

Splunk Observability Cloud and Elastic Observability both compete in the observability market, offering specialized tools for monitoring and analytics. Splunk Observability Cloud appears to have the upper hand due to its robust real-time dashboards and efficient handling of large data volumes, which greatly enhance visibility and performance metrics.
Features: Users of Splunk Observability Cloud value its real-time dashboards, which provide vibrant metrics that enhance workflow visibility, along with its fast alerting system and comprehensive APM monitoring. Elastic Observability is recognized for its powerful log analytics capabilities, its flexibility in integrating seamlessly with other systems, and strong search functionalities that offer valuable insights.
Room for Improvement: Splunk Observability Cloud could benefit from greater pricing transparency and an enhanced log management experience, while users also suggest improving the log search performance and alerting system. Elastic Observability users call for improved APM capabilities, more detailed dashboards, and better machine learning features to enhance scalability and ease of use.
Ease of Deployment and Customer Service: Splunk Observability Cloud provides versatile deployment options, supporting both on-premises and cloud environments, with efficient customer support, though technical support could improve in speed and depth. Elastic Observability favors hybrid and on-premises deployments and gains positive feedback for customer support response times but could enhance consistency and support expertise.
Pricing and ROI: Splunk Observability Cloud is perceived as expensive, with users suggesting a need for pricing transparency, but it still delivers a strong return on investment through efficiency gains. Elastic Observability offers more predictable and affordable pricing, appealing to larger organizations, although smaller users may find it costly. Despite pricing differences, both solutions highlight operational impact through their ROI, with Elastic's pricing benefitting budget-conscious users more.
Elastic Observability has saved us time as it's much easier to find relevant pieces across the system in one screen compared to our own software, and it has saved resources too since the same resources can use less time.
We have saved considerable amounts of money, reducing our expenditures from around three to four crores to approximately one to one point two crores.
We have been able to save a great deal of money, and our profits have increased by twenty percent.
We've been able to lower our mean time to resolution and make sure that we are resilient and quickly recover from disasters.
Elastic support really struggles in complex situations to resolve issues.
Their excellent documentation typically helps me solve any issues I encounter.
On a scale of 1 to 10, the customer service and technical support deserve a 10.
They have consistently helped us resolve any issues we've encountered.
The customer support system is the foundational pillar of any successful business.
I rate the scalability of Elastic Observability as a ten, as we have never seen issues even with a lot of data coming in from more customers, provided we have the appropriate configuration.
Elastic Observability seems to have a good scale-out capability.
Elastic Observability is easy in deployment in general for small scale, but when you deploy it at a really large scale, the complexity comes with the customizations.
We've used the solution across more than 250 people, including engineers.
As we are a growing company transitioning all our applications to the cloud, and with the increasing number of cloud-native applications, Splunk Observability Cloud will help us achieve digital resiliency and reduce our mean time to resolution.
We have never seen any kind of downtime or crashes, as it has been absolutely very easy to scale.
There are some bugs that come with each release, but they are keen always to build major versions and minor versions on time, including the CVE vulnerabilities to fix it.
I would rate the stability of Elastic Observability as a ten, as we don't experience any issues.
Elastic Observability is really stable.
When downtime occurs, it raises concerns about how we measure and receive alerts, as everything needs to be in place.
Splunk Observability Cloud is very stable.
It is highly scalable because it can handle approximately up to one hundred applications at a time without any lapse or lag.
For instance, if you have many error logs and want to create a rule with a custom query, such as triggering an alert for five errors in the last hour, all you need to do is open the AI bot, type this question, and it generates an Elastic query for you to use in your alert rules.
It lacked some capabilities when handling on-prem devices, like network observability, package flow analysis, and device performance data on the infrastructure side.
Some areas such as AI Ops still require data scientists to understand machine learning and AI, and it doesn't have a quick win with no-brainer use cases.
