Alternatives to Zipkin logo

Alternatives to Zipkin

Jaeger, OpenTracing, New Relic, AppDynamics, and Prometheus are the most popular alternatives and competitors to Zipkin.
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What is Zipkin and what are its top alternatives?

It helps gather timing data needed to troubleshoot latency problems in service architectures. Features include both the collection and lookup of this data.
Zipkin is a tool in the Monitoring Tools category of a tech stack.
Zipkin is an open source tool with 14.9K GitHub stars and 2.8K GitHub forks. Here’s a link to Zipkin's open source repository on GitHub

Top Alternatives to Zipkin

  • Jaeger

    Jaeger

    Jaeger, a Distributed Tracing System

  • OpenTracing

    OpenTracing

    Consistent, expressive, vendor-neutral APIs for distributed tracing and context propagation. ...

  • New Relic

    New Relic

    The world’s best software and DevOps teams rely on New Relic to move faster, make better decisions and create best-in-class digital experiences. If you run software, you need to run New Relic. More than 50% of the Fortune 100 do too. ...

  • AppDynamics

    AppDynamics

    AppDynamics develops application performance management (APM) solutions that deliver problem resolution for highly distributed applications through transaction flow monitoring and deep diagnostics. ...

  • Prometheus

    Prometheus

    Prometheus is a systems and service monitoring system. It collects metrics from configured targets at given intervals, evaluates rule expressions, displays the results, and can trigger alerts if some condition is observed to be true. ...

  • Splunk

    Splunk

    It provides the leading platform for Operational Intelligence. Customers use it to search, monitor, analyze and visualize machine data. ...

  • Datadog

    Datadog

    Datadog is the leading service for cloud-scale monitoring. It is used by IT, operations, and development teams who build and operate applications that run on dynamic or hybrid cloud infrastructure. Start monitoring in minutes with Datadog! ...

  • AWS X-Ray

    AWS X-Ray

    It helps developers analyze and debug production, distributed applications, such as those built using a microservices architecture. With this, you can understand how your application and its underlying services are performing to identify and troubleshoot the root cause of performance issues and errors. It provides an end-to-end view of requests as they travel through your application, and shows a map of your application’s underlying components. ...

Zipkin alternatives & related posts

Jaeger logo

Jaeger

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Distributed tracing system released as open source by Uber
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PROS OF JAEGER
  • 3
    Open Source
  • 2
    Easy to install
  • 2
    CNCF Project
  • 1
    Feature Rich UI
CONS OF JAEGER
    Be the first to leave a con

    related Jaeger posts

    OpenTracing logo

    OpenTracing

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    0
    Consistent, expressive, vendor-neutral APIs for distributed tracing and context propagation.
    84
    87
    + 1
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    PROS OF OPENTRACING
      Be the first to leave a pro
      CONS OF OPENTRACING
        Be the first to leave a con

        related OpenTracing posts

        New Relic logo

        New Relic

        18.5K
        6.7K
        1.9K
        New Relic is the industry’s largest and most comprehensive cloud-based observability platform.
        18.5K
        6.7K
        + 1
        1.9K
        PROS OF NEW RELIC
        • 414
          Easy setup
        • 344
          Really powerful
        • 244
          Awesome visualization
        • 194
          Ease of use
        • 151
          Great ui
        • 107
          Free tier
        • 81
          Great tool for insights
        • 66
          Heroku Integration
        • 55
          Market leader
        • 49
          Peace of mind
        • 21
          Push notifications
        • 20
          Email notifications
        • 17
          Heroku Add-on
        • 16
          Error Detection and Alerting
        • 12
          Multiple language support
        • 11
          SQL Analysis
        • 11
          Server Resources Monitoring
        • 9
          Transaction Tracing
        • 8
          Apdex Scores
        • 8
          Azure Add-on
        • 7
          Analysis of CPU, Disk, Memory, and Network
        • 6
          Detailed reports
        • 6
          Performance of External Services
        • 6
          Error Analysis
        • 6
          Application Availability Monitoring and Alerting
        • 6
          Application Response Times
        • 5
          JVM Performance Analyzer (Java)
        • 5
          Most Time Consuming Transactions
        • 4
          Top Database Operations
        • 4
          Easy to use
        • 4
          Browser Transaction Tracing
        • 3
          Application Map
        • 3
          Pagoda Box integration
        • 3
          Custom Dashboards
        • 3
          Weekly Performance Email
        • 2
          Easy visibility
        • 2
          App Speed Index
        • 2
          Easy to setup
        • 1
          Real User Monitoring Analysis and Breakdown
        • 1
          Incident Detection and Alerting
        • 1
          Real User Monitoring Overview
        • 1
          Worst Transactions by User Dissatisfaction
        • 1
          Metric Data Resolution
        • 1
          Metric Data Retention
        • 1
          Team Collaboration Tools
        • 1
          Super Expensive
        • 1
          Time Comparisons
        • 1
          Access to Performance Data API
        • 1
          Background Jobs Transaction Analysis
        • 1
          Free
        • 1
          Best of the best, what more can you ask for
        • 1
          Best monitoring on the market
        • 1
          Rails integration
        • 0
          Exceptions
        • 0
          Ddd
        CONS OF NEW RELIC
        • 19
          Pricing model doesn't suit microservices
        • 10
          UI isn't great
        • 7
          Visualizations aren't very helpful
        • 7
          Expensive
        • 5
          Hard to understand why things in your app are breaking

        related New Relic posts

        Farzeem Diamond Jiwani
        Software Engineer at IVP · | 5 upvotes · 652.3K views

        Hey there! We are looking at Datadog, Dynatrace, AppDynamics, and New Relic as options for our web application monitoring.

