Alternatives to Dynatrace logo

Alternatives to Dynatrace

Datadog, AppDynamics, New Relic, Splunk, and Prometheus are the most popular alternatives and competitors to Dynatrace.
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What is Dynatrace and what are its top alternatives?

Dynatrace is a leading software intelligence platform that provides monitoring and management capabilities for cloud-native architectures. It offers full-stack observability, AIOps, and digital experience management to optimize performance and user satisfaction. However, Dynatrace can be complex to set up and may come with a higher price tag compared to other alternatives.

  1. New Relic: New Relic is a cloud-based application performance monitoring tool that offers real-time analytics, error tracking, and infrastructure monitoring. It provides a user-friendly interface and customizable dashboards. Pros: Easy to use, scalable, and great support. Cons: Cost may be a concern for smaller businesses.
  2. AppDynamics: AppDynamics is an APM solution that helps businesses monitor the performance of their applications in real-time. It provides deep visibility into application performance and user interactions. Pros: Strong analytics capabilities and robust monitoring. Cons: Complex setup and pricing.
  3. Splunk: Splunk is a data analytics platform that can be used for monitoring and troubleshooting applications and IT infrastructure. It offers log management, real-time monitoring, and machine learning capabilities. Pros: Powerful analytics, customizable dashboards. Cons: Steep learning curve, high cost.
  4. Datadog: Datadog is a cloud monitoring and observability platform that provides infrastructure monitoring, application performance monitoring, and log management. It offers integrations with various cloud services and technologies. Pros: Easy to use, great visualization tools. Cons: Pricing can add up quickly.
  5. Azure Monitor: Azure Monitor is a cloud monitoring service provided by Microsoft Azure. It offers comprehensive monitoring and alerting capabilities for applications and infrastructure hosted on Azure. Pros: Seamless integration with Azure services, cost-effective for Azure users. Cons: Limited support for non-Azure environments.
  6. Prometheus: Prometheus is an open-source monitoring and alerting toolkit designed for cloud-native environments. It collects metrics from various sources, stores them, and provides a querying language for analysis. Pros: Open-source and highly customizable. Cons: Requires expertise to set up and maintain.
  7. Grafana: Grafana is an open-source visualization and monitoring platform that can be used with various data sources, including Prometheus, InfluxDB, and Graphite. It offers customizable dashboards and alerts. Pros: Highly customizable, community support. Cons: Can be challenging to set up.
  8. LogicMonitor: LogicMonitor is a SaaS-based performance monitoring platform that offers infrastructure monitoring, application performance monitoring, and log management. It provides automatic discovery and alerting capabilities. Pros: Easy to deploy, automated monitoring. Cons: Pricing may be a drawback for some users.
  9. Raygun: Raygun is an application performance monitoring tool that provides real-time insights into application performance and user experiences. It offers error tracking, crash reporting, and performance monitoring. Pros: Easy to set up, great error reporting. Cons: Limited integrations compared to other tools.
  10. SolarWinds AppOptics: SolarWinds AppOptics is a cloud-based infrastructure and application performance monitoring tool that offers real-time visibility into performance metrics and dependencies. It provides monitoring for cloud, on-premises, and hybrid environments. Pros: Cloud monitoring capabilities, easy setup. Cons: Pricing may be a concern for some users.

Top Alternatives to Dynatrace

  • 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! ...

  • AppDynamics
    AppDynamics

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

  • 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. ...

  • Splunk
    Splunk

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

  • 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. ...

  • Solarwinds
    Solarwinds

    Developed by network and systems engineers who know what it takes to manage today's dynamic IT environments, SolarWinds has a deep connection to the IT community. ...

  • SigNoz
    SigNoz

    SigNoz is an open-source application performance monitoring tool(APM) tool. It helps developers monitor their application and troubleshoot problems. It can be self-hosted, so it's a great tool for privacy focused companies. ...

  • Kibana
    Kibana

    Kibana is an open source (Apache Licensed), browser based analytics and search dashboard for Elasticsearch. Kibana is a snap to setup and start using. Kibana strives to be easy to get started with, while also being flexible and powerful, just like Elasticsearch. ...

