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  1. Stackups
  2. DevOps
  3. Performance Monitoring
  4. Performance Monitoring
  5. New Relic vs Scout

New Relic vs Scout

OverviewDecisionsComparisonAlternatives

Overview

New Relic
New Relic
Stacks22.7K
Followers8.7K
Votes1.9K
Scout
Scout
Stacks84
Followers86
Votes21

New Relic vs Scout: What are the differences?

Introduction

This Markdown code provides a comparison between New Relic and Scout, highlighting their key differences. New Relic and Scout are both monitoring tools that help users gain insights about the performance and behavior of their applications. However, they differ in various aspects that are outlined below.

  1. Pricing: New Relic offers a flexible pricing model based on the number of monitored hosts, but their plans can be expensive for smaller organizations. On the other hand, Scout follows a flat pricing model that includes all features, making it more cost-effective for smaller teams or startups.

  2. User Interface: New Relic provides a comprehensive and visually appealing user interface with various intuitive features. On the contrary, Scout offers a simpler and more streamlined user interface, focusing on essential metrics and minimizing clutter.

  3. Alerting Capabilities: New Relic offers a wide range of customizable alerting options, allowing users to set thresholds and receive notifications via multiple channels. Scout, on the other hand, lacks some advanced alerting features and might not be as extensive in terms of setting up complex alert conditions.

  4. Plugins and Integrations: New Relic has a vast ecosystem of plugins and integrations with popular software and platforms, enabling users to extend its monitoring capabilities. Scout, although it supports integrations, has a more limited selection of plugins available.

  5. Data Granularity: New Relic provides highly detailed monitoring data with minute-level granularity, allowing users to analyze application performance at a highly specific level. Scout, on the other hand, offers more aggregated data by default, which might be sufficient for most use cases but lacks the granularity of New Relic.

  6. Ease of Setup: New Relic has a more complex setup process that requires installing agents on hosts or using containerized environments. Scout, on the other hand, has a straightforward setup that can be done by installing a single agent or using lightweight monitoring tools.

In summary, New Relic provides a feature-rich monitoring solution with advanced alerting capabilities, a comprehensive user interface, and detailed data granularity. However, it can be costlier and more complex to set up compared to Scout, which offers a simpler interface, a more affordable pricing model, and a focus on essential metrics monitoring.

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Advice on New Relic, Scout

Medeti
Medeti

Jun 27, 2020

Needs adviceonAmazon EKSAmazon EKSKubernetesKubernetesAWS Elastic Load Balancing (ELB)AWS Elastic Load Balancing (ELB)

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?

1.51M views1.51M
Comments
Benoit
Benoit

Principal Engineer at Sqreen

Sep 17, 2019

Decided

I chose Datadog APM because the much better APM insights it provides (flamegraph, percentiles by default).

The drawbacks of this decision are we had to move our production monitoring to TimescaleDB + Telegraf instead of NR Insight

NewRelic is definitely easier when starting out. Agent is only a lib and doesn't require a daemon

457k views457k
Comments
Attila
Attila

Founder at artkonekt

Mar 24, 2020

Decided

I haven't heard much about Datadog until about a year ago. Ironically, the NewRelic sales person who I had a series of trainings with was trash talking about Datadog a lot. That drew my attention to Datadog and I gave it a try at another client project where we needed log handling, dashboards and alerting.

In 2019, Datadog was already offering log management and from that perspective, it was ahead of NewRelic. Other than that, from my perspective, the two tools are offering a very-very similar set of tools. Therefore I wouldn't say there's a significant difference between the two, the decision is likely a matter of taste. The pricing is also very similar.

The reasons why we chose Datadog over NewRelic were:

  • The presence of log handling feature (since then, logging is GA at NewRelic as well since falls 2019).
  • The setup was easier even though I already had experience with NewRelic, including participation in NewRelic trainings.
  • The UI of Datadog is more compact and my experience is smoother.
  • The NewRelic UI is very fragmented and New Relic One is just increasing this experience for me.
  • The log feature of Datadog is very well designed, I find very useful the tagging logs with services. The log filtering is also very awesome.

