

Find out in this report how the two AI Observability solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
Previously we had thirteen contractors doing the monitoring for us, which is now reduced to only five.
Datadog has delivered more than its value through reduced downtime, faster recovery, and infrastructure optimization.
We have also seen fewer escalations for minor issues because alerts help us catch problems earlier, which indirectly reduces downtime and improves overall efficiency.
Time saved is a relevant metric; it used to take us a week, but now it takes us only a day.
I have seen a return on investment with Kong Konnect, as it helps manage security very well, allows for faster API deployments saving developer time, and reduces salary costs with better uptime and minimal downtime, thus preventing potential business loss.
Our debugging time during regression cycles reduced roughly by 25% to 30%, mainly because the gateway layer helped us quickly identify whether issues were coming from authentication policies, rate limiting, throttling, or the backend services.
When I have additional questions, the ticket is updated with actual recommendations or suggestions pointing me in the correct direction.
Overall, the entire Datadog comprehensive experience of support, onboarding, getting everything in there, and having a good line of feedback has been exceptional.
I've had a couple instances where I reached out to Datadog's support team, and they have been really super helpful and very kind, even reaching back out after resolving my issues to check if everything's going well.
Technical support from Proofpoint was absolutely excellent.
When I raise an incident or a support ticket, it gets answered in four hours.
They offer twenty-four-hour support with SLA-based response times.
Datadog's scalability has been great as it has been able to grow with our needs.
Since it is a SaaS platform, we did not have to worry about backend scaling.
We have not faced any major performance issues from the platform side; it handles increased metrics and monitoring loads smoothly.
It supports auto-scaling of gateway nodes, especially in cloud setups, which helps it adjust dynamically based on traffic spikes without manual intervention.
The platform is fully scalable, providing various ways to manage data planes or runtimes.
Kong Konnect's scalability is very high, handles growth well, and since it is a stateless gateway, it scales easily in Kubernetes using horizontal scaling.
Metrics collection and alerting have been consistent in day-to-day use.
Datadog is very stable, as there hasn't been any downtime or issues since I've been here, and it's always on time.
Datadog seems stable in my experience without any downtime or reliability issues.
Most of the time, the gateway handled routing and policies reliably, even during heavy regression cycles and heavy customer throughput.
It was very fast, and we did not experience any interruptions.
Kong Konnect is very stable with no issues regarding reliability in my experience.
It would be great to see stronger AI-driven anomaly detection and predictive analytics to help identify potential issues before they impact performance.
We want to be able to customize the cost part, and we would appreciate more granular access control.
Having more transparent and granular cost control features would make it easier to manage usage.
A bit more granular and easily accessible logs would make troubleshooting faster.
The licensing model could be simplified, especially in how they charge and track usage.
When comparing documentation, Kong's documentation is not on par with Google, Amazon, or other cloud providers.
The setup cost for Datadog is more than $100.
Pricing is mainly based on data ingestion, such as logs, metrics, and traces, and it can increase quickly if everything is enabled by default.
Everybody wants the agent installed, but we only have so many dollars to spread across, so it's been difficult for me to prioritize who will benefit from Datadog at this time.
Pricing was the issue as it becomes very expensive due to the nature of local circumstances.
I wouldn't say that the setup cost is much more compared to using any other product.
While the pricing model isn't very clear on how usage is tracked, the initial cost and setup for using Kong Konnect are reasonable.
Our architecture is written in several languages, and one area where Datadog particularly shines is in providing first-class support for a multitude of programming languages.
Having all that associated analytics helps me in troubleshooting by not having to bounce around to other tools, which saves me a lot of time.
Datadog was able to find the alerts and trigger to notify our team in a very prompt manner before it got worse, allowing us to promptly adjust and remediate the situation in time.
The documentation is excellent, and it includes a developer portal, which helps create a common distribution channel for APIs within and outside the enterprise.
When I mention scalability, it means that when we experience peak traffic, Kong made it easy for us to scale and spawn new machines.
The security features of Kong Konnect have helped my team mainly by allowing us to use auth and JWT for applications needing external identity provider authentications, such as LDAP or other authentication providers that need to be connected to back-end applications.
| Product | Mindshare (%) |
|---|---|
| Datadog | 6.2% |
| Kong Konnect | 0.5% |
| Other | 93.3% |

| Company Size | Count |
|---|---|
| Small Business | 82 |
| Midsize Enterprise | 48 |
| Large Enterprise | 100 |
| Company Size | Count |
|---|---|
| Small Business | 5 |
| Midsize Enterprise | 2 |
| Large Enterprise | 2 |
Datadog integrates extensive monitoring solutions with features like customizable dashboards and real-time alerting, supporting efficient system management. Its seamless integration capabilities with tools like AWS and Slack make it a critical part of cloud infrastructure monitoring.
Datadog offers centralized logging and monitoring, making troubleshooting fast and efficient. It facilitates performance tracking in cloud environments such as AWS and Azure, utilizing tools like EC2 and APM for service management. Custom metrics and alerts improve the ability to respond to issues swiftly, while real-time tools enhance system responsiveness. However, users express the need for improved query performance, a more intuitive UI, and increased integration capabilities. Concerns about the pricing model's complexity have led to calls for greater transparency and control, and additional advanced customization options are sought. Datadog's implementation requires attention to these aspects, with enhanced documentation and onboarding recommended to reduce the learning curve.
What are Datadog's Key Features?In industries like finance and technology, Datadog is implemented for its monitoring capabilities across cloud architectures. Its ability to aggregate logs and provide a unified view enhances reliability in environments demanding high performance. By leveraging real-time insights and integration with platforms like AWS and Azure, organizations in these sectors efficiently manage their cloud infrastructures, ensuring optimal performance and proactive issue resolution.
Kong Konnect facilitates efficient management and integration of APIs, providing a streamlined experience for developers to manage their services with high scalability.
Kong Konnect is a comprehensive platform tailored for API development and management. It offers an intuitive interface that simplifies the process of connecting, managing, and securing APIs. Organizations benefit from its scalable architecture, ensuring it meets diverse operational demands and optimizes service delivery, supporting a robust API ecosystem that aligns with modern development practices.
What are the key features of Kong Konnect?In tech industries, Kong Konnect is often implemented to advance cloud-native applications by enhancing API connectivity and security. Financial services utilize it to ensure compliance and secure data sharing. Telecommunications deploy it to handle high data throughput efficiently.
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