        Current Environment: .NET Core Web app hosted on Microsoft IIS

        Future Environment: Web app will be hosted on Microsoft Azure

        Tech Stacks: IIS, RabbitMQ, Redis, Microsoft SQL Server

        Requirement: Infra Monitoring, APM, Real - User Monitoring (User activity monitoring i.e., time spent on a page, most active page, etc.), Service Tracing, Root Cause Analysis, and Centralized Log Management.

        Please advise on the above. Thanks!

        See more
        Sebastian Gębski

        Regarding Continuous Integration - we've started with something very easy to set up - CircleCI , but with time we're adding more & more complex pipelines - we use Jenkins to configure & run those. It's much more effort, but at some point we had to pay for the flexibility we expected. Our source code version control is Git (which probably doesn't require a rationale these days) and we keep repos in GitHub - since the very beginning & we never considered moving out. Our primary monitoring these days is in New Relic (Ruby & SPA apps) and AppSignal (Elixir apps) - we're considering unifying it in New Relic , but this will require some improvements in Elixir app observability. For error reporting we use Sentry (a very popular choice in this class) & we collect our distributed logs using Logentries (to avoid semi-manual handling here).

        See more
        AppDynamics logo

        AppDynamics

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        Application management for the cloud generation
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        PROS OF APPDYNAMICS
        • 18
          Deep code visibility
        • 11
          Powerful
        • 7
          Great visualization
        • 7
          Real-Time Visibility
        • 6
          Easy Setup
        • 5
          Comprehensive Coverage of Programming Languages
        • 3
          Deep DB Troubleshooting
        • 2
          Excellent Customer Support
        CONS OF APPDYNAMICS
        • 5
          Expensive
        • 2
          Poor to non-existent integration with aws services

        related AppDynamics posts

        Farzeem Diamond Jiwani
        Software Engineer at IVP · | 5 upvotes · 652.3K views

        Hey there! We are looking at Datadog, Dynatrace, AppDynamics, and New Relic as options for our web application monitoring.

        Current Environment: .NET Core Web app hosted on Microsoft IIS

        Future Environment: Web app will be hosted on Microsoft Azure

        Tech Stacks: IIS, RabbitMQ, Redis, Microsoft SQL Server

        Requirement: Infra Monitoring, APM, Real - User Monitoring (User activity monitoring i.e., time spent on a page, most active page, etc.), Service Tracing, Root Cause Analysis, and Centralized Log Management.

        Please advise on the above. Thanks!

        See more

        Hi Folks,

        I am trying to evaluate Site24x7 against AppDynamics, Dynatrace, and New Relic. Has anyone used Site24X7? If so, what are your opinions on the tool? I know that the license costs are very low compared to other tools in the market. Other than that, are there any major issues anyone has encountered using the tool itself?

        See more
        Prometheus logo

        Prometheus

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        An open-source service monitoring system and time series database, developed by SoundCloud
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        PROS OF PROMETHEUS
        • 45
          Powerful easy to use monitoring
        • 38
          Flexible query language
        • 32
          Dimensional data model
        • 27
          Alerts
        • 22
          Active and responsive community
        • 21
          Extensive integrations
        • 19
          Easy to setup
        • 12
          Beautiful Model and Query language
        • 7
          Easy to extend
        • 6
          Nice
        • 3
          Written in Go
        • 2
          Good for experimentation
        • 1
          Easy for monitoring
        CONS OF PROMETHEUS
        • 11
          Just for metrics
        • 6
          Needs monitoring to access metrics endpoints
        • 6
          Bad UI
        • 3
          Not easy to configure and use
        • 2
          Requires multiple applications and tools
        • 2
          Written in Go
        • 2
          Supports only active agents
        • 1
          TLS is quite difficult to understand

        related Prometheus posts

        Conor Myhrvold
        Tech Brand Mgr, Office of CTO at Uber · | 14 upvotes · 2.9M views

        Why we spent several years building an open source, large-scale metrics alerting system, M3, built for Prometheus:

        By late 2014, all services, infrastructure, and servers at Uber emitted metrics to a Graphite stack that stored them using the Whisper file format in a sharded Carbon cluster. We used Grafana for dashboarding and Nagios for alerting, issuing Graphite threshold checks via source-controlled scripts. While this worked for a while, expanding the Carbon cluster required a manual resharding process and, due to lack of replication, any single node’s disk failure caused permanent loss of its associated metrics. In short, this solution was not able to meet our needs as the company continued to grow.

