Catchpoint vs. Elasticsearch

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

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.

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

• 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.

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

• 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

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

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

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

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.

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

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.

Incentivized

very easy to implement as the product is user-friendly

Incentivized

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

Incentivized

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.

Incentivized

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.

Incentivized

• The ROI has been very good with this product, we have seen multiple folds of time-saving by using this tool and preempting any risk associated with non-performant times of our server, hence increasing the team's capability to respond to certain downtime scenarios and the level of action that needs to be taken.
• Catchpoint’s observability solution makes it easier to have global visibility of our website's performance and to fix issues quicker
• I don't have any negatives, every good product comes with a cost, that is the fact but the Catchpoint tool has ultimately improved our ROI much beyond the changes that we pay

Incentivized

• 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.

Incentivized