Catchpoint for Robust Monitoring
October 17, 2025
Catchpoint for Robust Monitoring
Score 8 out of 10
Vetted Review
Verified User
Overall Satisfaction with Catchpoint
Catchpoint is used for Synthetic monitoring of internal IT resources from various internal office locations and also for Product observability initiative from various last mile connectivity networks and cloud locations in accessing and using the cloud software products to measure the customer impact, connectivity challenges and product usage challenges. Real User monitoring is out of scope currently and IPM is under deep dive evaluation.
Pros
- Our standard operating material documents Catchpoint’s breadth on HTTP/Browser, API, Streaming, DNS, FTP, TCP, SMTP, Ping, Traceroute, SSH with content validation and custom widgets/dashboards. This gives SREs and L0/L1 a single place to validate both page flows and the underlying network/application protocols.
- Product runbooks use Catchpoint to validate critical steps (for ex, login, overview dashboard, unit dashboards) and to detect DNS issues that break those journeys. so we catch experience regressions even when the backend looks healthy.
- We’ve standardized Catchpoint alert categories/templates with ITSM so L0 includes the right analysis in handoffs. This tightened “first message, best message” during incidents.
- Our operating procedures use Catchpoint for alwayson availability checks with email notifications and multi‑location verification when a site is down. This is useful for unambiguous “is it up/where is it failing” signals.
Cons
- Catchpoint excels at realtime monitoring but offers only basic trend analysis. We noted that historical insights and advanced anomaly detection are weak compared to other observability platforms which provide richer forecasting and correlation features. This limits proactive problem prevention and long horizon of capacity planning.
- Catchpoint does not provide deep application level visibility like code level tracing, log ingestion, or distributed tracing. It is inability to correlate API and frontend failures with backend logs or infrastructure metrics is a challenge. This forces teams to rely on other tools for full stack troubleshooting.
- Catchpoint lacks AI powered anomaly detection and automated remediation. This gap means more manual triage and slower MTTR during incidents. Internal roadmap discussions flagged this as a strategic limitation for predictive observability.
- Catchpoint points based licensing for public hosted nodes is complicated and unpredictable in points required.
- Catchpoint lacks AI powered anomaly detection and automated remediation. This gap means more manual triage and slower MTTR during incidents.
- The advanced 360 degree blackbox monitoring is enabling us to monitor the APIs, UI and proactively gain insights into the application behavior and performance before customer is impacted.
We had been running the Catchpoint since long and was able to mature over the years. It took a long cycle to mature the platform.
Catchpoint is instrumental in helping diverse tech stack across hundreds of regions of the organization in cost efficient way.
Do you think Catchpoint delivers good value for the price?
Yes
Are you happy with Catchpoint's feature set?
Yes
Did Catchpoint live up to sales and marketing promises?
I wasn't involved with the selection/purchase process
Did implementation of Catchpoint go as expected?
I wasn't involved with the implementation phase
Would you buy Catchpoint again?
Yes
Comments
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