Alternatives to Azure Application Insights logo

Alternatives to Azure Application Insights

New Relic, Google Analytics, AppDynamics, Azure Monitor, and Dynatrace are the most popular alternatives and competitors to Azure Application Insights.
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What is Azure Application Insights and what are its top alternatives?

Azure Application Insights is a cloud-based application performance management service that allows developers to monitor and diagnose issues in their applications. It provides features such as performance monitoring, log analytics, and user analytics. However, some limitations of Azure Application Insights include its cost for large-scale applications and the learning curve required to fully utilize all of its features.

  1. New Relic: New Relic offers performance monitoring, error tracking, and infrastructure monitoring for applications. It provides detailed insights into application performance and user experience. Pros: user-friendly interface, strong community support. Cons: can be expensive for large applications.

  2. Datadog: Datadog is a cloud monitoring service that offers application performance monitoring, infrastructure monitoring, and log management. It helps teams track the performance of their applications and infrastructure in real-time. Pros: easy to set up, offers integrations with many popular tools. Cons: pricing can be complex.

  3. Dynatrace: Dynatrace is an application performance management tool that provides monitoring for web applications, mobile apps, and microservices. It offers AI-powered insights and automatic root cause analysis for issues. Pros: offers detailed insights, easy to use dashboard. Cons: can be costly.

  4. Splunk: Splunk is a platform for monitoring and analyzing machine data, including log data. It offers features such as log management, monitoring, and alerting. Pros: powerful search capabilities, customizable dashboards. Cons: can have a steep learning curve.

  5. AppDynamics: AppDynamics is an application performance management tool that offers real-time monitoring, troubleshooting, and analytics for applications. It helps teams identify performance issues and optimize application performance. Pros: seamless integration with different technologies, extensive monitoring capabilities. Cons: high pricing.

  6. Raygun: Raygun offers application performance monitoring and error tracking for web and mobile applications. It provides real-time insights into application performance and user experience. Pros: user-friendly interface, affordable pricing plans. Cons: limited customization options.

  7. Stackify Retrace: Stackify Retrace is an APM tool that offers application monitoring, error tracking, and log management. It helps developers identify performance issues and troubleshoot errors in their applications. Pros: easy to set up, offers detailed performance metrics. Cons: limited integrations compared to other tools.

  8. Opsgenie by Atlassian: Opsgenie is an incident management and alerting tool that integrates with monitoring tools like Azure Application Insights. It helps teams respond to incidents faster and improve their incident management process. Pros: robust alerting capabilities, integrates with various monitoring tools. Cons: may require additional setup for full functionality.

  9. Instana: Instana is an application performance monitoring tool that offers automatic monitoring and tracing for cloud-native applications. It provides real-time insights into performance metrics and dependencies. Pros: automatic discovery of services, detailed performance analysis. Cons: pricing can be on the higher side.

  10. Grafana Cloud: Grafana Cloud is an observability platform that includes Grafana for visualization, Prometheus for monitoring, and Loki for logging. It offers a comprehensive solution for monitoring applications, infrastructure, and logs. Pros: powerful visualization capabilities, scalable platform. Cons: may require some technical expertise to set up and configure.

Top Alternatives to Azure Application Insights

  • 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. ...

  • Google Analytics
    Google Analytics

    Google Analytics lets you measure your advertising ROI as well as track your Flash, video, and social networking sites and applications. ...

  • AppDynamics
    AppDynamics

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

  • Azure Monitor
    Azure Monitor

    It provides sophisticated tools for collecting and analyzing telemetry that allow you to maximize the performance and availability of your cloud and on-premises resources and applications. ...

  • 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. ...

  • Splunk
    Splunk

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

  • ELK
    ELK

    It is the acronym for three open source projects: Elasticsearch, Logstash, and Kibana. Elasticsearch is a search and analytics engine. Logstash is a server‑side data processing pipeline that ingests data from multiple sources simultaneously, transforms it, and then sends it to a "stash" like Elasticsearch. Kibana lets users visualize data with charts and graphs in Elasticsearch. ...

  • Serilog
    Serilog

    It provides diagnostic logging to files, the console, and elsewhere. It is easy to set up, has a clean API, and is portable between recent .NET platforms. ...