Bottom line is that both tools are great and it makes sense to discover both and making the decision based on your use case. In our case, Datadog was the clear winner due to its UI, ease of setup and the awesome logging and alerting features.

471k views471k
Comments

Detailed Comparison

New Relic
New Relic
Scout
Scout

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.

Scout APM helps developers quickly pinpoint & resolve performance issues before the customer ever sees them. Spend less time debugging & more time building with a streamlined interface & tracing logic that ties bottlenecks to source code.

Performance Data Retention;Real-User Response Time, Throughput, & Breakdown by Layer;App Response Time, Throughput, & Breakdown by Component;App Availability Monitoring, Alerting, and Notification;Automatic Application Topology Mapping;Server Resource and Availability Monitoring;Error Detection, Alerting, & Analysis;JVM Performance Analyzer;Database Call Response Time & Throughput;Performance Data API Access;Code Level Diagnostics, Transaction Tracing, & Stack Trace Details;Slow SQL and SQL Performance Details;Real-User Breakdown by Web Page, Browser, & Geography;Track Individual Key Transactions;Mobile Features- Alerting, Summary Data, Overview Page, Topo Map, HTTP Requests, HTTP Error Summary, HTTP Error Detail, Versions, Carriers, Devices, Geo Map
Monitors Ruby, PHP, Python, Node.js & Elixir apps;Easy install;Detailed transaction traces;Alerting;Deploy Tracking
Statistics
Stacks
22.7K
Stacks
84
Followers
8.7K
Followers
86
Votes
1.9K
Votes
21
Pros & Cons
Pros
  • 414
    Easy setup
  • 344
    Really powerful
  • 245
    Awesome visualization
  • 194
    Ease of use
  • 151
    Great ui
Cons
  • 20
    Pricing model doesn't suit microservices
  • 10
    UI isn't great
  • 7
    Expensive
  • 7
    Visualizations aren't very helpful
  • 5
    Hard to understand why things in your app are breaking
Pros
  • 8
    Easy setup
  • 5
    Plugins
  • 3
    Affordable
  • 1
    GIT Integration
  • 1
    Profiles Ruby Memory Usage
Integrations
AppHarbor
AppHarbor
Cloudability
Cloudability
HP Cloud Compute
HP Cloud Compute
cloudControl
cloudControl
Papertrail
Papertrail
Loggly
Loggly
Ducksboard
Ducksboard
Blitz
Blitz
Pivotal Tracker
Pivotal Tracker
Red Hat OpenShift
Red Hat OpenShift
No integrations available

What are some alternatives to New Relic, Scout?

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!

Raygun

Raygun

Raygun gives you a window into how users are really experiencing your software applications. Detect, diagnose and resolve issues that are affecting end users with greater speed and accuracy.

AppSignal

AppSignal

AppSignal gives you and your team alerts and detailed metrics about your Ruby, Node.js or Elixir application. Sensible pricing, no aggressive sales & support by developers.

AppDynamics

AppDynamics

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

Stackify

Stackify

Stackify offers the only developers-friendly innovative cloud based solution that fully integrates application performance management (APM) with error and log. Allowing them to easily monitor, detect and resolve application issues faster

Skylight

Skylight

Skylight is a smart profiler for your Rails apps that visualizes request performance across all of your servers.

Librato

Librato

Librato provides a complete solution for monitoring and understanding the metrics that impact your business at all levels of the stack. We provide everything you need to visualize, analyze, and actively alert on the metrics that matter to you.

Keymetrics

Keymetrics

PM2 is a production process manager for Node.js applications with a built-in load balancer. It allows you to keep applications alive forever, to reload them without downtime and to facilitate common system admin tasks.

Dynatrace

Dynatrace

It is an AI-powered, full stack, automated performance management solution. It provides user experience analysis that identifies and resolves application performance issues faster than ever before.

SignalFx

SignalFx

We provide operational intelligence for today’s elastic architectures through monitoring specifically designed for microservices and containers with: -powerful and proactive alerting -metrics aggregation -visualization into time series data

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