Elasticsearch is an enterprise search tool from Elastic in Mountain View, California.
$16
per month
IBM Instana
Score 8.1 out of 10
N/A
Instana, an IBM company since the December 2020 acquisition, provides APM services for SOA, microservices, containerized applications and Kubernetes, and cloud native applications, as well as discovery and monitoring for IT assets.
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.
With enterprise IT assets in a multitude of ecosystems, cloud infrastructures and sometimes still left stuck in a legacy on prem architecture, IBM Instana makes it easy to get the right data to drive development and / or DevSecOps processes with tangible input from the target environment itself.
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.
Can monitor application(s) and system(s) with very large throughput of transactions by the second ( it gets everything !!!)
Provide strong drill down for your applications and will tell you where the points of failure of an application's is ( servers , network , Databases , etc you name it )
Very easy to set up and have it up and running when using the SaaS solution. There's an on premise solution which works just as well but requires more effort and preparation from an infrastructure point of view for your teams to implement.
Continuously improve their features and their agents auto-update and keep up. All while not interfering with your applications.
Let's you create your own dashboards and visualizations that can be tailored for different kind of users with the data collected.
Create your own events and smart alerts so you can know on the spot if something is happening or is likely to happen that needs addressing on your applications / systems
It's very difficult to create custom dashboards, only a handful of scenarios can be visualized to dashboards.
Extracting information from Instana to further analysis into excel for example is something that can be improved. Using an API to get data is very limiting.
Open telemetry features which allow to send application data to Instana is not working as documented.
Instana has been able to fulfill our all requirement and provide out of box solution for multiple component like AWS RDS Monitoring and real time alerting setup on basis of that. it is also easy to integrate with other open-source alerting and monitoring tools which makes it easier to incorporate into our 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.
IBM Instana totally alters our monitoring approach since it increases the stability of the system and simplifies the process of problem solving. And since it helps to lower the degree of alert exhaustion that we experience, it is a total game changer for us.
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.
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.
As a DevOps engineer, I've explored various Application Performance Monitoring (APM) tools, including New Relic for real-time insights, AppDynamics for code-level visibility, Dynatrace for AI-driven monitoring, Datadog for comprehensive observability, Splunk for log management, Stackify Retrace for error tracking, and Raygun for crash reporting. Each tool offers distinct features, and the choice depends on specific use cases, technology stacks, and organizational needs. Thorough evaluations, considering factors like ease of use, integration capabilities, and scalability, help in selecting the most suitable APM solution for effective application monitoring in a DevOps environment.
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.
