Both Splunk APM and Elastic Observability are popular APM tools with distinct features, pricing structures, and user feedback. Splunk APM frequently appeals for its advanced machine learning capabilities, while Elastic Observability is noted for its customizable open-source platform.
Features: Splunk APM provides AI-driven analytics, comprehensive monitoring capabilities, and advanced machine learning features. Elastic Observability offers flexible data visualizations, extensive integrations, and customization options from its open-source approach.
Room for Improvement: Splunk APM needs better scalability, improved real-time data processing, and enhanced performance at scale. Elastic Observability requires better support, more out-of-the-box integrations, and stronger user support and integration enhancements.
Ease of Deployment and Customer Service: Splunk APM has a relatively straightforward deployment but receives mixed feedback on customer service responsiveness. Elastic Observability has a more complex deployment process but benefits from active community support and comprehensive documentation.
Pricing and ROI: Splunk APM is often seen as costly to set up but offers strong ROI through its advanced features. Elastic Observability is generally viewed as more cost-effective due to its open-source model, appealing to budget-conscious users.
They did not have a clear answer.
One example is the inability to monitor very old databases with the newest version.
Elastic Observability could improve asset discovery as the current requirement to push the agent is not ideal.
There is room for improvement in the alerting system, which is complicated and has less documentation available.
Elastic Observability seems to have a good scale-out capability.
What is not scalable for us is not on Elastic's side.
Elastic Observability is cost-efficient and provides all features in the enterprise license without asset-based licensing.
The license is reasonably priced, however, the VMs where we host the solution are extremely expensive, making the overall cost in the public cloud high.
It appears to be expensive compared to competitors.
It is very stable, and I would rate it ten out of ten based on my interaction with it.
Elastic Observability is really stable.
I would rate its stability a nine out of ten.
The most valuable feature is the integrated platform that allows customers to start from observability and expand into other areas like security, EDR solutions, etc.
All the features that we use, such as monitoring, dashboarding, reporting, the possibility of alerting, and the way we index the data, are important.
Splunk APM provides a holistic view of the application.
Elastic Observability is primarily used for monitoring login events, application performance, and infrastructure, supporting significant data volumes through features like log aggregation, centralized logging, and system metric analysis.
Elastic Observability employs Elastic APM for performance and latency analysis, significantly aiding business KPIs and technical stability. It is popular among users for system and server monitoring, capacity planning, cyber security, and managing data pipelines. With the integration of Kibana, it offers robust visualization, reporting, and incident response capabilities through rapid log searches while supporting machine learning and hybrid cloud environments.
What are Elastic Observability's key features?Companies in technology, finance, healthcare, and other industries implement Elastic Observability for tailored monitoring solutions. They find its integration with existing systems useful for maintaining operation efficiency and security, particularly valuing the visualization capabilities through Kibana to monitor KPIs and improve incident response times.
Splunk APM is a comprehensive application performance monitoring solution that provides real-time insights into the performance and availability of your applications.
It offers end-to-end visibility across the entire application stack, from the front-end user experience to the back-end infrastructure. With Splunk APM, you can proactively identify and resolve performance issues, optimize application performance, and ensure a seamless user experience.
Splunk APM leverages machine learning and AI-powered analytics to automatically detect anomalies and provide actionable insights. The product supports a wide range of programming languages and frameworks, making it suitable for both monolithic and microservices-based architectures. It also integrates seamlessly with other Splunk products, allowing you to correlate APM data with logs, metrics, and other operational data for a holistic view of your application environment.
With its intuitive interface and powerful features, Splunk APM empowers developers, operations teams, and business stakeholders to deliver high-performing applications and drive better business outcomes.
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