        To ensure the scalability of Uber’s metrics backend, we decided to build out a system that provided fault tolerant metrics ingestion, storage, and querying as a managed platform...

        https://eng.uber.com/m3/

        (GitHub : https://github.com/m3db/m3)

        See more
        Matt Menzenski
        Senior Software Engineering Manager at PayIt · | 12 upvotes · 77.1K views

        Grafana and Prometheus together, running on Kubernetes , is a powerful combination. These tools are cloud-native and offer a large community and easy integrations. At PayIt we're using exporting Java application metrics using a Dropwizard metrics exporter, and our Node.js services now use the prom-client npm library to serve metrics.

        See more
        Splunk logo

        Splunk

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        Search, monitor, analyze and visualize machine data
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        PROS OF SPLUNK
        • 2
          API for searching logs, running reports
        • 1
          Query engine supports joining, aggregation, stats, etc
        • 1
          Query any log as key-value pairs
        • 1
          Splunk language supports string, date manip, math, etc
        • 1
          Granular scheduling and time window support
        • 1
          Alert system based on custom query results
        • 1
          Custom log parsing as well as automatic parsing
        • 1
          Dashboarding on any log contents
        • 1
          Ability to style search results into reports
        • 1
          Rich GUI for searching live logs
        CONS OF SPLUNK
        • 1
          Splunk query language rich so lots to learn

        related Splunk posts

        Shared insights
        on
        KibanaKibanaSplunkSplunkGrafanaGrafana

        I use Kibana because it ships with the ELK stack. I don't find it as powerful as Splunk however it is light years above grepping through log files. We previously used Grafana but found it to be annoying to maintain a separate tool outside of the ELK stack. We were able to get everything we needed from Kibana.

        See more
        Datadog logo

        Datadog

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        Unify logs, metrics, and traces from across your distributed infrastructure.
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        PROS OF DATADOG
        • 133
          Monitoring for many apps (databases, web servers, etc)
        • 104
          Easy setup
        • 84
          Powerful ui
        • 81
          Powerful integrations
        • 68
          Great value
        • 52
          Great visualization
        • 44
          Events + metrics = clarity
        • 40
          Custom metrics
        • 39
          Notifications
        • 37
          Flexibility
        • 17
          Free & paid plans
        • 14
          Great customer support
        • 13
          Makes my life easier
        • 8
          Adapts automatically as i scale up
        • 8
          Easy setup and plugins
        • 6
          Super easy and powerful
        • 5
          In-context collaboration
        • 5
          AWS support
        • 4
          Rich in features
        • 3
          Docker support
        • 3
          Cost
        • 3
          Best than others
        • 2
          Source control and bug tracking
        • 2
          Easy to Analyze
        • 2
          Expensive
        • 2
          Cute logo
        • 2
          Good for Startups
        • 2
          Free setup
        • 2
          Monitor almost everything
        • 2
          Automation tools
        • 2
          Simple, powerful, great for infra
        • 2
          Full visibility of applications
        • 1
          Best in the field
        CONS OF DATADOG
        • 16
          Expensive
        • 3
          No errors exception tracking
        • 2
          External Network Goes Down You Wont Be Logging
        • 1
          Complicated

        related Datadog posts

        Robert Zuber

        Our primary source of monitoring and alerting is Datadog. We’ve got prebuilt dashboards for every scenario and integration with PagerDuty to manage routing any alerts. We’ve definitely scaled past the point where managing dashboards is easy, but we haven’t had time to invest in using features like Anomaly Detection. We’ve started using Honeycomb for some targeted debugging of complex production issues and we are liking what we’ve seen. We capture any unhandled exceptions with Rollbar and, if we realize one will keep happening, we quickly convert the metrics to point back to Datadog, to keep Rollbar as clean as possible.

        We use Segment to consolidate all of our trackers, the most important of which goes to Amplitude to analyze user patterns. However, if we need a more consolidated view, we push all of our data to our own data warehouse running PostgreSQL; this is available for analytics and dashboard creation through Looker.

        See more

        We are looking for a centralised monitoring solution for our application deployed on Amazon EKS. We would like to monitor using metrics from Kubernetes, AWS services (NeptuneDB, AWS Elastic Load Balancing (ELB), Amazon EBS, Amazon S3, etc) and application microservice's custom metrics.

        We are expected to use around 80 microservices (not replicas). I think a total of 200-250 microservices will be there in the system with 10-12 slave nodes.

        We tried Prometheus but it looks like maintenance is a big issue. We need to manage scaling, maintaining the storage, and dealing with multiple exporters and Grafana. I felt this itself needs few dedicated resources (at least 2-3 people) to manage. Not sure if I am thinking in the correct direction. Please confirm.

        You mentioned Datadog and Sysdig charges per host. Does it charge per slave node?

        See more
        AWS X-Ray logo

        AWS X-Ray

        53
        80
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        An application performance management service
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        PROS OF AWS X-RAY
          Be the first to leave a pro
          CONS OF AWS X-RAY
            Be the first to leave a con

            related AWS X-Ray posts