Catchpoint vs. Splunk Observability Cloud

Proactive Website and API performance testing, Synthetic monitoring, and third-party integration are where Catchpoint is best suited. Catchpoint is less appropriate in Deep Application Performance monitoring, debugging complex user journeys in real-time, Small businesses, and Mobile app performance monitoring. These are the scenarios where I find Catchpoint is well-suited and scenarios where it is less appropriate.

Incentivized

The query language is relatively easy and flexible when looking into an application's problems. These queries can then be used for alerts, reports, and dashboards. I believe Splunk is a platform that can help a system grow into its proactive application management, using incidents to add insights as needed without trying to work out every scenario in advance.

Incentivized

• Catchpoint Synthetics: We create our synthetic monitoring using catchpoint. Creating the synthetics monitors are easy and requires basic knowledge on selenium and javascript. It allows you to run the test from external(backbone) and internal enterprise nodes. The screenshot and filmstrip feature is an add-on along with various customisations. Once created, It provides a detailed insight of each request that is involved in the application flow which helps us in addressing the issue at the request level.
• Catchpoint API Test: This is another kind of test which we have explored in our organisation. This has helped us to maintain the health check of our APIs and also we have utilised it for a variety of our use cases.
• Catchpoint Dashboard: This is our one-stop shop for all our monitors. It has multiple widgets that displays various application performance metrics. We use this feature immensely and it is of great value to the business.
• Catchpoint UI: It is very user friendly and with basic introduction anyone can just get started with it.

Incentivized

• The first one is its Kubernetes container monitoring.
• I really like this features because as we know how much K8s is vast and to manually monitor each part of the Kubernetes it takes so much time but Splunk Observability Cloud makes it easier. And even once we integrate K8s with Splunk Observability Cloud it gives us some prebuilt dashboards which gives holistic view of our Cluster and its nodes, pods, etc.
• The dashbaord feature of Splunk Observability Cloud, it gives us full flexibility to customize our dashboard with a wide range of predefined chart types.
• Now it also supports OTEL, which is a plus point for observability. As now everyone is moving towards Otel and in current market there are only few tools who supports OTEL based integrations, Splunk Observability Cloud is one out of them.

Incentivized

• The ability to monitor the Catchpoint nodes with the ability to setup a take a recovery action based on specific criteria
• The ability to tell us when we are at X% capacity so that we better plan or budget for increasing the "capacity" of the Catchpoint nodes before we get to an overloaded state. The capacity utilization graph is not a reliable indicator for this metric. How can the capacity utilization rate get above 100%, it does not make sense

Incentivized

• An indicator for errors on the navigations pane so that we don't have to go through each tab.
• As we go more and more cloud maybe you guys can implement a pay-as-you-use strategy so that small companies using it not frequently can also afford it.
• That's it can't think of any and it wont let me skip to next question. Thanks

Incentivized

we are heavily dependent catchpoint system for the following functions * Detect end-user availability/performance-related problems * Ensures
service level objectives (SLO) are met, that prevents service level
agreement (SLA) breaches * Identify and understand the cause of any
network connectivity or application level issue * Improves the
availability and response time service levels

Incentivized

Good: Stable system with low error rate Easy to use for simple use cases Bad: UI is not very clear for complex usage Mobile view (when logged in from phone) is bad No library for .net

Incentivized

It's hard to find the functionalities that I am looking for in the application. Even if I did something in the past, after a time I have to re-learn again where the functionalities are. This is a powerful tool, but not user-friendly. Texts in the buttons and menus are not always meaningful or easily comprehensible.

Incentivized

When there is an issue, it’s a win if one can easily identify the root cause. To do the same, it should allow the user to dig deep with multiple data points and compare the data and identify the anomaly. In this use case, it’s good to drive from Splunk 011y.

Incentivized

The customer support is fantastic as they keep you updated and follow up even though we may not even follow up. Make sure they send a communication so that we remain updated. They value engineers who will get on a call with you to understand any requirement we have on any test, and they bring in the best developers on call.

Incentivized

Splunk support is very quick and efficient. Pre-sale specialists are very skilled and available.

Incentivized

very easy to implement as the product is user-friendly

Incentivized

Follow a training before starting.

Incentivized

Datadog is good, but more expensive. New Relic is good but does not provide the same features as Catchpoint does. Checkly is good, but Catchpoint offers different frameworks to create synthetic tests, which is preferable to my engineering team.

Incentivized

We initially chose Splunk Observability Cloud because it promised full-stack visibility and tighter integration. The other tools didn't offer this as part of the core package. Their analytics and real-time dashboards looked strong during the demo but it turned out to a lot heavier and more complex than expected. If I had to decide again, I’d probably go with something more streamlined and easier to manage.

Incentivized

• 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.

Incentivized

• Significantly reduced the MTTR (Mean Time To Recovery), which in turn has improved the end-user experience tremendously.
• Meets compliance requirements of security policies, audit, regulation, and forensics.
• Helps us to track/manage the resource usage on our cloud instances which has a direct implication on the recurring cost.

Incentivized