

Find out in this report how the two Cloud Monitoring Software solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
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.
The primary return comes from its effectiveness, leading to significant cost savings, especially since we can create tenants and allow multiple countries to utilize the nodes through shared tools.
It saves time by issuing alerts that notify engineers about problems or incidents.
Elastic support really struggles in complex situations to resolve issues.
Their excellent documentation typically helps me solve any issues I encounter.
the support is quick and meets service-level agreements
I get an instant response and on-call support as well.
The complexities and internal processes in approvals necessitate a more tailored support approach, ensuring that assistance is relevant and timely.
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.
The product is very easy to scale.
A single polling engine with enterprise supports up to 100 additional polling engines, monitoring up to 100,000 elements per instance.
The scalability of SolarWinds Hybrid Cloud Observability is great.
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.
It is very stable, and I would rate it ten out of ten based on my interaction with it.
I would rate the stability of Elastic Observability as a ten, as we don't experience any issues.
In my current environment, we have experienced instability likely due to the deployment not meeting required standards.
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 solution could improve in areas such as CICD observability.
The initial setup and configuration can also be complex for new users.
I think deeper integration into Kubernetes, serverless functions, and cloud-native tracing can be implemented as these matter to many organizations.
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.
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.
The pricing is mid-segment, which means it is neither cheap nor expensive compared to other products.
The new pricing models lack clarity in communication, bundling services that we may not actually need, leading to unnecessary costs.
Before, everything was licensed. Now with SaaS, it is easy, but some companies say that they are SaaS, but their business model is a license, so it is difficult to do business with them.
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.
All the features that we use, such as monitoring, dashboarding, reporting, the possibility of alerting, and the way we index the data, are important.
It is easy to scale by increasing the count of observable objects, adding additional servers, and polling engines, which is crucial for enterprise-level projects.
It has an alerting engine where I can define thresholds and configure custom alerts, which can also be integrated with ITSM or a ticketing system to auto-create tickets.
Smart Alerts in SolarWinds Hybrid Cloud Observability has been really helpful for our team. For instance, one day, a switch interface started hitting high utilization, which would have caused slowness in network traffic. SolarWinds Hybrid Cloud Observability sent an alert immediately, so we could check the devices and fix the issue before users noticed any problem.
| Product | Market Share (%) |
|---|---|
| Elastic Observability | 3.0% |
| SolarWinds Hybrid Cloud Observability | 0.8% |
| Other | 96.2% |

| Company Size | Count |
|---|---|
| Small Business | 9 |
| Midsize Enterprise | 4 |
| Large Enterprise | 16 |
| Company Size | Count |
|---|---|
| Small Business | 3 |
| Midsize Enterprise | 1 |
| Large Enterprise | 4 |
Elastic Observability offers a comprehensive suite for log analytics, application performance monitoring, and machine learning. It integrates seamlessly with platforms like Teams and Slack, enhancing data visualization and scalability for real-time insights.
Elastic Observability is designed to support production environments with features like logging, data collection, and infrastructure tracking. Centralized logging and powerful search functionalities make incident response and performance tracking efficient. Elastic APM and Kibana facilitate detailed data visualization, promoting rapid troubleshooting and effective system performance analysis. Integrated services and extensive connectivity options enhance its role in business and technical decision-making by providing actionable data insights.
What are the most important features of Elastic Observability?Elastic Observability is employed across industries for critical operations, such as in finance for transaction monitoring, in healthcare for secure data management, and in technology for optimizing application performance. Its data-driven approach aids efficient event tracing, supporting diverse industry requirements.
SolarWinds Hybrid Cloud Observability enhances IT operations with comprehensive visibility across hybrid environments for improved performance and uptime.
Providing a unified platform, SolarWinds Hybrid Cloud Observability allows IT teams to manage, monitor, and optimize both on-premises and cloud resources. It integrates seamlessly with existing tools, improving efficiency with robust data analytics and visualization. Its advanced features decrease time-to-resolution for system issues and help maintain system health.
What are the most important features of SolarWinds Hybrid Cloud Observability?SolarWinds Hybrid Cloud Observability is implemented across multiple industries like healthcare, finance, and manufacturing to ensure reliable performance and security of IT ecosystems. Its adaptability and comprehensive coverage make it a favored choice for enterprises managing both legacy and cloud-based infrastructures.
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