Elastic Observability vs InfoScale comparison

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Elastic Observability

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Executive Summary

We performed a comparison between Elastic Observability and InfoScale based on real PeerSpot user reviews.

Find out in this report how the two IT Infrastructure Monitoring solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.

To learn more, read our detailed Elastic Observability vs. InfoScale Report (Updated: September 2026).

Elastic Observability vs. InfoScale

September 2026

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Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Categories and Ranking

Elastic Observability

Ranking in IT Infrastructure Monitoring

13th

Average Rating

8.0

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Application Performance Monitoring (APM) and Observability (11th), Log Management (14th), Container Monitoring (5th), Cloud Monitoring Software (12th)

InfoScale

Ranking in IT Infrastructure Monitoring

25th

Average Rating

8.6

Reviews Sentiment

6.1

Number of Reviews

Ranking in other categories

Data Loss Prevention (DLP) (19th), High Availability Clustering (1st), Disaster Recovery (DR) Software (13th), Data Storage for Kubernetes (2nd), Autonomous Operational Resilience (4th)

Mindshare comparison

As of October 2026, in the IT Infrastructure Monitoring category, the mindshare of Elastic Observability is 1.3%, down from 2.9% compared to the previous year. The mindshare of InfoScale is 0.1%. It is calculated based on PeerSpot user engagement data.

IT Infrastructure Monitoring Mindshare Distribution
Product	Mindshare (%)
Elastic Observability	1.3%
InfoScale	0.1%
Other	98.6%

IT Infrastructure Monitoring

Featured Reviews

Stefan Decuypere

Technology Consultant at Hybrid software

Real-time dashboards and visual insights have streamlined issue analysis and monitoring

After careful consideration about areas for improvement in Elastic Observability, aspects such as pricing, customization, implementation, and scalability could be improved. As a user of the system, I know what it costs but am not directly involved in cost-benefit evaluations or maintenance, which is handled by another team. I develop the visual representation of the data and frankly, I don't see major gaps in my application or anything I would really miss; I appreciate the fast pace of the developments that have occurred in the last couple of years. Regarding room for improvement in Elastic Observability, I would have preferred built-in tools to manage the indexes on deployment for better visual representation, as the initial feedback regarding system performance and data storage was fairly primitive and lacking.

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TABISH JAVED

Site Reliability Engineer (Certified) at Kyndryl India

Automated recovery has minimized downtime and supports seamless multi‑datacenter failover

Beyond pricing, there are areas where I would like to see InfoScale improved or enhanced. Veritas offers three management approaches. The first, which Veritas currently recommends, is Veritas Operation Manager. The second is the Cluster Manager Java Console graphical interface. The Cluster Manager Java Console has not been revised since version 6.1 or 6.2. This tool was critical for me, particularly valuable when managing small cluster footprints of 20 to 30 server nodes. I relied heavily on this tool, but Veritas has moved away from it in favor of Operation Manager. I recommend Veritas continue evolving this tool rather than discarding it. The third approach is the command line, suitable for individuals with extensive Veritas expertise and experience, but command line use in live environments consumed excessive time, leading me to prefer the graphical interface. Apart from pricing, I have not discovered disadvantages. The product is excellent. My concern is Veritas discarding the Cluster Manager Java Console in favor of Veritas Operation Manager. Setting up Operation Manager requires time and a dedicated server that runs continuously. I had to create a single server just for Veritas Operation Manager. While this works well for larger environments with hundreds of clusters, it is less useful for smaller deployments. I still recommend Veritas reconsider this application and evolve it by incorporating new features from Veritas Operation Manager. Adding these new features to the Java console would be beneficial because that tool runs on my laptop without consuming environment resources, and I can connect directly to clusters from my laptop. I am not opposing Veritas Operation Manager, which is excellent and resembles hardware management consoles for power machines, but smaller tools that previously performed these tasks should remain as options to provide clients with greater ease. From a features and functionality perspective, I do not find missing features in InfoScale at this moment. However, I am not actively using Veritas, managing only legacy machines on older hardware. I am upgrading operating systems but not Veritas due to contract expiration and end-of-life status. The contract is not being renewed because the customer wants to move away. Since I have not logged into VCS since 2021 and transferred responsibilities to another team, I am unaware of features arriving in version 8 or beyond and cannot comment specifically on recent Veritas introductions.

