Catchpoint vs. Elasticsearch

I like the synthetic test feature it has from the edge which mimics the real user - that for me is one of the best features. The certificate expiration, the API monitoring, the slowness breakdown to show where the slowdown happens, and more.

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Elasticsearch is a really scalable solution that can fit a lot of needs, but the bigger and/or those needs become, the more understanding & infrastructure you will need for your instance to be running correctly. Elasticsearch is not problem-free - you can get yourself in a lot of trouble if you are not following good practices and/or if are not managing the cluster correctly. Licensing is a big decision point here as Elasticsearch is a middleware component - be sure to read the licensing agreement of the version you want to try before you commit to it. Same goes for long-term support - be sure to keep yourself in the know for this aspect you may end up stuck with an unpatched version for years.

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• 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.

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• As I mentioned before, Elasticsearch's flexible data model is unparalleled. You can nest fields as deeply as you want, have as many fields as you want, but whatever you want in those fields (as long as it stays the same type), and all of it will be searchable and you don't need to even declare a schema beforehand!
• Elastic, the company behind Elasticsearch, is super strong financially and they have a great team of devs and product managers working on Elasticsearch. When I first started using ES 3 years ago, I was 90% impressed and knew it would be a good fit. 3 years later, I am 200% impressed and blown away by how far it has come and gotten even better. If there are features that are missing or you don't think it's fast enough right now, I bet it'll be suitable next year because the team behind it is so dang fast!
• Elasticsearch is really, really stable. It takes a lot to bring down a cluster. It's self-balancing algorithms, leader-election system, self-healing properties are state of the art. We've never seen network failures or hard-drive corruption or CPU bugs bring down an ES cluster.

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• Missing Functionality: For our organisation, we use multiple observability tools and what we miss in Catchpoint is its ability to display a list of muted monitors in the dashboard. This was a business requirement for our company where the business wanted to know at any given point of time, a list of monitors that were muted during an outage or a scheduled maintenance. This feature was unavailable in Catchpoint, however, we hope to see some enhancements in the future.

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• Joining data requires duplicate de-normalized documents that make parent child relationships. It is hard and requires a lot of synchronizations
• Tracking errors in the data in the logs can be hard, and sometimes recurring errors blow up the error logs
• Schema changes require complete reindexing of an index

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The Catchpoint tool has now become an integral part of our DevOps toolkit due to its extensive range of capabilities, including application performance monitoring, network health tracking, DNS visibility, and edge performance analysis. Its seamless integration with our existing monitoring infrastructure has significantly enhanced our ability to detect potential issues proactively, analyze root causes in real time, and resolve incidents much faster, ultimately improving overall system reliability and user experience.

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We're pretty heavily invested in ElasticSearch at this point, and there aren't any obvious negatives that would make us reconsider this decision.

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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.

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To get started with Elasticsearch, you don't have to get very involved in configuring what really is an incredibly complex system under the hood. You simply install the package, run the service, and you're immediately able to begin using it. You don't need to learn any sort of query language to add data to Elasticsearch or perform some basic searching. If you're used to any sort of RESTful API, getting started with Elasticsearch is a breeze. If you've never interacted with a RESTful API directly, the journey may be a little more bumpy. Overall, though, it's incredibly simple to use for what it's doing under the covers.

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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.

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We've only used it as an opensource tooling. We did not purchase any additional support to roll out the elasticsearch software. When rolling out the application on our platform we've used the documentation which was available online. During our test phases we did not experience any bugs or issues so we did not rely on support at all.

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very easy to implement as the product is user-friendly

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Do not mix data and master roles. Dedicate at least 3 nodes just for Master

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Smart Bear Foglight Dynatrace CEM Catchpoint: I have used many synthetic monitoring products. Honestly, there are no big differences in features among all the products listed above or that I have used before. Probably, price and support might play big roles in selecting the products. I do not know the prices of these products.

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As far as we are concerned, Elasticsearch is the gold standard and we have barely evaluated any alternatives. You could consider it an alternative to a relational or NoSQL database, so in cases where those suffice, you don't need Elasticsearch. But if you want powerful text-based search capabilities across large data sets, Elasticsearch is the way to go.

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• Catchpoint is not the only monitoring tool we use for our web properties. The test alerts raised by Catchpoint serves as a confirmation of possible outages/problems with an application. This has helped to reduce false-positive alerts thus improving the response of the operations team; they don't have spend time chasing ghosts
• The unlimited scheduled tests we can run on the enterprise nodes has been a very cost effective solution compared to similar web monitoring tools
• The ability to quickly dive into the test result details help to get to the root cause of a test failure quickly

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• We have had great luck with implementing Elasticsearch for our search and analytics use cases.
• While the operational burden is not minimal, operating a cluster of servers, using a custom query language, writing Elasticsearch-specific bulk insert code, the performance and the relative operational ease of Elasticsearch are unparalleled.
• We've easily saved hundreds of thousands of dollars implementing Elasticsearch vs. RDBMS vs. other no-SQL solutions for our specific set of problems.

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Independently Invited by TrustRadius

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info