Microsoft System Center and Elastic Observability compete in the IT management and monitoring category. Microsoft System Center seems to have the upper hand in Microsoft's ecosystem integration, while Elastic Observability offers greater flexibility and cost-effectiveness for diverse infrastructures.
Features: Microsoft System Center is renowned for its robust integration with Microsoft products, offering comprehensive automation features and ease of configuration. It excels in deployment, patch management, and license tracking, proving valuable in Windows environments. Elastic Observability provides powerful search capabilities and is highly versatile due to its open-source nature. It supports real-time data analysis, allowing swift incident response, and offers diverse infrastructure monitoring.
Room for Improvement: Microsoft System Center could simplify multi-tenant environments and enhance integration with non-Microsoft products. Users request improved performance, better integration ease, and a modern interface. Elastic Observability faces challenges with limited APM capabilities, visualization, and automation. Users seek improved infrastructure monitoring, richer dashboards, and easier log retrieval.
Ease of Deployment and Customer Service: Microsoft System Center primarily operates in on-premises and hybrid settings, with complex setups and satisfactory yet occasionally delayed support. Elastic Observability offers flexibility across on-premises, public cloud, and hybrid environments, benefiting from its open-source framework. Both products deal with timely support challenges, but Elastic's diverse deployment options provide more adaptability. Microsoft users rely on traditional support channels, while Elastic users benefit from community-driven assistance.
Pricing and ROI: Microsoft System Center is higher in cost with annual licensing and support contract dependency but delivers over 50% ROI through in-house management. Elastic Observability is cost-effective, particularly with open-source components and competitive pricing against premium solutions. It suits larger organizations needing scalable monitoring but can be costly for small startups, with pricing tied to data and infrastructure usage requiring careful cost management.
Elastic Observability seems to have a good scale-out capability.
What is not scalable for us is not on Elastic's side.
It is very stable, and I would rate it ten out of ten based on my interaction with it.
Elastic Observability is really stable.
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.
Observability is actually cheaper compared to logs because you're not indexing huge blobs of text and trying to parse those.
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.
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.
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.
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.
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