Splunk AppDynamics and IBM Turbonomic are competitive products in the IT infrastructure management space, focusing on application performance monitoring and resource optimization, respectively. AppDynamics is superior in application insights with its deep dive analyses and transaction tracking, whereas Turbonomic excels at automating resource allocation, making it ideal for optimizing IT infrastructure.
Features: AppDynamics offers code-level deep dive analysis, JVM memory monitoring, and transaction tracking, providing detailed application performance insights. These features are crucial for diagnosing complex environments. Turbonomic specializes in resource allocation, automation, and capacity planning, with features focused on improving IT infrastructure efficiency.
Room for Improvement: AppDynamics users cite challenges with initial setup due to high pricing and a complex licensing model. Enhancements are needed in network monitoring and agent upgrade simplification. Turbonomic users suggest improving UI usability and better integration with emerging technologies like AI and machine learning. It also needs to handle large environments more effectively in reporting and planning.
Ease of Deployment and Customer Service: AppDynamics provides flexible SaaS deployment but has a complex setup process. It receives praise for excellent customer support. Turbonomic operates primarily on-premises with straightforward deployment and is recognized for outstanding post-sales support, aiding users in overcoming initial setup hurdles.
Pricing and ROI: AppDynamics is noted for high pricing due to its detailed monitoring capabilities, justifying the cost for large enterprises. Turbonomic offers competitive pricing appealing to those focused on infrastructure optimization. It provides cost savings through efficiency improvements. AppDynamics users find value in enhanced performance, while Turbonomic users benefit from resource allocation savings.
According to errors, exceptions, and code-level details related to their application performance on a daily basis, the application development team tries to help with Splunk AppDynamics to reduce errors and exceptions, which helps the end users get application availability and feel more confident.
To understand the magnitude of it, when the company asked to replace Splunk AppDynamics with another tool, I indicated that for the proposed tool, we would need five people to do the analysis that Splunk AppDynamics enables me to do.
It's very hard to find ROI because we are currently focused only on the on-premises applications.
AppDynamics is much more helpful.
We got a contact, an account manager, to work directly with for technical support.
They help us resolve any issues raised by our team relating to operations, application instrumentation, or any other issues.
We have reached maximum capacity in our tier, and extending capacity has not been cost-effective from Splunk's perspective.
I would rate the scalability of Splunk AppDynamics as a nine out of ten.
I did not find any Docker solution available with it, and a separate instance has to be installed.
It is necessary to conduct appropriate testing before deploying them in production to prevent potential outages.
There are no issues or bugs with the 20.4 version; it is very stable with no functionality or operational issues.
I can rate it nine out of ten.
Splunk AppDynamics does not support the complete MELT framework, which includes metrics, events, logging, and tracing for the entire stack.
If AppDynamics could develop a means to monitor without an agent, it could significantly improve application performance and reduce potential problems.
A good integration with Splunk would be very interesting, as Splunk is a good product for logs, and that part is currently missing in Splunk AppDynamics.
Customers have to pay a premium price, however, they receive considerable value from the product.
All these solutions at the moment are cheap, but it is like paying for insurance; you pay insurance to avoid major damage.
We find its pricing reasonable and competitive.
We have multiple tools, but end users prefer to use Splunk AppDynamics because their portal navigation is very simple and clear.
The feature that I appreciate in AppDynamics Browser Real-User Monitoring is the intuitive and user-friendly dynamic mapping it creates for workflows.
What I like the most about Splunk AppDynamics is the end-to-end observability for the application, along with traces.
IBM Turbonomic offers automation, planning, and right-sizing recommendations to streamline resource management, improve efficiencies, and optimize costs across virtualized environments and cloud platforms.
IBM Turbonomic is valued for its capability to optimize resource allocation and monitor virtual environments efficiently. It facilitates automated decision-making in VM sizing, load balancing, and cost optimization for both on-premises and cloud deployments. Users can leverage insights for workload placement, ensure peak performance assurance, and effectively right-size across VMware and Azure. The ongoing transition to HTML5 aims to improve visual and navigational ease, while expanded reporting features are anticipated. Opportunities for improved training, documentation, and integrations enhance platform usability and functionality.
What Are the Key Features?In finance, IBM Turbonomic aids in maintaining platform efficiency during market fluctuations. Healthcare organizations leverage its capability for resource optimization during high-demand periods to enhance patient care support. Retailers use it for planning in peak seasons, ensuring resources align with fluctuating demand to maintain performance continuity.
Splunk AppDynamics enhances application performance monitoring with advanced diagnostics and real-time insights, offering seamless end-to-end transaction tracking and infrastructure visibility.
AppDynamics provides critical tools for businesses to analyze application behavior and performance. Through innovative features like transaction snapshot analysis and adaptable dashboards, users can quickly identify and address issues, ensuring high levels of system uptime and efficiency. It is designed to support complex environments including Kubernetes and AWS, enhancing user experience by detecting performance issues early. Despite needing improvements in network monitoring and integration, it remains a robust option for tracking application health.
What are the key features of AppDynamics?In industries like financial services and e-commerce, AppDynamics facilitates performance tracking across distributed systems, optimizing infrastructure to meet consumer demands. It excels in environments needing precise transaction monitoring and is pivotal in delivering high value and satisfaction.
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