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New Relic vs Splunk: What are the differences?
Introduction:
New Relic and Splunk are both popular tools used for monitoring and managing IT infrastructure and applications. While they have some similarities, there are key differences between the two.
Data Collection and Analysis: New Relic focuses on real-time application performance monitoring and offers easy-to-use, agent-based data collection. It provides deep insights into application performance metrics such as response times, error rates, and throughput. In contrast, Splunk is a log management and analytical tool that can ingest and analyze data from various sources, including logs, metrics, and events. It offers more flexibility in terms of data sources and provides powerful searching and reporting capabilities.
Scope and Use Case: New Relic is primarily designed for monitoring web applications and infrastructure performance. It helps developers and DevOps teams identify performance bottlenecks and optimize their web applications. Splunk, on the other hand, has a broader scope and can be used for different use cases such as IT operations management, security investigation, and business analytics. It allows users to correlate and analyze data from multiple sources to gain actionable insights.
User Interface and Visualization: New Relic offers a user-friendly and intuitive web-based interface with pre-built dashboards and visualizations. It provides out-of-the-box visibility into various performance metrics, making it easy to quickly identify and troubleshoot issues. Splunk's user interface is highly customizable and allows users to create their own dashboards and visualizations using search and reporting tools. It provides more flexibility in terms of data visualization but may require more configuration and expertise to get started.
Alerting and Notification: New Relic provides robust alerting capabilities, allowing users to set up threshold-based alerts and receive notifications via email, SMS, or chat tools. It offers integrations with popular incident management tools for seamless incident response. Splunk also offers alerting and notification features, but it goes beyond threshold-based alerts. Users can create complex alerting rules using search queries and correlation searches to detect anomalies or specific patterns in the data.
Integration with Third-party Tools: New Relic has a wide range of integrations with popular technologies and frameworks used in web application development. It provides plugins and APIs to easily integrate with tools such as Kubernetes, AWS, and Java frameworks. Splunk also offers a rich ecosystem of integrations and has extensive support for various data sources and logging formats. It provides connectors and add-ons for integrating with technologies like AWS, Azure, and popular security tools.
Scalability and Deployment Options: New Relic offers a cloud-based SaaS solution, which simplifies deployment and scalability. It provides automatic scaling and load balancing capabilities, allowing users to handle varying workloads. Splunk offers both on-premises and cloud-based deployment options. It provides more flexibility in terms of deployment models but requires users to manage and scale the infrastructure themselves.
In summary, New Relic focuses on real-time application performance monitoring with a user-friendly interface, while Splunk offers a broader scope with powerful data analysis and visualization capabilities. Their differences lie in the scope of use cases, data collection, analysis capabilities, and deployment options.
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?
Can't say anything to Sysdig. I clearly prefer Datadog as
- they provide plenty of easy to "switch-on" plugins for various technologies (incl. most of AWS)
- easy to code (python) agent plugins / api for own metrics
- brillant dashboarding / alarms with many customization options
- pricing is OK, there are cheaper options for specific use cases but if you want superior dashboarding / alarms I haven't seen a good competitor (despite your own Prometheus / Grafana / Kibana dog food)
IMHO NewRelic is "promising since years" ;) good ideas but bad integration between their products. Their Dashboard query language is really nice but lacks critical functions like multiple data sets or advanced calculations. Needless to say you get all of that with Datadog.
Need help setting up a monitoring / logging / alarm infrastructure? Send me a message!
Hi Medeti,
you are right. Building based on your stack something with open source is heavy lifting. A lot of people I know start with such a set-up, but quickly run into frustration as they need to dedicated their best people to build a monitoring which is doing the job in a professional way.
As you are microservice focussed and are looking for 'low implementation and maintenance effort', you might want to have a look at INSTANA, which was built with modern tool stacks in mind. https://www.instana.com/apm-for-microservices/
We have a public sand-box available if you just want to have a look at the product once and of course also a free-trial: https://www.instana.com/getting-started-with-apm/
Let me know if you need anything on top.
I have hands on production experience both with New Relic and Datadog. I personally prefer Datadog over NewRelic because of the UI, the Documentation and the overall user/developer experience.
NewRelic however, can do basically the same things as Datadog can, and some of the features like alerting have been present in NewRelic for longer than in Datadog. The cool thing about NewRelic is their last-summer-updated pricing: you no longer pay per host but after data you send towards New Relic. This can be a huge cost saver depending on your particular setup
I'd go for Datadog, but given you have lots of containers I would also make a cost calculation. If the price difference is significant and there's a budget constraint NewRelic might be the better choice.
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.
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
Pros of New Relic
- Easy setup415
- Really powerful344
- Awesome visualization245
- Ease of use194
- Great ui151
- Free tier106
- Great tool for insights80
- Heroku Integration66
- Market leader55
- Peace of mind49
- Push notifications21
- Email notifications20
- Heroku Add-on17
- Error Detection and Alerting16
- Multiple language support13
- SQL Analysis11
- Server Resources Monitoring11
- Transaction Tracing9
- Apdex Scores8
- Azure Add-on8
- Analysis of CPU, Disk, Memory, and Network7
- Detailed reports7
- Performance of External Services6
- Error Analysis6
- Application Availability Monitoring and Alerting6
- Application Response Times6
- Most Time Consuming Transactions5
- JVM Performance Analyzer (Java)5
- Browser Transaction Tracing4
- Top Database Operations4
- Easy to use4
- Application Map3
- Weekly Performance Email3
- Pagoda Box integration3
- Custom Dashboards3
- Easy to setup2
- Background Jobs Transaction Analysis2
- App Speed Index2
- Super Expensive1
- Team Collaboration Tools1
- Metric Data Retention1
- Metric Data Resolution1
- Worst Transactions by User Dissatisfaction1
- Real User Monitoring Overview1
- Real User Monitoring Analysis and Breakdown1
- Time Comparisons1
- Access to Performance Data API1
- Incident Detection and Alerting1
- Best of the best, what more can you ask for1
- Best monitoring on the market1
- Rails integration1
- Free1
- Proce0
- Price0
- Exceptions0
- Cost0
Pros of Splunk
- API for searching logs, running reports3
- Alert system based on custom query results3
- Splunk language supports string, date manip, math, etc2
- Dashboarding on any log contents2
- Custom log parsing as well as automatic parsing2
- Query engine supports joining, aggregation, stats, etc2
- Rich GUI for searching live logs2
- Ability to style search results into reports2
- Granular scheduling and time window support1
- Query any log as key-value pairs1
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Cons of New Relic
- Pricing model doesn't suit microservices20
- UI isn't great10
- Expensive7
- Visualizations aren't very helpful7
- Hard to understand why things in your app are breaking5
Cons of Splunk
- Splunk query language rich so lots to learn1
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