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Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros

"I think Elastic Observability is already in very good shape."

"The solution is open-source and helps with back-end logging. It is also easy to handle."

"It is a powerful tool that allows users to collect and transform logs as needed, enabling flexible visualization and analysis."

"It has always been a stable solution."

"I have built a mini business intelligence system based on Elastic Observability."

"Elastic Observability is highly stable; we ingested nearly 170 million records in the system and we have tested it, and you get your reports and dashboards within a few seconds, so it doesn't take much time."

"In addition to the fact that we are more proactive in the detection of incident before they occur, we can on one click see the request path from the customer to the backend."

"It is scalable and supports multitenancy, which is beneficial for MSPs."

More Elastic Observability pros

"The best feature is that it supports high availability and automatic failover, which minimizes downtime and helps the environment reduce downtime and improve high availability for critical applications."

"The best feature in InfoScale is the file system, which is the greatest feature as you can get any storage LUN from any hardware because it's software-defined and create a volume that can consist of storage from two or more different vendors, which avoids any vendor lock-in and makes it easier when you expand as time goes."

"InfoScale does that all by itself without any dependency on different solutions."

"It offers High Availability for many applications, including Oracle and SAP environment."

"It's a stable solution."

"InfoScale's ability to maintain data integrity and availability during a cyber event such as a ransomware attack is excellent."

"From a recovery standpoint, InfoScale is excellent and easy to manage."

"It integrates well with other solutions."

More InfoScale pros

Cons

"There could be more low-code features included in the product."

"Elastic Observability’s price could be improved."

"The auto-discovery isn't nearly as good. That's a big portion of it. When you drop the agent onto the JVM and you're trying to figure things out, having to go through and manually do all that is cumbersome."

"One example is the inability to monitor very old databases with the newest version."

"I would have preferred built-in tools to manage the indexes on deployment for better visual representation, as the initial feedback regarding system performance and data storage was fairly primitive and lacking."

"It lacked some capabilities when handling on-prem devices, like network observability, package flow analysis, and device performance data on the infrastructure side."

"Elastic Observability is difficult to use. There are only three options for customization but this can be difficult for our use case. We do not have other options to choose the metrics shown, such as CPU or memory usage."

"The tool's scalability involves a more complex implementation process. It requires careful calculations to determine the number of nodes needed, the specifications of each node, and the configuration of hot, warm, and cold zones for data storage. Additionally, managing log retention policies adds further complexity. The solution's pricing also needs to be cheaper."

More Elastic Observability cons

"It could be more stable and more secure."

"While InfoScale is mainly used by enterprise-level customers, it does not inherently support many applications, which presents a scalability issue."

"The primary concern is licensing cost, as the customer is unwilling to invest further and has begun cost-cutting measures."

"Many customers can see the benefits of InfoScale, but they are usually not able to buy the products and solutions because of the licensing costs."

"Based on my experience with support, I would rate them a nine, only because occasionally the first person I talk to does not know more than I do and it needs to be escalated to reach someone more knowledgeable."

"Many customers can see the benefit of InfoScale, but they are usually not able to purchase the product because the license cost is very high."

"My experience with pricing, setup cost, and licensing is that it is a bit expensive, but rather than that, because it is used in critical environments with no competitor, most of the customers go for it anyways."

"It's very difficult to implement."

More InfoScale cons

Pricing and Cost Advice

"The product is not that cheap."

"So far, there are just the standard licensing fees. Several of the components are embedded in the license or are even open source. They're even free depending on what you use, which makes it even more appealing to someone that is discussing pricing of the solution."

"There are two types: cloud and SaaS. They charge based on data ingestion, ingest rate, hard retention, and warm retention. I believe it costs around $25,000 annually to ingest 30GB of data daily. That is the SaaS version. There is also a self-managed license where the customer manages their own infrastructure on-prem. In such cases, there are three license tiers that respectively cost $5,000 annually per node, $7,000 per node, and $12,500 per node."

"Since we are a huge company, Elastic Observability is an affordable solution for us."