Dynatrace alternatives & related posts

Datadog logo

Datadog

9.4K
860
Unify logs, metrics, and traces from across your distributed infrastructure.
9.4K
860
PROS OF DATADOG
  • 139
    Monitoring for many apps (databases, web servers, etc)
  • 107
    Easy setup
  • 87
    Powerful ui
  • 84
    Powerful integrations
  • 70
    Great value
  • 54
    Great visualization
  • 46
    Events + metrics = clarity
  • 41
    Notifications
  • 41
    Custom metrics
  • 39
    Flexibility
  • 19
    Free & paid plans
  • 16
    Great customer support
  • 15
    Makes my life easier
  • 10
    Adapts automatically as i scale up
  • 9
    Easy setup and plugins
  • 8
    Super easy and powerful
  • 7
    AWS support
  • 7
    In-context collaboration
  • 6
    Rich in features
  • 5
    Docker support
  • 4
    Cost
  • 4
    Full visibility of applications
  • 4
    Monitor almost everything
  • 4
    Cute logo
  • 4
    Automation tools
  • 4
    Source control and bug tracking
  • 4
    Simple, powerful, great for infra
  • 4
    Easy to Analyze
  • 4
    Best than others
  • 3
    Best in the field
  • 3
    Expensive
  • 3
    Good for Startups
  • 3
    Free setup
  • 2
    APM
CONS OF DATADOG
  • 20
    Expensive
  • 4
    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.

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Farzeem Diamond Jiwani
Software Engineer at IVP · | 8 upvotes · 1.5M 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
AppDynamics logo

AppDynamics

310
68
Application management for the cloud generation
310
68
PROS OF APPDYNAMICS
  • 21
    Deep code visibility
  • 13
    Powerful
  • 8
    Real-Time Visibility
  • 7
    Great visualization
  • 6
    Easy Setup
  • 6
    Comprehensive Coverage of Programming Languages
  • 4
    Deep DB Troubleshooting
  • 3
    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 · | 8 upvotes · 1.5M 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

We are evaluating an APM tool and would like to select between AppDynamics or Datadog. Our applications are largely hosted on Microsoft Azure but we would keep the option to move to AWS or Google Cloud Platform in the future.

In addition to core Azure services, we will be hosting other components - including MongoDB, Keycloak, PagerDuty, etc. Our applications are largely C# and React-based using frontend for Backend patterns and Azure API gateway. In addition, there are close to 50+ external services integrated using both REST and SOAP.

See more
New Relic logo

New Relic

20.8K
1.9K
New Relic is the industry’s largest and most comprehensive cloud-based observability platform.
20.8K
1.9K
PROS OF NEW RELIC
  • 415
    Easy setup
  • 344
    Really powerful
  • 245
    Awesome visualization
  • 194
    Ease of use
  • 151
    Great ui
  • 106
    Free tier
  • 80
    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
  • 13
    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
  • 7
    Detailed reports
  • 6
    Performance of External Services
  • 6
    Error Analysis
  • 6
    Application Availability Monitoring and Alerting
  • 6
    Application Response Times
  • 5
    Most Time Consuming Transactions
  • 5
    JVM Performance Analyzer (Java)
  • 4
    Browser Transaction Tracing
  • 4
    Top Database Operations
  • 4
    Easy to use
  • 3
    Application Map
  • 3
    Weekly Performance Email
  • 3
    Pagoda Box integration
  • 3
    Custom Dashboards
  • 2
    Easy to setup
  • 2
    Background Jobs Transaction Analysis
  • 2
    App Speed Index
  • 1
    Super Expensive
  • 1
    Team Collaboration Tools
  • 1
    Metric Data Retention
  • 1
    Metric Data Resolution
  • 1
    Worst Transactions by User Dissatisfaction
  • 1
    Real User Monitoring Overview
  • 1
    Real User Monitoring Analysis and Breakdown
  • 1
    Time Comparisons
  • 1
    Access to Performance Data API
  • 1
    Incident Detection and Alerting
  • 1
    Best of the best, what more can you ask for
  • 1
    Best monitoring on the market
  • 1
    Rails integration
  • 1
    Free
  • 0
    Proce
  • 0
    Price
  • 0
    Exceptions
  • 0
    Cost
CONS OF NEW RELIC
  • 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

related New Relic posts

Farzeem Diamond Jiwani
Software Engineer at IVP · | 8 upvotes · 1.5M 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
Shared insights
on
New RelicNew RelicKibanaKibana

I need to choose a monitoring tool for my project, but currently, my application doesn't have much load or many users. My application is not generating GBs of data. We don't want to send the user information to New Relic because it's a 3rd party tool. And we can deploy Kibana locally on our server. What should I use, Kibana or New Relic?