The out-of-the-box customizable dashboards in Splunk Observability Cloud are very effective in showcasing IT performance to business leaders.
The next release of Splunk Observability Cloud should include a feature that makes it so that when looking at charts and dashboards, and also looking at one environment regardless of the product feature that you're in, APM, infrastructure, RUM, the environment that is chosen in the first location when you sign into Splunk Observability Cloud needs to stay persistent all the way through.
There should be a solution to update OTeL agents from Splunk Observability Cloud itself.
Elastic Observability is cost-efficient and provides all features in the enterprise license without asset-based licensing.
Observability is actually cheaper compared to logs because you're not indexing huge blobs of text and trying to parse those.
Many customers struggle to understand their total cost of ownership because Elastic licensing is not dependent on easy, quantifiable metrics such as number of users or amount of data.
Splunk is a bit expensive since it charges based on the indexing rate of data.
It is expensive, especially when there are other vendors that offer something similar for much cheaper.
I can confidently say our availability improved by forty percent, and downtime was reduced by approximately seventy to eighty percent.
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.
the most valued feature of Elastic is its log analytics capabilities.
Every integration, whether for Windows or Linux or even Palo Alto or Fortinet, installs the out-of-the-box dashboards along with it, making it easy to parse incoming data meaningfully and immediately start viewing dashboards to see what's happening in the platform.
Splunk provides advanced notifications of roadblocks in the application, which helps us to improve and avoid impacts during high-volume days.
For troubleshooting, we can detect problems in seconds, which is particularly helpful for digital teams.
It offers unified visibility for logs, metrics, and traces.
| Product | Mindshare (%) |
|---|---|
| Splunk Observability Cloud | 2.6% |
| Elastic Observability | 1.5% |
| Other | 95.9% |

| Company Size | Count |
|---|---|
| Small Business | 9 |
| Midsize Enterprise | 4 |
| Large Enterprise | 16 |
| Company Size | Count |
|---|---|
| Small Business | 38 |
| Midsize Enterprise | 9 |
| Large Enterprise | 70 |
Elastic Observability is known for its powerful search capabilities, central logging, and integration with cloud-native tasks. It enhances monitoring for applications and systems through its flexibility and machine learning features.
Elastic Observability is a robust tool offering end-to-end monitoring and performance analysis, widely utilized for application performance monitoring, centralized logging, and metrics collection. Kibana enables data visualization and connection of sources, while the platform aids in incident response with real-time insights. Despite its complex learning curve, limited customization, and licensing challenges, it remains valuable for businesses seeking to improve operational efficiency with additional support from log analytics and system automation.
What are the key features of Elastic Observability?A wide range of industries apply Elastic Observability for its capabilities in capturing significant data points to offer insights into business and technical performance. Its applications span log events, application monitoring, network protocol monitoring, and more, aiding in data-driven decision-making processes within sectors like IT, finance, and e-commerce.
Splunk Observability Cloud provides advanced real-time monitoring and AI-powered insights, streamlining operations and reducing downtime across diverse computing environments.
Offering powerful tools for real-time monitoring, Splunk Observability Cloud enhances performance visibility and operational resilience through AI insights and comprehensive dashboards. With No-Sample Tracing and customizable alerts, it allows quick issue detection and resolution. Its user-friendly interface and seamless integration facilitate troubleshooting and decision-making. The platform's unified infrastructure is equipped for environments like Kubernetes, ensuring stability and efficiency. Users report reduced downtime and increased transparency.
What are the key features of Splunk Observability Cloud?Splunk Observability Cloud is widely used for monitoring cloud infrastructures and microservices, optimizing AI applications, and enhancing application performance. It's integral in environments requiring real-time alerts, anomaly detection, and multi-cloud management, supporting use cases like infrastructure and application performance monitoring. Users leverage its capabilities for end-to-end visibility, focusing on metrics, logs, and traces for rapid problem-solving and performance assessment.
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