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AWS X-Ray vs Datadog: What are the differences?
AWS X-Ray, a native AWS service, focuses on providing insights into distributed applications running on the AWS infrastructure, while Datadog is a comprehensive third-party monitoring platform that supports multi-cloud environments and on-premises setups. Let's explore the key differences between them.
Integration and Platform Support: Datadog is a third-party monitoring and observability tool that can be used across different cloud platforms, including AWS, Azure, and Google Cloud. It supports numerous integrations with various technologies, making it versatile for different environments. On the other hand, AWS X-Ray is a native AWS service, tightly integrated with other AWS services, ensuring seamless monitoring and tracing within the AWS ecosystem.
Service Focus: AWS X-Ray specifically focuses on monitoring and tracing AWS resources and distributed applications hosted on the AWS infrastructure. It provides in-depth analytics and visualizations to identify performance bottlenecks and troubleshoot issues within AWS environments. Datadog, however, takes a broader approach and offers monitoring and observability features for both cloud and on-premises infrastructures, supporting multiple cloud providers and technologies.
Feature Set: AWS X-Ray mainly provides end-to-end request tracing, which allows you to trace requests as they flow through different AWS services. It helps in identifying latency, errors, and dependencies within the AWS environment. Datadog, on the other hand, offers a comprehensive set of monitoring tools including infrastructure monitoring, application performance monitoring (APM), log analytics, and synthetic monitoring. It provides a holistic view of your entire system, not limited to AWS services.
Ease of Use: AWS X-Ray is tightly integrated with AWS services, making it simple to enable and use within AWS environments. It automatically captures traces and integrates with other AWS monitoring services. Datadog, being a third-party tool, requires an additional setup process for integration with different cloud platforms and services. However, it offers a user-friendly interface and intuitive dashboards for seamless navigation and analysis of monitoring data.
Pricing Model: AWS X-Ray pricing is primarily based on the number of traces recorded and retrieved, with additional charges for data ingestion and data transfer. The pricing structure can be cost-effective for monitoring AWS resources. Datadog, on the other hand, follows a tiered pricing model based on the number of hosts and specific features used. It provides flexibility to choose the desired pricing plan based on your requirements and budget.
Alerting and Collaboration: Datadog offers advanced alerting capabilities, allowing you to set up custom alerts based on specific metrics and thresholds. It also provides collaboration features, enabling teams to collaborate on troubleshooting and monitoring tasks. AWS X-Ray, though lacking dedicated alerting capabilities, can integrate with AWS CloudWatch alarms for basic alerting. Collaboration features within AWS X-Ray are limited compared to the extensive collaboration options provided by Datadog.
In summary, AWS X-Ray is tailored for users deeply entrenched in the AWS ecosystem, offering integrated tracing and monitoring capabilities, while Datadog stands out as a versatile, cross-cloud solution with a broader scope, encompassing logs, metrics, and APM (Application Performance Monitoring).
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!
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 AWS X-Ray
Pros of Datadog
- Monitoring for many apps (databases, web servers, etc)137
- Easy setup107
- Powerful ui87
- Powerful integrations83
- Great value70
- Great visualization54
- Events + metrics = clarity46
- Custom metrics41
- Notifications41
- Flexibility39
- Free & paid plans19
- Great customer support16
- Makes my life easier15
- Adapts automatically as i scale up10
- Easy setup and plugins9
- Super easy and powerful8
- AWS support7
- In-context collaboration7
- Rich in features6
- Docker support5
- Cost4
- Source control and bug tracking4
- Automation tools4
- Cute logo4
- Monitor almost everything4
- Full visibility of applications4
- Simple, powerful, great for infra4
- Easy to Analyze4
- Best than others4
- Expensive3
- Best in the field3
- Free setup3
- Good for Startups3
- APM2
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Cons of AWS X-Ray
Cons of Datadog
- Expensive19
- No errors exception tracking4
- External Network Goes Down You Wont Be Logging2
- Complicated1
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