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Splunk logo

Splunk

614
20
Search, monitor, analyze and visualize machine data
614
20
PROS OF SPLUNK
  • 3
    API for searching logs, running reports
  • 3
    Alert system based on custom query results
  • 2
    Splunk language supports string, date manip, math, etc
  • 2
    Dashboarding on any log contents
  • 2
    Custom log parsing as well as automatic parsing
  • 2
    Query engine supports joining, aggregation, stats, etc
  • 2
    Rich GUI for searching live logs
  • 2
    Ability to style search results into reports
  • 1
    Granular scheduling and time window support
  • 1
    Query any log as key-value pairs
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.

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Shared insights
on
SplunkSplunkElasticsearchElasticsearch

We are currently exploring Elasticsearch and Splunk for our centralized logging solution. I need some feedback about these two tools. We expect our logs in the range of upwards > of 10TB of logging data.

See more
Prometheus logo

Prometheus

4.3K
239
An open-source service monitoring system and time series database, developed by SoundCloud
4.3K
239
PROS OF PROMETHEUS
  • 47
    Powerful easy to use monitoring
  • 38
    Flexible query language
  • 32
    Dimensional data model
  • 27
    Alerts
  • 23
    Active and responsive community
  • 22
    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
  • 12
    Just for metrics
  • 6
    Bad UI
  • 6
    Needs monitoring to access metrics endpoints
  • 4
    Not easy to configure and use
  • 3
    Supports only active agents
  • 2
    Written in Go
  • 2
    TLS is quite difficult to understand
  • 2
    Requires multiple applications and tools
  • 1
    Single point of failure

related Prometheus posts

Matt Menzenski
Senior Software Engineering Manager at PayIt · | 16 upvotes · 1M 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
Conor Myhrvold
Tech Brand Mgr, Office of CTO at Uber · | 15 upvotes · 5M 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
Solarwinds logo

Solarwinds

77
0
Unlock powerful workflows, automation, and reporting
77
0
PROS OF SOLARWINDS
    Be the first to leave a pro
    CONS OF SOLARWINDS
      Be the first to leave a con

      related Solarwinds posts

      SigNoz logo

      SigNoz

      15
      2
      Open-source alternative to DataDog
      15
      2
      PROS OF SIGNOZ
      • 1
        Based on OpenTelemetry
      • 1
        Open Source
      CONS OF SIGNOZ
        Be the first to leave a con

        related SigNoz posts

        Kibana logo

        Kibana

        20.4K
        262
        Visualize your Elasticsearch data and navigate the Elastic Stack
        20.4K
        262
        PROS OF KIBANA
        • 88
          Easy to setup
        • 65
          Free
        • 45
          Can search text
        • 21
          Has pie chart
        • 13
          X-axis is not restricted to timestamp
        • 9
          Easy queries and is a good way to view logs
        • 6
          Supports Plugins
        • 4
          Dev Tools
        • 3
          More "user-friendly"
        • 3
          Can build dashboards
        • 2
          Out-of-Box Dashboards/Analytics for Metrics/Heartbeat
        • 2
          Easy to drill-down
        • 1
          Up and running
        CONS OF KIBANA
        • 7
          Unintuituve
        • 4
          Works on top of elastic only
        • 4
          Elasticsearch is huge
        • 3
          Hardweight UI

        related Kibana posts

        Tymoteusz Paul
        Devops guy at X20X Development LTD · | 23 upvotes · 9.8M views

        Often enough I have to explain my way of going about setting up a CI/CD pipeline with multiple deployment platforms. Since I am a bit tired of yapping the same every single time, I've decided to write it up and share with the world this way, and send people to read it instead ;). I will explain it on "live-example" of how the Rome got built, basing that current methodology exists only of readme.md and wishes of good luck (as it usually is ;)).