"One needs to pay for the licenses, and it is an annual subscription model right now."

"Elastic Observability's pricing could be better for small-scale users."

"The product’s pricing needs improvement."

"The price of Elastic Observability is expensive."

More Elastic Observability pricing and cost advice

"Our clients pay for licensing on a yearly basis."

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915,341 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Financial Services Firm

14%

Computer Software Company

Comms Service Provider

Manufacturing Company

Financial Services Firm

18%

Manufacturing Company

Outsourcing Company

Media Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	9
Midsize Enterprise	4
Large Enterprise	16

By reviewers
Company Size	Count
Small Business	7
Midsize Enterprise	4
Large Enterprise	6

Questions from the Community

What is your experience regarding pricing and costs for Elastic Observability?

The problem is their licensing model, which is a bit confusing. Many customers struggle to understand their total cost of ownership because Elastic licensing is not dependent on easy, quantifiable ...

What needs improvement with Elastic Observability?

What is your primary use case for Elastic Observability?

My use case for Elastic Observability is observability, as we upload our customers' data, including logs, and when there is an issue, we can analyze what went wrong.

What is your experience regarding pricing and costs for Veritas InfoScale Availability?

My experience with pricing, setup cost, and licensing is that it is a bit expensive, but rather than that, because it is used in critical environments with no competitor, most of the customers go f...

What needs improvement with Veritas InfoScale Availability?

InfoScale can be improved if it added more robust reporting features; it has reporting, but it is very simple. If it created an integration with a reporting tool that makes it official, customers c...

What is your primary use case for Veritas InfoScale Availability?

My main use case for InfoScale is that we use it in many scenarios. In some scenarios, we use it for clustering for a product like Enterprise Vault, using InfoScale Enterprise, where we handle the ...

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Product Reports

Download Elastic Observability product report

Elastic Observability

October 2026

Download InfoScale product report

September 2026

Also Known As

No data available

Veritas InfoScale Availability, Arctera InfoScale for Kubernetes

Overview

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?

Centralized Logging: Streamlines the collection, analysis, and storage of log data.
Powerful Search: Provides robust search capabilities for quick access to relevant information.
Scalability: Supports growing data needs across diverse environments.
Real-time Telemetry: Ensures up-to-date insights and monitoring.
Platform Integration: Seamlessly connects with services like Teams and Slack.
Data Visualization: Enhances visibility with Elastic APM and Kibana.

What benefits and ROI should users explore in reviews?

Cost-effectiveness: Offers significant savings through efficient data management.
Rapid Incident Response: Minimizes downtime with quick troubleshooting tools.
Comprehensive Insights: Supports better business decisions with detailed data analysis.
Performance Tracking: Enables assessment of system effectiveness and improvements.

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.

Elastic

InfoScale delivers robust data availability and protection for enterprises by managing critical workloads across hybrid cloud environments, ensuring minimal downtime and seamless performance.

InfoScale is designed to enhance data resilience and operational efficiency. By enabling quick data access across hybrid infrastructures, it reduces potential downtime and enhances business continuity. Its scalable architecture adapts to dynamic workloads, providing reliable performance under pressure while maintaining seamless integration with cloud-based solutions.

What are the key features of InfoScale?

Data Resiliency: Ensures continuous data availability through advanced clustering and replication technologies.
Scalability: Supports dynamic scaling to meet changing demands without compromising performance.
Cloud Integration: Offers seamless transition and operation within cloud environments.
Automated Operations: Streamlines management processes with automation to reduce manual intervention.

What benefits and ROI should users consider?

Increased Uptime: Improved reliability translates to reduced business interruption.
Cost Efficiency: Potentially lowers operational costs through optimized resource allocation.
Enhanced Security: Provides robust protection measures for critical data assets.
Operational Agility: Facilitates swift adaptation to evolving business requirements.

InfoScale is particularly effective in sectors such as healthcare and finance where data integrity and uptime are crucial. Its implementation empowers industries to handle data-intensive operations efficiently, ensuring continuity and compliance with industry standards.

Sample Customers

PSCU, Entel, VITAS, Mimecast, Barrett Steel, Butterfield Bank

Wayne State University, Zenith Mart