AppDynamics is an APM and Mobile APM program, with application mapping and predictive capabilities. These capacities enable automated remediation and code-level diagnostics in real time. It can be deployed on-premise or as a SaaS.
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Elasticsearch
Score 8.4 out of 10
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Elasticsearch is an enterprise search tool from Elastic in Mountain View, California.
Platforms for software as a service (SaaS) frequently cater to a large number of users with a variety of needs and usage patterns. Because AppDynamics offers multi-tenant monitoring capabilities to track performance across various customer environments, it is a good choice for SaaS platform monitoring. SaaS providers can maximize resource utilization, proactively detect and resolve performance issues, and provide a dependable and consistent user experience for their clients with AppDynamics.
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.
AppDynamics delves deeply into traceability and profiling at the code level. By identifying and refactoring any hidden performance hogs in our code, we can directly observe the performance improvements.
AppDynamics provides real-time dashboards and in-depth insights into each layer of the application stack, lifting the curtain on performance.
AppDynamics gives us the ability to proactively detect and resolve performance issues. We are able to keep things running smoothly for our users and stop outages.
We can monitor stability and performance prior to, during, and following releases with AppDynamics, which helps to minimize regression risks and facilitate smooth rollouts.
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.
Improving the clarity and comprehensiveness of the documentation could benefit users. Clearer documentation ensures that users can make the most of all the functionalities
Leverages AI and machine learning for intelligent insights, aiding in issue identification and prediction.
Competitive, with AI-driven features becoming increasingly common in APM solutions.
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.
AppDynamics has its own community site that includes forums and a knowledge base. On the forums, you can converse with other members of the community and ask technical questions as you have them. Though this forum isn’t filled with people there are active members for you to gain some valuable insights.
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.
It is distinguished from these programs because the platform provides visualizations of application processes, showing the interplay between various parts and services. Understanding the architecture of complicated apps and finding their weak spots is greatly aided by this.
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.
AppDynamics has played a pivotal role in optimizing our applications for a seamless user experience. The proactive monitoring and quick issue resolution have translated into improved user satisfaction and increased retention rates.
The initial cost and effort associated with implementing AppDynamics might be considered a negative impact, particularly for organizations with budget constraints. However, the long-term benefits have justified this initial investment.
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.
