

Splunk AppDynamics and Gigamon Deep Observability Pipeline both operate in IT infrastructure monitoring, focusing on different strengths. AppDynamics holds an advantage with comprehensive transaction insights ensuring swift issue resolution.
Features: AppDynamics offers automatic incident detection with transaction snapshots, dynamic baselining that provides alerts without needing additional configuration, and advanced transaction snapshots that help identify performance bottlenecks. Gigamon provides valuable network traffic filtering, deduplication, and powerful packet capture features, helping in efficient network analysis.
Room for Improvement: AppDynamics could improve its dashboard configuration and better support asynchronous calls. Gigamon needs enhancements in cloud network monitoring capabilities and scalability due to challenges faced with SPAN traffic, requiring better performance optimization.
Ease of Deployment and Customer Service: AppDynamics offers versatile deployment options including Public, Hybrid, and Private Clouds, with strong customer service despite needing faster support resolutions. Gigamon primarily serves on-premises and hybrid models, with onboarding sessions essential for maximizing its utility.
Pricing and ROI: AppDynamics is often seen as premium-priced with a complex licensing model but promises a high ROI by rapidly addressing application issues, especially valuable in high-stakes sectors. Gigamon is also considered expensive, with ROI focusing more on network optimization than application performance, highlighting different areas for value return.
Overall, as a production gatekeeper, we achieve at least 50% efficiency immediately, with potential savings ranging from 60 to 70% as well, reinforcing why it is a popular tool in the banking industry.
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.
The technical support by Gigamon Deep Observability Pipeline is good because it has a local architect in my area.
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 assess how Splunk AppDynamics scales with the growing needs of my organization as good, since we are growing and adding more servers.
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.
Splunk AppDynamics is superior to any alternative, including Dynatrace.
Splunk AppDynamics does not support the complete MELT framework, which includes metrics, events, logging, and tracing for the entire stack.
AI could provide more insights for annual or half-yearly reports and forecast future changes in the asset landscape.
Functionality-wise, I would like to see more cognitive solutions in Splunk AppDynamics, ideally with a single agent that can implement policies and provide predictive insights regarding application performance degradation during peak times.
We completed a three-year deal for Splunk and for AppDynamics, which costs millions of dollars.
Overall, I consider Splunk AppDynamics an expensive product; it's very expensive.
The resource team finds the best prices, ensuring that Splunk AppDynamics is an acceptable option for the end user.
The Pipeline's Comprehensive Insights into data flows have helped improve operational efficiency and security.
We have multiple tools, but end users prefer to use Splunk AppDynamics because their portal navigation is very simple and clear.
The real user monitoring and digital experience monitoring effectively track actual user experience with the applications, including page loading, interaction time for both desktop and mobile applications.
This is the best feature because, although you can't monitor a whole application at once, Splunk AppDynamics gives you the option that if there is any failure—simple failure regarding anything set up as per our use cases—you will get an alert.
| Product | Mindshare (%) |
|---|---|
| Splunk AppDynamics | 4.2% |
| Gigamon Deep Observability Pipeline | 0.6% |
| Other | 95.2% |

| Company Size | Count |
|---|---|
| Small Business | 3 |
| Midsize Enterprise | 1 |
| Large Enterprise | 5 |
| Company Size | Count |
|---|---|
| Small Business | 58 |
| Midsize Enterprise | 37 |
| Large Enterprise | 202 |
Gigamon Deep Observability Pipeline boosts network visibility and performance through features like NetFlow and deduplication, facilitating data flow insights and improved security. It supports traffic monitoring and management across various infrastructures.
Gigamon Deep Observability Pipeline enhances network management by offering features such as NetFlow, deduplication, header stripping, and packet filtering. These capabilities are instrumental in optimizing performance, offering users stability and improved encryption processes. Despite its robust hardware capabilities, it requires enhancements in security, filtering, and delivery time for hardware. Users note challenges with monitoring cloud networks and insufficient cluster capacity. There is also a call for improved interface design and internal traffic flow visualization.
What are the essential features of Gigamon Deep Observability Pipeline?Gigamon Deep Observability Pipeline finds application across industries for network visibility and management. It is used extensively for traffic monitoring, SSL inspection, mobile network oversight, and data center operations. Organizations leverage its capabilities to address network issues, enhance security, and streamline performance monitoring processes. Its ability to group traffic aids significantly in problem-solving and SSL detection.
Splunk AppDynamics is a comprehensive performance monitoring tool providing end-to-end transaction tracking, real-time monitoring, and a user-friendly interface. With AI-powered features, it enhances operational efficiency and resilience by offering insights into user interactions and infrastructure issues.
Splunk AppDynamics excels in monitoring applications and infrastructure performance, offering extensive support across environments like AWS and cloud. It aids in application performance monitoring, end-user experience, database analysis, and proactive incident detection. Supporting Java, .NET, and other technologies, it provides real-time insights into application health, resource utilization, and transaction tracking, ensuring reliable user experiences. Challenges remain in UI complexity, agent-based architecture, integration with diverse environments, and documentation clarity. Its licensing model is costly, and customer support may be slow. Performance concerns exist in historical data granularity and network visibility.
What features make Splunk AppDynamics stand out?
What benefits and ROI can users expect from Splunk AppDynamics?
Organizations in industries like finance and healthcare implement Splunk AppDynamics to monitor critical applications and infrastructure. Its capabilities in transaction tracking and AI-driven insights are crucial for maintaining system reliability, supporting technologies such as Java and .NET, and ensuring optimal resource utilization.
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