Azure Application Insights alternatives & related posts

New Relic logo

New Relic

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New Relic is the industry’s largest and most comprehensive cloud-based observability platform.
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PROS OF NEW RELIC
  • 415
    Easy setup
  • 344
    Really powerful
  • 245
    Awesome visualization
  • 194
    Ease of use
  • 151
    Great ui
  • 107
    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
    Server Resources Monitoring
  • 11
    SQL Analysis
  • 9
    Transaction Tracing
  • 8
    Azure Add-on
  • 8
    Apdex Scores
  • 7
    Analysis of CPU, Disk, Memory, and Network
  • 7
    Detailed reports
  • 6
    Application Response Times
  • 6
    Error Analysis
  • 6
    Performance of External Services
  • 6
    Application Availability Monitoring and Alerting
  • 5
    JVM Performance Analyzer (Java)
  • 5
    Most Time Consuming Transactions
  • 4
    Top Database Operations
  • 4
    Browser Transaction Tracing
  • 4
    Easy to use
  • 3
    Application Map
  • 3
    Weekly Performance Email
  • 3
    Pagoda Box integration
  • 3
    Custom Dashboards
  • 2
    Easy to setup
  • 2
    App Speed Index
  • 2
    Background Jobs Transaction Analysis
  • 1
    Real User Monitoring Analysis and Breakdown
  • 1
    Incident Detection and Alerting
  • 1
    Team Collaboration Tools
  • 1
    Metric Data Retention
  • 1
    Metric Data Resolution
  • 1
    Worst Transactions by User Dissatisfaction
  • 1
    Real User Monitoring Overview
  • 1
    Free
  • 1
    Time Comparisons
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    Access to Performance Data API
  • 1
    Best of the best, what more can you ask for
  • 1
    Best monitoring on the market
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    Rails integration
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    Super Expensive
  • 0
    Proce
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    Exceptions
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    Price
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    Cost
CONS OF NEW RELIC
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    Pricing model doesn't suit microservices
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    UI isn't great
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    Expensive
  • 7
    Visualizations aren't very helpful
  • 5
    Hard to understand why things in your app are breaking

related New Relic posts

Cooper Marcus
Director of Ecosystem at Kong Inc. · | 17 upvotes · 111.1K views
Shared insights
on
New RelicNew RelicGitHubGitHubZapierZapier
at

I've used more and more of New Relic Insights here in my work at Kong. New Relic Insights is a "time series event database as a service" with a super-easy API for inserting custom events, and a flexible query language for building visualization widgets and dashboards.

I'm a big fan of New Relic Insights when I have data I know I need to analyze, but perhaps I'm not exactly sure how I want to analyze it in the future. For example, at Kong we recently wanted to get some understanding of our open source community's activity on our GitHub repos. I was able to quickly configure GitHub to send webhooks to Zapier , which in turn posted the JSON to New Relic Insights.

Insights is schema-less and configuration-less - just start posting JSON key value pairs, then start querying your data.

Within minutes, data was flowing from GitHub to Insights, and I was building widgets on my Insights dashboard to help my colleagues visualize the activity of our open source community.

#GitHubAnalytics #OpenSourceCommunityAnalytics #CommunityAnalytics #RepoAnalytics

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Julien DeFrance
Principal Software Engineer at Tophatter · | 16 upvotes · 3.2M views

Back in 2014, I was given an opportunity to re-architect SmartZip Analytics platform, and flagship product: SmartTargeting. This is a SaaS software helping real estate professionals keeping up with their prospects and leads in a given neighborhood/territory, finding out (thanks to predictive analytics) who's the most likely to list/sell their home, and running cross-channel marketing automation against them: direct mail, online ads, email... The company also does provide Data APIs to Enterprise customers.

I had inherited years and years of technical debt and I knew things had to change radically. The first enabler to this was to make use of the cloud and go with AWS, so we would stop re-inventing the wheel, and build around managed/scalable services.

For the SaaS product, we kept on working with Rails as this was what my team had the most knowledge in. We've however broken up the monolith and decoupled the front-end application from the backend thanks to the use of Rails API so we'd get independently scalable micro-services from now on.

Our various applications could now be deployed using AWS Elastic Beanstalk so we wouldn't waste any more efforts writing time-consuming Capistrano deployment scripts for instance. Combined with Docker so our application would run within its own container, independently from the underlying host configuration.

Storage-wise, we went with Amazon S3 and ditched any pre-existing local or network storage people used to deal with in our legacy systems. On the database side: Amazon RDS / MySQL initially. Ultimately migrated to Amazon RDS for Aurora / MySQL when it got released. Once again, here you need a managed service your cloud provider handles for you.

