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What is Zipkin?

It assists in gathering timing details that are crucial for identifying latency problems in service architectures. Its capabilities include both the collection and retrieval of this vital information. With a trace ID from a log, you can seamlessly access the related data. In cases where a trace ID is unavailable, queries can be conducted using multiple parameters such as service names, operation titles, tags, and duration. Furthermore, important data is presented in a summarized format, showcasing the time allocation for each service as well as the success or failure rates of operations. The Zipkin user interface is equipped with a dependency diagram that visualizes the number of traced requests handled by each application, making it easier to spot general trends, including error patterns and interactions with legacy services. This visualization aids in pinpointing specific issues within the system. Ultimately, this tool not only streamlines the troubleshooting process but also deepens the understanding of service interactions in intricate architectures. The insights gained can lead to more informed decision-making and improvements in service performance over time.

What is Dash0?

Engineering teams that adopt OpenTelemetry often hit the same wall: instrumentation is standardized, but the backend receiving it is not. Dash0 was built to close that gap. Every signal, whether a trace, a log record, a metric, or the resource emitting it, is stored against OpenTelemetry semantic conventions and correlated automatically. A request that ran long can be examined next to the log lines it produced and the pod it ran on, with no manual joins and no hopping between products. Ingestion happens through a standard OTLP endpoint. Nothing proprietary gets deployed, and existing instrumentation keeps working untouched. Because the wire format is open, data can be redirected to a different destination later without changes to application code. Prometheus users are treated as first-class. Full PromQL is supported, existing recording and alerting rules carry over, and Grafana dashboard definitions import directly. Cluster-level collection is handled by a dedicated Kubernetes operator covering workloads, nodes, and control plane components. Visualization runs on Perses, with dashboard, check, and alert definitions expressed declaratively and kept under version control. Investigations start broad and get narrow: heatmaps expose the shape of a latency distribution, then filters on high-cardinality attributes isolate the affected requests. Machine learning is applied to telemetry during processing rather than surfaced as a chatbot. Log AI assigns severity to records that arrive without it, discovers recurring patterns, and clusters similar entries, turning noisy third-party output into something queryable. For failing requests, the SIFT methodology structures the path from symptom to root cause. Consumption stays transparent throughout. Teams can identify which services, attributes, and log volumes are responsible for their bill and reduce them at the source, before the invoice arrives.

Media

Media

Integrations Supported

GitHub
ActiveMQ

Integrations Supported

GitHub
Akamai
Altinity
Claude
ClickHouse
Confluent
Fluentd
Google Chat
Google Cloud Platform
Grafana Cloud
Istio
Kubernetes
Linkerd
Logstash
Node.js
Slack
Stripe
Vercel
incident.io

API Availability

API Availability

Has API

Pricing Information

Pricing not provided

Pricing Information

$0.00 per month
Completely transparent usage based pricing
Free Trial Offered?

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Zipkin

Company Website

zipkin.io

Company Facts

Organization Name

Dash0

Date Founded

2023

Company Location

United States

Company Website

www.dash0.com

Categories and Features

Categories and Features

AI Observability

Not specified

AI SRE Agents

Not specified

Cloud Monitoring

Not specified

Container Monitoring

Not specified

Database Monitoring

Not specified

IT Alerting

Not specified

Log Analysis

Not specified

Log Management

Not specified

Observability

Not specified

Telemetry

Not specified

Website Monitoring

Not specified

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