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AWS X-Ray VS statsmodels

Compare AWS X-Ray VS statsmodels and see what are their differences

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AWS X-Ray logo AWS X-Ray

AWS X-Ray helps developers analyze and debug production and distributed applications.

statsmodels logo statsmodels

Statsmodels: statistical modeling and econometrics in Python - statsmodels/statsmodels
  • AWS X-Ray Landing page
    Landing page //
    2023-04-20
  • statsmodels Landing page
    Landing page //
    2023-08-18

AWS X-Ray features and specs

  • Comprehensive Tracing
    AWS X-Ray provides end-to-end tracing capabilities, allowing you to analyze and debug applications across various AWS services. This helps in identifying performance bottlenecks and understanding user impact.
  • Integration with AWS Services
    X-Ray seamlessly integrates with a wide range of AWS services, such as Lambda, EC2, and DynamoDB, offering in-depth insights into how these services are interacting with your applications.
  • Visual Depictions
    The service offers a visual representation of service maps and trace data, making it easier for developers to understand application performance issues without needing deep technical knowledge.
  • Sampling and Customization
    AWS X-Ray supports configurable sampling, enabling you to control the amount of data being traced. This helps manage both the overhead and cost associated with tracing operations.
  • Improves Developer Productivity
    By providing real-time insights and powerful debugging capabilities, AWS X-Ray reduces the time and effort required for diagnosing production issues, thereby enhancing developer productivity.

Possible disadvantages of AWS X-Ray

  • Complexity in Setup
    Setting up AWS X-Ray, especially in large and complex environments, can be intricate and may require significant effort to properly configure its various components.
  • Cost Considerations
    Using AWS X-Ray could lead to potential increases in costs, particularly in large-scale deployments where extensive tracing and data storage might be needed.
  • Performance Overheads
    Although designed to minimize impact, enabling X-Ray on applications may introduce some performance overhead, especially with higher sampling rates.
  • Learning Curve
    There is a learning curve associated with understanding and effectively utilizing AWS X-Ray's features, particularly for developers new to distributed tracing or the AWS ecosystem.
  • Limited Support for Non-AWS Environments
    While AWS X-Ray is highly effective within the AWS ecosystem, its support and integration options for non-AWS or hybrid cloud environments might be limited compared to other third-party solutions.

statsmodels features and specs

No features have been listed yet.

AWS X-Ray videos

+ Add

Optimize Application Performance with AWS X-Ray

More videos:

  • Demo - AWS X-Ray: Analyze, Debug & Optimize Application Performance | Concept | Demo
  • Review - AWS re:Invent 2017: Monitoring Modern Applications: Introduction to AWS X-Ray (DEV204)

statsmodels videos

+ Add

Linear Regressions with StatsModels

More videos:

  • Review - Code review - Z Test using statsmodels
  • Review - Code Review: Analyse Training VAR statsmodels with a real world dataset

Category Popularity

0-100% (relative to AWS X-Ray and statsmodels)

AWS X-Ray

statsmodels

Monitoring Tools
100 100%
Monitoring Tools
0% 0
Development Tools
0 0%
Development Tools
100% 100
Application Performance Monitoring
100 100%
Application Performance Monitoring
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100

User comments

Share your experience with using AWS X-Ray and statsmodels. For example, how are they different and which one is better?
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Social recommendations and mentions

Based on our record, AWS X-Ray should be more popular than statsmodels. It has been mentiond 24 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

AWS X-Ray mentions (24)

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statsmodels mentions (4)

  • [P] statsmodels.tsa.holtwinters.ExponentialSmoothing results in NaN forecasts and parameters when fitting on entire dataset using known parameters from training model.
    I reckon you're more likely to get a good response on their Github page than here. Unless a dev happens to see this post. Source: almost 3 years ago
  • How do you usually build your models?
    Since you are using python, pandas, scikit-learn, scipy, and statsmodels are what you are looking for. Source: about 3 years ago
  • Can we solve serverless cold starts?
    In case you're really worried about cold start latency and your application load shows high variance in the number of concurrent requests, you might want to get a bit fancier. You could use time-series forecasting to anticipate how many containers should be warmed at each point in time. StatsModels is an open-source project that offers the most common algorithms for working with time-series. Here's a good... - Source: dev.to / about 4 years ago
  • Advice required to choose appropriate software for an assignment
    Can't you get a student discount for Stata? R would definitely be able to handle everything. For Python, have a look through the statsmodel package https://github.com/statsmodels/statsmodels. Source: over 4 years ago

What are some alternatives?

When comparing AWS X-Ray and statsmodels, you can also consider the following products

Lumigo - With one-click distributed tracing, Lumigo lets developers effortlessly find and fix issues in serverless and microservices environments.

Flutter - Build beautiful native apps in record time 🚀

Amazon CloudWatch - Amazon CloudWatch is a monitoring service for AWS cloud resources and the applications you run on AWS.

python wiki - Component Libraries

Datadog - See metrics from all of your apps, tools & services in one place with Datadog's cloud monitoring as a service solution. Try it for free.

Ionic - Ionic is a cross-platform mobile development stack for building performant apps on all platforms with open web technologies.

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