helm-charts VS jaeger

Compare helm-charts vs jaeger and see what are their differences.

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helm-charts jaeger
1 97
256 19,906
1.2% 1.3%
7.7 9.8
6 days ago 4 days ago
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Apache License 2.0 Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.


Posts with mentions or reviews of helm-charts. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-12-20.
  • Serverless Spy Vs. Spy Chapter 3: X-Ray vs Jaeger - Send Lambda traces with open telemetry
    4 projects | dev.to | 20 Dec 2022
    With the sample apps from the opentelemetry-lambda repository the Lambda part itself was easy to implement. What took me some time was to provide the jaeger Fargate service with IaC ouside of an k8s environment. But with ECS and ServiceDiscovery that was easy in the end. This should be even more simple in an EKS environment with the jaegertracing helm-charts.


Posts with mentions or reviews of jaeger. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-07-18.
  • Instrumenting Django Applications using OpenTelemetry
    5 projects | dev.to | 18 Jul 2024
    In this articles we are going to go through instrumentating your django application using OTel. The project will demonstrate how to add logging for Prometheus and how to visualised spans using Jaeger.
  • OpenTelemetry Trace Context Propagation for gRPC Streams
    7 projects | dev.to | 19 Jun 2024
    First, you need to set up a basic infrastructure, with an OpenTelemetry (OTel) Collector to receive traces and Jaeger to store them, structuring the system like this:
  • Golang REST API boilerplate
    12 projects | dev.to | 4 Jun 2024
  • Observability with OpenTelemetry, Jaeger and Rails
    1 project | dev.to | 22 Feb 2024
    Jaeger maps the flow of requests and data as they traverse a distributed system. These requests may make calls to multiple services, which may introduce their own delays or errors. https://www.jaegertracing.io/
  • Show HN: An open source performance monitoring tool
    2 projects | news.ycombinator.com | 1 Feb 2024
    As engineers at past startups, we often had to debug slow queries, poor load times, inconsistent errors, etc... While tools like Jaegar [2] helped us inspect server-side performance, we had no way to tie user events to the traces we were inspecting. In other words, although we had an idea of what API route was slow, there wasn’t much visibility into the actual bottleneck.

    This is where our performance product comes in: we’re rethinking a tracing/performance tool that focuses on bridging the gap between the client and server.

    What’s unique about our approach is that we lean heavily into creating traces from the frontend. For example, if you’re using our Next.js SDK, we automatically connect browser HTTP requests with server-side code execution, all from the perspective of a user. We find this much more powerful because you can understand what part of your frontend codebase causes a given trace to occur. There’s an example here [3].

    From an instrumentation perspective, we’ve built our SDKs on-top of OTel, so you can create custom spans to expand highlight-created traces in server routes that will transparently roll up into the flame graph you see in our UI. You can also send us raw OTel traces and manually set up the client-server connection if you want. [4] Here’s an example of what a trace looks like with a database integration using our Golang GORM SDK, triggered by a frontend GraphQL query [5] [6].

    In terms of how it's built, we continue to rely heavily on ClickHouse as our time-series storage engine. Given that traces require that we also query based on an ID for specific groups of spans (more akin to an OLTP db), we’ve leveraged the power of CH materialized views to make these operations efficient (described here [7]).

    To try it out, you can spin up the project with our self hosted docs [8] or use our cloud offering at app.highlight.io. The entire stack runs in docker via a compose file, including an OpenTelemetry collector for data ingestion. You’ll need to point your SDK to export data to it by setting the relevant OTLP endpoint configuration (ie. environment variable OTEL_EXPORTER_OTLP_LOGS_ENDPOINT [9]).

    Overall, we’d really appreciate feedback on what we’re building here. We’re also all ears if anyone has opinions on what they’d like to see in a product like this!

    [1] https://github.com/highlight/highlight/blob/main/LICENSE

    [2] https://www.jaegertracing.io

    [3] https://app.highlight.io/1383/sessions/COu90Th4Qc3PVYTXbx9Xe...

    [4] https://www.highlight.io/docs/getting-started/native-opentel...

    [5] https://static.highlight.io/assets/docs/gorm.png

    [6] https://github.com/highlight/highlight/blob/1fc9487a676409f1...