        It always starts with an app, whatever it may be and reading the readmes available while Vagrant and VirtualBox is installing and updating. Following that is the first hurdle to go over - convert all the instruction/scripts into Ansible playbook(s), and only stopping when doing a clear vagrant up or vagrant reload we will have a fully working environment. As our Vagrant environment is now functional, it's time to break it! This is the moment to look for how things can be done better (too rigid/too lose versioning? Sloppy environment setup?) and replace them with the right way to do stuff, one that won't bite us in the backside. This is the point, and the best opportunity, to upcycle the existing way of doing dev environment to produce a proper, production-grade product.

        I should probably digress here for a moment and explain why. I firmly believe that the way you deploy production is the same way you should deploy develop, shy of few debugging-friendly setting. This way you avoid the discrepancy between how production work vs how development works, which almost always causes major pains in the back of the neck, and with use of proper tools should mean no more work for the developers. That's why we start with Vagrant as developer boxes should be as easy as vagrant up, but the meat of our product lies in Ansible which will do meat of the work and can be applied to almost anything: AWS, bare metal, docker, LXC, in open net, behind vpn - you name it.

        We must also give proper consideration to monitoring and logging hoovering at this point. My generic answer here is to grab Elasticsearch, Kibana, and Logstash. While for different use cases there may be better solutions, this one is well battle-tested, performs reasonably and is very easy to scale both vertically (within some limits) and horizontally. Logstash rules are easy to write and are well supported in maintenance through Ansible, which as I've mentioned earlier, are at the very core of things, and creating triggers/reports and alerts based on Elastic and Kibana is generally a breeze, including some quite complex aggregations.

        If we are happy with the state of the Ansible it's time to move on and put all those roles and playbooks to work. Namely, we need something to manage our CI/CD pipelines. For me, the choice is obvious: TeamCity. It's modern, robust and unlike most of the light-weight alternatives, it's transparent. What I mean by that is that it doesn't tell you how to do things, doesn't limit your ways to deploy, or test, or package for that matter. Instead, it provides a developer-friendly and rich playground for your pipelines. You can do most the same with Jenkins, but it has a quite dated look and feel to it, while also missing some key functionality that must be brought in via plugins (like quality REST API which comes built-in with TeamCity). It also comes with all the common-handy plugins like Slack or Apache Maven integration.

        The exact flow between CI and CD varies too greatly from one application to another to describe, so I will outline a few rules that guide me in it: 1. Make build steps as small as possible. This way when something breaks, we know exactly where, without needing to dig and root around. 2. All security credentials besides development environment must be sources from individual Vault instances. Keys to those containers should exist only on the CI/CD box and accessible by a few people (the less the better). This is pretty self-explanatory, as anything besides dev may contain sensitive data and, at times, be public-facing. Because of that appropriate security must be present. TeamCity shines in this department with excellent secrets-management. 3. Every part of the build chain shall consume and produce artifacts. If it creates nothing, it likely shouldn't be its own build. This way if any issue shows up with any environment or version, all developer has to do it is grab appropriate artifacts to reproduce the issue locally. 4. Deployment builds should be directly tied to specific Git branches/tags. This enables much easier tracking of what caused an issue, including automated identifying and tagging the author (nothing like automated regression testing!).

        Speaking of deployments, I generally try to keep it simple but also with a close eye on the wallet. Because of that, I am more than happy with AWS or another cloud provider, but also constantly peeking at the loads and do we get the value of what we are paying for. Often enough the pattern of use is not constantly erratic, but rather has a firm baseline which could be migrated away from the cloud and into bare metal boxes. That is another part where this approach strongly triumphs over the common Docker and CircleCI setup, where you are very much tied in to use cloud providers and getting out is expensive. Here to embrace bare-metal hosting all you need is a help of some container-based self-hosting software, my personal preference is with Proxmox and LXC. Following that all you must write are ansible scripts to manage hardware of Proxmox, similar way as you do for Amazon EC2 (ansible supports both greatly) and you are good to go. One does not exclude another, quite the opposite, as they can live in great synergy and cut your costs dramatically (the heavier your base load, the bigger the savings) while providing production-grade resiliency.

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        Tassanai Singprom

        This is my stack in Application & Data

        JavaScript PHP HTML5 jQuery Redis Amazon EC2 Ubuntu Sass Vue.js Firebase Laravel Lumen Amazon RDS GraphQL MariaDB

        My Utilities Tools

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