Future improvements / technology decisions included:

Caching: Amazon ElastiCache / Memcached CDN: Amazon CloudFront Systems Integration: Segment / Zapier Data-warehousing: Amazon Redshift BI: Amazon Quicksight / Superset Search: Elasticsearch / Amazon Elasticsearch Service / Algolia Monitoring: New Relic

As our usage grows, patterns changed, and/or our business needs evolved, my role as Engineering Manager then Director of Engineering was also to ensure my team kept on learning and innovating, while delivering on business value.

One of these innovations was to get ourselves into Serverless : Adopting AWS Lambda was a big step forward. At the time, only available for Node.js (Not Ruby ) but a great way to handle cost efficiency, unpredictable traffic, sudden bursts of traffic... Ultimately you want the whole chain of services involved in a call to be serverless, and that's when we've started leveraging Amazon DynamoDB on these projects so they'd be fully scalable.

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Google Analytics logo

Google Analytics

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Enterprise-class web analytics.
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PROS OF GOOGLE ANALYTICS
  • 1.5K
    Free
  • 926
    Easy setup
  • 890
    Data visualization
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    Real-time stats
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    Comprehensive feature set
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    Goals tracking
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    Powerful funnel conversion reporting
  • 138
    Customizable reports
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    Custom events try
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    Elastic api
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    Updated regulary
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  • 3
    Google play
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    Advanced ecommerce
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  • 1
    Medium / Channel data split
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    Irina
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    Financial Management Challenges -2015h
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    Lifesaver
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    Easy to integrate
CONS OF GOOGLE ANALYTICS
  • 11
    Confusing UX/UI
  • 8
    Super complex
  • 6
    Very hard to build out funnels
  • 4
    Poor web performance metrics
  • 3
    Very easy to confuse the user of the analytics
  • 2
    Time spent on page isn't accurate out of the box

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Alex Step

We used to use Google Analytics to get audience insights while running a startup and we are constantly doing experiments to lear our users. We are a small team and we have a lack of time to keep up with trends. Here is the list of problems we are experiencing: - Analytics takes too much time - We have enough time to regularly monitor analytics - Google Analytics interface is too advanced and complicated - It's difficult to detect anomalies and trends in GA

We considered other solutions on a market, but found 2 main issues: - The solution created for analytic experts - The solution is pretty expensive and non-automated

After learning this fact we decided to create AI-powered Slack bot to analyze Google Analytics and share trends. The bot is currently working and highlights trends for us.

We are thinking about publishing this solution as a SaaS. If you are interested in automating Google Analytics analysis, drop a comment and you'll get an early access.

We will implement this solution only if we have 20+ early adaptors. Leave a message with your thought. I appreciate any feedback.

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Tim Specht
‎Co-Founder and CTO at Dubsmash · | 14 upvotes · 957.6K views

In order to accurately measure & track user behaviour on our platform we moved over quickly from the initial solution using Google Analytics to a custom-built one due to resource & pricing concerns we had.

While this does sound complicated, it’s as easy as clients sending JSON blobs of events to Amazon Kinesis from where we use AWS Lambda & Amazon SQS to batch and process incoming events and then ingest them into Google BigQuery. Once events are stored in BigQuery (which usually only takes a second from the time the client sends the data until it’s available), we can use almost-standard-SQL to simply query for data while Google makes sure that, even with terabytes of data being scanned, query times stay in the range of seconds rather than hours. Before ingesting their data into the pipeline, our mobile clients are aggregating events internally and, once a certain threshold is reached or the app is going to the background, sending the events as a JSON blob into the stream.

In the past we had workers running that continuously read from the stream and would validate and post-process the data and then enqueue them for other workers to write them to BigQuery. We went ahead and implemented the Lambda-based approach in such a way that Lambda functions would automatically be triggered for incoming records, pre-aggregate events, and write them back to SQS, from which we then read them, and persist the events to BigQuery. While this approach had a couple of bumps on the road, like re-triggering functions asynchronously to keep up with the stream and proper batch sizes, we finally managed to get it running in a reliable way and are very happy with this solution today.

#ServerlessTaskProcessing #GeneralAnalytics #RealTimeDataProcessing #BigDataAsAService

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AppDynamics logo

AppDynamics

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Application management for the cloud generation
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PROS OF APPDYNAMICS
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    Deep code visibility
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    Powerful
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    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

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Farzeem Diamond Jiwani
Software Engineer at IVP · | 8 upvotes · 1.4M 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!

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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.