    [7] https://highlight.io/blog/clickhouse-materialized-views

    [8] https://www.highlight.io/docs/getting-started/self-host/self...

    [9] https://opentelemetry.io/docs/concepts/sdk-configuration/otl...

  • Kubernetes Ingress Visibility
    2 projects | /r/kubernetes | 10 Dec 2023
    For the request following, something like jeager https://www.jaegertracing.io/, because you are talking more about tracing than necessarily logging. For just monitoring, https://github.com/prometheus-community/helm-charts/tree/main/charts/kube-prometheus-stack would be the starting point, then it depends. Nginx gives metrics out of the box, then you can pull in the dashboard like https://grafana.com/grafana/dashboards/14314-kubernetes-nginx-ingress-controller-nextgen-devops-nirvana/ , or full metal with something like service mesh monitoring which would provably fulfil most of the requirements
  • Migrating to OpenTelemetry
    8 projects | news.ycombinator.com | 16 Nov 2023
    Have you checked out Jaeger [1]? It is lightweight enough for a personal project, but featureful enough to really help "turn on the lightbulb" with other engineers to show them the difference between logging/monitoring and tracing.

    [1] https://www.jaegertracing.io/

  • The Road to GraphQL At Enterprise Scale
    6 projects | dev.to | 8 Nov 2023
    From the perspective of the realization of GraphQL infrastructure, the interesting direction is "Finding". How to find the problem? How to find the bottleneck of the system? Distributed Tracing System (DTS) will help answer this question. Distributed tracing is a method of observing requests as they propagate through distributed environments. In our scenario, we have dozens of subgraphs, gateway, and transport layer through which the request goes. We have several tools that can be used to detect the whole lifecycle of the request through the system, e.g. Jaeger, Zipkin or solutions that provided DTS as a part of the solution NewRelic.
  • OpenTelemetry Exporters - Types and Configuration Steps
    5 projects | dev.to | 30 Oct 2023
    Jaeger is an open-source, distributed tracing system that monitors and troubleshoots the flow of requests through complex, microservices-based applications, providing a comprehensive view of system interactions.
  • Fault Tolerance in Distributed Systems: Strategies and Case Studies
    4 projects | dev.to | 18 Oct 2023
    However, ensuring fault tolerance in distributed systems is not at all easy. These systems are complex, with multiple nodes or components working together. A failure in one node can cascade across the system if not addressed timely. Moreover, the inherently distributed nature of these systems can make it challenging to pinpoint the exact location and cause of fault - that is why modern systems rely heavily on distributed tracing solutions pioneered by Google Dapper and widely available now in Jaeger and OpenTracing. But still, understanding and implementing fault tolerance becomes not just about addressing the failure but predicting and mitigating potential risks before they escalate.

What are some alternatives?

When comparing helm-charts and jaeger you can also consider the following projects:

charts - Fairwinds helm chart repository

Sentry - Developer-first error tracking and performance monitoring

cp-helm-charts - The Confluent Platform Helm charts enable you to deploy Confluent Platform services on Kubernetes for development, test, and proof of concept environments.

skywalking - APM, Application Performance Monitoring System

opentelemetry-lambda - Create your own Lambda Layer in each OTel language using this starter code. Add the Lambda Layer to your Lamdba Function to get tracing with OpenTelemetry.

prometheus - The Prometheus monitoring system and time series database.

helm-charts - Prometheus community Helm charts

signoz - SigNoz is an open-source observability platform native to OpenTelemetry with logs, traces and metrics in a single application. An open-source alternative to DataDog, NewRelic, etc. 🔥 🖥. 👉 Open source Application Performance Monitoring (APM) & Observability tool

adot-otelstarter - Sending traces to jaeger with AWS lambda using the ADOT - AWS Distro for OpenTelemetry

Pinpoint - APM, (Application Performance Management) tool for large-scale distributed systems.

helm-charts - Helm chart repository containing the jenkins-infra public charts.

fluent-bit - Fast and Lightweight Logs and Metrics processor for Linux, BSD, OSX and Windows

InfluxDB - Power Real-Time Data Analytics at Scale
Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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SaaSHub helps you find the best software and product alternatives

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