Azure Monitor and Elastic Observability are two prominent tools in the observability market. Elastic Observability seems to have the upper hand due to its powerful features and flexibility.
Features: Azure Monitor users appreciate its straightforward interface, seamless integration with Azure services, and user-friendly experience. Elastic Observability is valued for its advanced analytics, powerful search capabilities, and support for a wide range of data sources.
Room for Improvement: Azure Monitor users suggest enhancements in complex query handling, cost predictability, and user experience related to feature complexity. Elastic Observability users recommend improvements in documentation, user training resources, and easing the learning curve.
Ease of Deployment and Customer Service: Azure Monitor benefits from tight integration with Azure's ecosystem, making deployment smoother for Azure users, while its customer service is generally well-regarded. Elastic Observability supports a more diverse infrastructure, offering flexible deployment options, but users report a steeper learning curve. Elastic's customer service receives positive feedback for responsive support.
Pricing and ROI: Azure Monitor's pricing is seen as predictable and reasonable, especially for existing Azure customers, providing a good ROI. Elastic Observability attracts users with its extensive capabilities, though its pricing can be higher. Users feel that despite the cost, Elastic's comprehensive features justify the investment and offer substantial ROI.
Azure Monitor helps prevent impacts on their system.
However, the second-line support is good.
Users end up getting no resolution from their team because they're outsourced vendors, and they don't have deeper expertise over any of the products they are referring to.
I would rate the support for Azure Monitor as a seven.
Elastic support really struggles in complex situations to resolve issues.
Azure Monitor is very scalable; there are no issues with scalability for different kinds of businesses.
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.
What is not scalable for us is not on Elastic's side.
Azure Monitor is working fine, yet I face a costing issue as if there are a lot of logs collected in the workspace or in the center, it becomes very costly.
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.
Elastic Observability is really stable.
If Azure Monitor can independently add one gigabyte, two gigabytes, or five gigabytes at least to log storage, I can fix the logs without syncing with Log Analytics Workspace and Sentinel.
The cost skyrockets once you start using it, and there are complaints that the actual cost of the Kubernetes cluster was less than the cost they were incurring for Azure Monitor.
The challenges with Azure Monitor are that it's initially complex to set up because you need multiple components.
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.
When I export logs into the application, workspace, log analytic workspace, and into Sentinel to read reports, I need to add storage, which increases the cost.
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 alerting features definitely help in reducing operational downtime for my customers by allowing us to get notifications in advance and take active actions.
Resource monitoring is essential.
The ease of access in Azure is significant because it's native to the platform and easy to integrate.
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.
Product | Market Share (%) |
---|---|
Azure Monitor | 5.1% |
Elastic Observability | 3.9% |
Other | 91.0% |
Company Size | Count |
---|---|
Small Business | 23 |
Midsize Enterprise | 6 |
Large Enterprise | 29 |
Company Size | Count |
---|---|
Small Business | 8 |
Midsize Enterprise | 4 |
Large Enterprise | 16 |
Azure Monitor is a comprehensive monitoring solution offered by Microsoft Azure. It provides a centralized platform for monitoring the performance and health of various Azure resources, applications, and infrastructure.
With Azure Monitor, users can gain insights into the availability, performance, and usage of their applications and infrastructure. The key features of Azure Monitor include metrics, logs, alerts, and dashboards. Metrics allow users to collect and analyze performance data from various Azure resources, such as virtual machines, databases, and storage accounts.
Logs enable users to collect and analyze log data from different sources, including Azure resources, applications, and operating systems. Azure Monitor also provides a robust alerting mechanism that allows users to set up alerts based on specific conditions or thresholds. These alerts can be configured to notify users via email, SMS, or other notification channels. Additionally, Azure Monitor offers customizable dashboards that allow users to visualize and analyze their monitoring data in a personalized and intuitive manner.
Azure Monitor integrates seamlessly with other Azure services, such as Azure Automation and Azure Logic Apps, enabling users to automate actions based on monitoring data. It also supports integration with third-party monitoring tools and services, providing flexibility and extensibility.
Overall, Azure Monitor is a powerful and versatile monitoring solution that helps users gain deep insights into the performance and health of their Azure resources and applications. It offers a wide range of features and integrations, making it a comprehensive solution for monitoring and managing Azure environments.
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.
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