, retention, and costs associated with the data you ingest.

Amplify your incident resolution speed, monitor performance trends, and enjoy real-time analysis, monitoring, and reporting of insightful data and custom metrics. Our all-in-one observability platform presents throughput, availability, reliability, and error rates, supplying detailed insights for effective technical decision-making.

What Is Distributed Tracing?

Distributed tracing is a process used to follow and visualize the flow of requests as they traverse across multiple services and components within a distributed application or system. The main objective is to supply a detailed understanding of the interactions and dependencies between different parts of the system.

OTLPJaegerservice mapspan search
api
checkout
payments
inventory
notify
Trace · checkout.completep95 84ms
gateway
42ms
checkout
28ms
payments
19ms
inventory
14ms
notify
9ms
+ 1.02M spans this month
! 1 slow payment span
+ service map healthy

Distributed Tracing With Logit.io

Logit.io's distributed tracing tool plays a pivotal role in aiding developers and system operators in finding and rectifying issues within complex, distributed systems. An example of this is through end-to-end visibility. Distributed tracing provides end-to-end visibility into the whole lifecycle of a request as it moves through various services. This visibility enables you to view the sequence of operations, comprehend the flow of requests, and pinpoint the exact location of performance bottlenecks or errors. Another example is latency analysis. By inspecting the duration of a specific span within a trace, you can find components or services that contribute to latency. This is especially valuable for comprehending where delays happen and optimizing the performance of critical paths in your system.

Finally, Logit.io's observability platform incorporates OpenTelemetry, making end-to-end observability easier than ever. This solution supplies unified analysis and comprehensive centralization for numerous types of telemetry data. As a result, Logit.io for OpenTelemetry provides a compliant, secure, and production-ready distribution of the OpenTelemetry project.

stream
--:--:-- INFO request.completed duration_ms=42 route="/api/v1/orders"
--:--:-- WARN latency.spike service=checkout p95=820ms threshold=500ms
--:--:-- INFO trace.exported spans=128 backend=jaeger status="ok"
--:--:-- INFO metric.scrape target=prometheus job=k8s-pods samples=8421
--:--:-- INFO log.shipped bytes=184032 index=logs-prod
--:--:-- WARN auth.failure ip=203.0.113.42 attempts=3 action=rate_limit
--:--:-- INFO alert.routed severity=high channel="#incidents" dedupe=on
--:--:-- INFO dashboard.refresh uid=ops-overview panels=14 cache=hit
--:--:-- ERROR disk.pressure node=worker-3 usage=92% reclaim=started
--:--:-- INFO pipeline.batch size=2048 lag_ms=18 status=healthy
--:--:-- WARN queue.backpressure topic=ingest depth=1200
--:--:-- INFO otel.export endpoint=collector.svc spans_ok=512
--:--:-- INFO search.query hits=1284 took_ms=37 index=logs-*
--:--:-- INFO retention.policy applied hot=14d warm=30d
--:--:-- WARN tls.cert.expiring host=ingest.logit.io days=12
--:--:-- INFO ha.failover check region=eu-west status=ready
--:--:-- INFO request.completed duration_ms=42 route="/api/v1/orders"
--:--:-- WARN latency.spike service=checkout p95=820ms threshold=500ms
--:--:-- INFO trace.exported spans=128 backend=jaeger status="ok"
--:--:-- INFO metric.scrape target=prometheus job=k8s-pods samples=8421
--:--:-- INFO log.shipped bytes=184032 index=logs-prod
--:--:-- WARN auth.failure ip=203.0.113.42 attempts=3 action=rate_limit
--:--:-- INFO alert.routed severity=high channel="#incidents" dedupe=on
--:--:-- INFO dashboard.refresh uid=ops-overview panels=14 cache=hit
--:--:-- ERROR disk.pressure node=worker-3 usage=92% reclaim=started
--:--:-- INFO pipeline.batch size=2048 lag_ms=18 status=healthy
--:--:-- WARN queue.backpressure topic=ingest depth=1200
--:--:-- INFO otel.export endpoint=collector.svc spans_ok=512
--:--:-- INFO search.query hits=1284 took_ms=37 index=logs-*
--:--:-- INFO retention.policy applied hot=14d warm=30d
--:--:-- WARN tls.cert.expiring host=ingest.logit.io days=12
--:--:-- INFO ha.failover check region=eu-west status=ready

Pinpoint issues with ease

A trace unfolds a comprehensive narrative of a request or transaction, while metrics offer a broad overview of whether the system is functioning as expected, without delving into the underlying reasons. On the other hand, logs provide detailed information about events, including timestamps and event sequencing.

Choosing traces over logs is often considered more advanced, as it enables you to work with additional context surrounding your events. Trace data can be filtered and visualized based on application, subsystem, service, and action. With Logit.io, you can analyze tracing data grouped by service, allowing you to precisely pinpoint the origin of a problem by filtering for traces that exceed a specified latency.

OTLPJaegerservice mapspan search
api
checkout
payments
inventory
notify
Trace · checkout.completep95 84ms
gateway
42ms
checkout
28ms
payments
19ms
inventory
14ms
notify
9ms
+ 1.02M spans this month
! 1 slow payment span
+ service map healthy

Data flow and dependency visualisations

In the realm of ongoing application changes, swift deployments, and evolving user behavior, production issues are inevitable. Logit.io stands ready to assist in resolving these challenges. Irrespective of your role, even if you possess limited knowledge about the application, Logit.io can provide valuable insights into the factors behind performance issues.

metrics
latency
throughput
errors
p95 latency 84ms · ingest 12.4k/s · error rate 0.08%

Logit.io For OpenTelemetry

Combining OpenTelemetry (OTel) with Logit.io streamlines the achievement of end-to-end observability. OpenTelemetry empowers engineers to standardize data from any source efficiently. Logit.io for OpenTelemetry, as a secure, compliant, and production-ready distribution of the OpenTelemetry project, facilitates unified analysis and centralized management of diverse telemetry data. As major observability vendors are obligated to support the OpenTelemetry protocol, opting for an analysis service that is already OpenTelemetry-compliant becomes a crucial step in future-proofing your operations.

Find out more about OTel
OTLPJaegerservice mapspan search
api
checkout
payments
inventory
notify
Trace · checkout.completep95 84ms
gateway
42ms
checkout
28ms
payments
19ms
inventory
14ms
notify
9ms
+ 1.02M spans this month
! 1 slow payment span
+ service map healthy

Companies Feel The Difference When They Use Logit.io

Internally, Logit.io has made it easier for us to provide better support for our customers, since finding individual messages based on various data in the payload has become easier.

At Youredi, pretty much everyone from our technical support teams through to our professional services teams uses Logit.io.

Youredi

Mats von Weissenberg

CTO @ Youredi

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