Splunk Observability Cloud and Elastic Observability compete in the observability platform category. Splunk seems to have the upper hand due to its user-friendly dashboards and strong visualization capabilities, which are frequently highlighted by users.
Features: Splunk Observability Cloud is known for customizable dashboards, robust data ingestion, and swift log search and reporting. It provides end-to-end visibility and excels in visualization and user-friendliness. Elastic Observability is recognized for comprehensive APM capabilities, machine learning features, and powerful search abilities that integrate well with multiple tools. Its open-source options potentially reduce costs, appealing to budget-conscious users.
Room for Improvement: Splunk users express a need for better integration options, handling large data volumes, and refining automation capabilities. Elastic users need enhanced visualization tools and better integration support, while scalability and implementation complexity are challenges. Both could use more user-friendly features and cost efficiencies, but Splunk's cost is often more prohibitive than Elastic's flexible pricing.
Ease of Deployment and Customer Service: Splunk Observability Cloud is praised for its ease of use in hybrid and multi-cloud environments, though some learning curve is present. Customer support is generally good but could improve on response times. Elastic benefits from open-source simplicity in deployment but struggles with a steep learning curve and complex customization. Its support varies but generally meets expectations. Both require significant setup, but Splunk's support is perceived as slightly better.
Pricing and ROI: Splunk Observability Cloud is considered expensive, but the investment is seen as worthwhile due to its operational efficiency and incident management ROI. Elastic Observability offers a cost-effective alternative, especially with open-source options that are attractive to budget-focused users. Though pricing increases with scaling, it remains competitive. Splunk is noted for troubleshooting efficiency, while Elastic emphasizes cost-effectiveness.
They often require multiple questions, with five or six emails to get a response.
If any issues arise, we can raise a vendor case, and resolutions are provided in a timely and accurate manner.
They did not have a clear answer.
Elastic Observability seems to have a good scale-out capability.
What is not scalable for us is not on Elastic's side.
We've used the solution across more than 250 people, including engineers.
I would rate its scalability an eight out of ten.
It is very stable, and I would rate it ten out of ten based on my interaction with it.
Elastic Observability is really stable.
We rarely have problems accessing the dashboard or the page.
I would rate its stability a nine out of ten.
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.
One example is the inability to monitor very old databases with the newest version.
There is room for improvement in the alerting system, which is complicated and has less documentation available.
Customers sometimes need to create specific dashboards, particularly for applicative metrics such as Java and process terms.
It would be beneficial if server details could be retrieved directly in synthetic monitoring.
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.
Observability is actually cheaper compared to logs because you're not indexing huge blobs of text and trying to parse those.
Splunk Observability Cloud is expensive.
It appears to be expensive compared to competitors.
the most valued feature of Elastic is its log analytics capabilities.
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.
It offers unified visibility for logs, metrics, and traces.
Saving time with automation can save us weeks. It's improving our resilience.
Unlike other APMs, Splunk's service map is quite effective.
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 Observability Cloud combines log search, data integration, and dashboards for seamless monitoring, enhancing infrastructure visibility and security. Its cloud integration and scalability support diverse environments, improving operational efficiency.
Splunk Observability Cloud offers comprehensive monitoring tools with user-friendly interfaces, enabling end-to-end infrastructure visibility. Its real-time alerting and predictive capabilities enhance security monitoring, while centralized dashboards provide cross-platform visibility. Users benefit from fast data integration and extensive insights into application performance. Despite its advantages, improvements could be made in integration with other tools, data reliability, scalability, and cost management. Users face challenges in configuration complexity and require better automation and endpoint protection features. Enhancing AI integration, alerts, and adaptation for high-throughput services could further improve usability.
What are the key features of Splunk Observability Cloud?In industries like finance and healthcare, Splunk Observability Cloud is implemented for application performance monitoring and infrastructure metrics. Its ability to track incidents and analyze machine data benefits network infrastructure, while distributed tracing and log analysis aid in tackling security threats. Organizations often integrate it for compliance and auditing purposes, enhancing visibility into network traffic and optimizing performance.
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