Elastic Observability and Cribl compete in the observability solutions category, with Elastic offering a broader feature set while Cribl excels in real-time data handling capabilities, making them stand out in different aspects as per user assessments.
Features: Elastic Observability provides an open-source platform enriched with machine learning features, comprehensive logging, and integrated tools for alerting, which are particularly beneficial for large-scale deployments. Cribl, on the other hand, is known for its real-time data transformation within pipelines, flexible data routing, and easy plugin configurations, allowing for efficient handling of large data volumes.
Room for Improvement: Elastic Observability needs improvements in automation and better visualization, along with enhanced APM capabilities. Users also indicate that its support system needs broadening to incorporate a wider user base. Cribl could benefit from enhancements in documentation, additional custom packs for log management, and addressing legacy integration issues, in addition to refining its versioning system for improved user accessibility.
Ease of Deployment and Customer Service: Both Elastic Observability and Cribl support cloud and hybrid environments effectively. Elastic boasts strong documentation and community support, whereas Cribl receives positive ratings for its technical support. Elastic's widespread community offers additional resources, enhancing its troubleshooting capabilities.
Pricing and ROI: Elastic Observability offers cost-effective solutions ideal for large enterprises, providing good ROI by improving incident response times. However, its pricing may not be as favorable for smaller users. Cribl is noted for being budget-friendly, especially compared to competitors like Splunk, with a pricing model that proves cost-effective for managing larger data requirements.
The community, including the engineering and sales teams, is available on Slack and is very supportive.
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.
Perhaps more flexibility in terms of metrics would be helpful.
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.
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.
The community on Slack is excellent for solving questions and getting ideas.
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.
Cribl optimizes log collection, data processing, and migration to Splunk Cloud, ensuring efficient data ingestion and management for improved operational efficiency.
Cribl offers seamless log collection directly from cloud sources, allowing users to visually extract necessary data and replay specific events for in-depth analysis. It provides robust management of events, parsing, and enrichment of data, along with effective log size reduction. Cribl is particularly beneficial for migrating enterprise logs, optimizing usage, and reducing costs while streamlining the transition between different log management tools.
What are Cribl's most important features?
What benefits and ROI should users look for?
Cribl is widely implemented in industries requiring extensive data management, such as technology and finance. Users leverage Cribl to handle log collection, processing, and migration efficiently, ensuring smooth operation and effective data analysis. It aids in managing temporary data storage during downtimes and better handling historical data, preventing data loss and allowing extended periods for viewing statistics and monitoring trends.
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.
We monitor all Application Performance Monitoring (APM) and Observability reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.