Logpoint and Elastic Observability are leading solutions in the observability space. Elastic Observability stands out due to its advanced feature set and functionality.
Features: Logpoint offers intuitive alert management, effective correlation capabilities, and a streamlined security incident response system. Elastic Observability provides extensive data ingestion, powerful analytics tools, and detailed monitoring features designed for larger organizations.
Room for Improvement: Logpoint users highlight the need for better integration options and expanding its third-party tool ecosystem. Elastic Observability users mention a steep learning curve, the need for an improved onboarding process, and the challenge of simplifying comprehensive features for new users.
Ease of Deployment and Customer Service: Logpoint is recognized for an easy deployment process and responsive customer service, making implementation smooth for most teams. Elastic Observability requires more technical expertise for setup, posing a challenge despite offering detailed customization and flexible deployment potential.
Pricing and ROI: Logpoint is preferred by budget-sensitive users due to lower setup costs and satisfactory ROI, aligning well with medium-sized enterprises. Elastic Observability, though more costly, offers a significant ROI through advanced capabilities, appealing to organizations seeking high-performance tools.
The technical support for Logpoint is very good, and I would rate it as nine out of ten.
Logpoint's customer support is not sufficient with only one engineer in the US.
Elastic Observability seems to have a good scale-out capability.
What is not scalable for us is not on Elastic's side.
It is web-based and accommodates the expansion of our organization.
Logpoint is scalable and capable of expanding.
It is very stable, and I would rate it ten out of ten based on my interaction with it.
Elastic Observability is really stable.
I have received reports indicating glitches and downtimes with Logpoint.
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.
Elastic Observability could improve asset discovery as the current requirement to push the agent is not ideal.
Dealing with foreign entities for support was a challenge, leading us to switch providers due to lack of adequate support.
Logpoint needs to be cloud-native, as currently, it is not.
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.
Elastic Observability is cost-efficient and provides all features in the enterprise license without asset-based licensing.
I rate the pricing at eight, suggesting it's relatively good or affordable.
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.
The UEBA enables us to monitor at the device level, and SOAR provides playbooks and templates that we can modify and incorporate into the platform.
It effectively facilitates logging and log storage and assists in security event management by ingesting security events.
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.
Logpoint is a cutting-edge security information and event management (SIEM) solution that is designed to be intuitive and flexible enough to be used by an array of different businesses. It is capable of expanding according to its users' needs.
Benefits of Logpoint
Some of the benefits of using Logpoint include:
Reviews from Real Users
Logpoint is a security and management solution that stands out among its competitors for a number of reasons. Two major ones are its data gathering and artificial intelligence (AI) capabilities. Logpoint enables users to not only gather the data, but also to maximize both the amount of data that can be gathered and its usefulness. It removes many of the challenges that users may face in data collection. The solution allows users to set rules for collection and then it pulls information from sources that meet the rules that have been set. This data is then broken into manageable segments and ordered. Users can then analyze these ordered segments with ease. Additionally, LogPoint utilizes both machine learning and AI technology. Users gain the ability to protect themselves from and if necessary resolve emerging threats as soon as they arise. The AI sets security parameters for a user’s system. These act as a baseline that are triggered and notify the user if anything deviates from the rules that it set up.
The chief infrastructure & security officer at a financial services firm writes, “It is a very comprehensive solution for gathering data. It has got a lot of capabilities for collecting logs from different systems. Logs are notoriously difficult to collect because they come in all formats. Logpoint has a very sophisticated mechanism for you to be able to connect to or listen to a system, get the data, and parse it. Logs come in text formats that are not easily parsed because all logs are not the same, but with Logpoint, you can define a policy for collecting the data. You can create a parser very quickly to get the logs into a structured mechanism so that you can analyze them.”
A. Secca., a Cyber Security Analyst at a transportation company, writes, “It is an AI technology because it is using machine learning technology. So far, there is nothing better out there for UEBA in terms of monitoring endpoints and user activity. It is using machine learning language, so it is right at the top. It provides that capability and monitors all of the user’s activities. It devises a baseline and monitors if there is any deviation from the baseline.”
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