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Azure Monitor logo

Azure Monitor

54
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Full observability into your applications, infrastructure, and network
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PROS OF AZURE MONITOR
    Be the first to leave a pro
    CONS OF AZURE MONITOR
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      related Azure Monitor posts

      Hello People, I want suggestions about monitoring and alert tools to use with .NET application which will be hosted on Microsoft Azure. I have Azure Monitor,, Grafana, and Prometheus in my consideration. What would you suggest among these tools? If you have any other suggestions, please share the ideas. Thank you.

      See more

      Can I get metrics available through Prometheus into Azure Monitor, specifically into log analytics? (VM'S). I am running a couple of VM's inside Azure portal and I have my own private besu nodes running on them. I have my metrics set up inside the Prometheus but I was hoping to hook it up securely to Grafana but I tried everything and I can't. So the next thing is to see if can I get the metrics available through Prometheus into azure monitor, specifically into log analytics. The aim is to get the sync status, and the highest block number on each node, into log analytics so we can see what each is doing. That way we know, on a quick look, the status of each node and by extension, the condition of the private chain. What worries me is that although I have alerts if blocks stop being created or nodes lose peers we cannot see it quickly.

      Prometheus is one option to give us those stats. If we can get data from Prometheus into log analytics that would solve the problem.

      Can anyone help me with how I can go about it or any links? All I am seeing is for containers but I want for my VMs.

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      Dynatrace logo

      Dynatrace

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      Monitor, optimize, and scale every app, in any cloud
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      PROS OF DYNATRACE
      • 4
        Real User Monitoring
      • 4
        Automated RCA
      • 3
        Out-of-the-box distributed transaction tracing
      • 2
        Built on massive industry expertise (since 2005)
      • 2
        AI-powered platform
      • 2
        Extensible via SDK
      • 1
        Digital Experience
      • 1
        Easy setup
      • 1
        Accelerate software delivery
      • 1
        Infrastructure Monitoring
      • 1
        Applications & Microservices
      • 1
        Application Security
      • 1
        Built on API-first design principles
      • 1
        Automatic instrumentathird generation full stack Agents
      • 1
        Analytics vMotion events detection Discovery Performanc
      • 1
        Automation
      • 1
        Business Analytics
      CONS OF DYNATRACE
      • 0
        Application Security
      • 0
        Real User Monitoring
      • 0
        Infrastructure Monitoring
      • 0
        Applications & Microservices
      • 0
        AI-powered platform

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      Farzeem Diamond Jiwani
      Software Engineer at IVP · | 8 upvotes · 1.4M 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?

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      Splunk logo

      Splunk

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

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      Shared insights
      on
      SplunkSplunkDjangoDjango

      I am designing a Django application for my organization which will be used as an internal tool. The infra team said that I will not be having SSH access to the production server and I will have to log all my backend application messages to Splunk. I have no knowledge of Splunk so the following are the approaches I am considering: Approach 1: Create an hourly cron job that uploads the server log file to some Splunk storage for later analysis. - Is this possible? Approach 2: Is it possible just to stream the logs to some splunk endpoint? (If yes, I feel network usage and communication overhead will be a pain-point for my application)

      Is there any better or standard approach? Thanks in advance.

      See more
      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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      ELK logo

      ELK

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      The acronym for three open source projects: Elasticsearch, Logstash, and Kibana
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      PROS OF ELK
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        Open source
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        Can run locally
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        Good for startups with monetary limitations
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        External Network Goes Down You Aren't Without Logging
      • 1
        Easy to setup
      • 0
        Json log supprt
      • 0
        Live logging
      CONS OF ELK
      • 5
        Elastic Search is a resource hog
      • 3
        Logstash configuration is a pain
      • 1
        Bad for startups with personal limitations

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      Cyber Security Analyst · | 2 upvotes · 860.8K views

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      Serilog logo

      Serilog

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      A portable and structured logging framework to record diagnostic logs
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      PROS OF SERILOG
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        It's a logging library
      CONS OF SERILOG
      • 1
        They are two different things
      • 1
        You can't compare this to seq

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      Waqas Riaz
      Software Engineer at Center for Water Informatics & Technology · | 4 upvotes · 1M views

      Hi All, I am working upon developing a C# based windows service to work as a TCP server using Visual Studio 2019 as a development studio while using .NET Core 3.0.

      As its a background application, therefore, I am up on to add tracing and logging feature into it and want to write to 'text file' my trace and log outputs.

      By my research, I came upon 2 potential tracing and logging frameworks and on the verge to choose 1, therefore Serilog OR NLog.

      Anyone here who can help me out by his/her experience of 1 framework being better than other.?

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