Datadog vs. Splunk On-Call

As per my experience, Datadog is best suited for complex, cloud-native environments where unified observability is critical, as it integrates seamlessly with AWS and Azure. Moreover, it provides deep visibility into latency and error rates. Datadog pricing is less appropriate for Startups with a tight budget and for organizations needing advanced incident management.

Incentivized

I recommend Splunk on-call is more suited where there are high incident queues; multiple teams need to be involved in handling a P1 severity issue. Multiple levels of escalation are needed environment where automated action is required. I recommend the solution for large-scale & medium-scale business units. For small-scale business units, I see the functional value is less.

Incentivized

• The thing which Datadog does really well, one of them are its broad range of services integrations and features which makes it one step observability solution for all. We can monitor all types of our application, infrastructure, hosts, databases etc with Datadog.
• Its custom dashboard feature which helps us to visualize the data in a better way . It supports different types of charts through those charts we can create our dashboard more attractive.
• Its AI powered alerting capability though that we can easily identify the root cause and also it has a low noise alerting capability which means it correlated the similar type of issues.

Incentivized

• Easily assign work/tickets between multiple users
• Supports a wide variety of software integrations
• Easy to manage scheduling tool
• As part of the Splunk toolset, provides detailed levels of data analysis at our engineers fingertips

Incentivized

• In my experience, .NET Tracing Agent caused severe and untraceable performance issues
• In my opinion, usage and billing structures were opaque and surprising
• In my experience, documentation was incomplete, contradicting or sometimes completely wrong, even for common infrastructure (AWS Fargate)
• I feel support was unhelpful at times, and bounced us back and forth to other teams
• In my opinion, multiple methods of sample rate control were ineffective, adding to excessive usage and cost

Incentivized

• The user interface can be furthe improved
• Licensing needs to be simplified and packaged as a bundle with other Splunk product like Enterprise Security
• Customer outreach can be further enhanced

Incentivized

Definitely will not revisit after our issues and, in my opinion, poor support.

Incentivized

It was a good solution with a good comprimise prize/features for our use cases

Incentivized

There are so many features that it can be hard to figure out where you need to go for your own use case. For example, RUM monitoring us buried in a "Digital Experience" sidebar setting when this is one of our key use cases that I sometimes struggle to find in the application. It appears that ECS + Fargate monitoring was recently released which is great because we had to build a lambda reporting solution for ephemeral task monitoring. But this new feature was never on my radar until I starting clicking around the application.

Incentivized

Not a lot of love given to VO since the acquisition by Splunk from my POV

Incentivized

The support team usually gets it right. We did have a rather complicate issue setting up monitoring on a domain controller. However, they are usually responsive and helpful over chat. The downside would be I don’t think they have any phone support. If that is important to you this might not be a good fit.

Incentivized

VictorOps support has proven excellent for us. Because it is such a widely used tool, there is a lot of documentation on usage, and a large community of users to lean on. Also, many engineers have had experience working with VictorOps already, and the tool is so easy to setup / manage that much support isn't really necessary.

Incentivized

Documentation was difficult to work through, rollout was catastrophic (completely outage)

Incentivized

It was a good solution with a good comprimise prize/features for our use cases

Incentivized

Our logs are very important, and Datadog manages them exceptionally well. We frequently use Datadog services for our investigations. Use case: Monitor your apps, infrastructure, APIs, and user experience.


Key features:


Logs, metrics, and APM (Application Performance Monitoring)


Real-time alerting and dashboards


Supports Kubernetes, AWS, GCP, and other integrations


RUM (Real User Monitoring) and Synthetics





✅ Best for backend, server, and distributed systems monitoring.

Incentivized

Splunk On-Call integrates better with our Splunk Cybersecurity and Reporting products due to the same family tree of the same eco system. We were previously using built-in on-call from individual applications and while adequate, they were difficult to manage and support SLA varied greatly across different applications. In addition we also used xMatters which did not integrate well with SAP products nor Citrix products so we were still using more than a single on-call product which was solved by implementing Splunk On-Call

Incentivized

• Saved us (time & money) from developing our own monitoring utilities that would pale in comparison
• Alerts allow us to remedy issues before our customers even know about them
• Tracking resource usage over time allows us to better plan for future needs, before it becomes a pain-point.

Incentivized

• It runs our on call rotation so it makes it easy for us.
• It integrates with Slack so it makes it easy for us to manage through Slack.

Incentivized