Elastic Observability Reviews & Product Details

What I like most about Elastic Observability is the unified visibility it provides across logs, metrics, traces, and application performance—all within a single platform. Its powerful search and analytics features, along with AI-driven capabilities, make it easier to spot issues quickly and support better overall operational efficiency. Review collected by and hosted on G2.com.

The main areas I’d improve are the learning curve and the complexity of advanced configuration. I’d also like to see simpler cost management and dashboards that feel more intuitive and easier to navigate. Review collected by and hosted on G2.com.

Elastic Observability stands out by bringing logs, metrics, and APM traces together in one unified dashboard. Built on Elasticsearch, it delivers blazing-fast query performance, and the built-in AI Assistant helps engineering teams pinpoint root causes and resolve system outages instantly. Review collected by and hosted on G2.com.

Elastic Observability comes with a steep learning curve, and maintaining it can be complex—especially when it comes to managing agents and cluster configurations. On top of that, ingesting high volumes of logs and traces can make storage costs unpredictable, and those costs can rise quickly as you scale. Review collected by and hosted on G2.com.

We used it mostly for logs, and its easy to manage teams and roles so user dont get permission to see logs that they should not see, which is very important in banking system Review collected by and hosted on G2.com.

Updates are coming very fast, you have to keep up with them and watch expetionaly for major updates. Sometimes there are some metadata that take storage and are not easy to deal with Review collected by and hosted on G2.com.

Elastic Observability provides a comprehensive and generally intuitive UI/UX, making it easier to navigate logs, dashboards, alerts, and visualizations during troubleshooting. Its broad integration capabilities allow us to bring together data from different applications, infrastructure, and services, providing centralized visibility across the environment.

From a performance perspective, the ability to search and analyze large volumes of operational data quickly is particularly valuable during production incidents. This contributes directly to ROI by reducing investigation time and helping teams identify and resolve issues faster.

The available documentation, support, and onboarding resources are helpful when configuring integrations and building operational use cases. Additionally, the growing AI and intelligence capabilities have the potential to further improve troubleshooting through anomaly detection, event correlation, and assisted root-cause analysis.

Overall, its combination of usability, integrations, performance, and troubleshooting capabilities makes it a valuable platform for SRE and operational teams. Review collected by and hosted on G2.com.

Although the overall UI/UX is good, creating Kibana/KQL queries for complex pattern matching and detailed debugging can sometimes be difficult and time-consuming. Similarly, while Elastic provides extensive integrations, configuring and maintaining some integrations may require additional technical knowledge and effort.

Performance is generally strong, but managing large data volumes, retention, and complex searches requires appropriate configuration and capacity planning. This also affects pricing and ROI, as costs can increase with higher ingestion volumes and longer retention periods, making optimization important.

There is also a learning curve during onboarding, particularly around advanced queries, dashboards, integrations, and configuration. Documentation and support help, but simplifying these areas would improve adoption. More advanced AI-assisted troubleshooting, such as natural-language querying, intelligent query suggestions, automated event correlation, and root-cause recommendations, could further reduce this complexity. Review collected by and hosted on G2.com.

• Blazing Fast Analytics: Leverages the core power of Elasticsearch to query petabytes of log data and trace streams in real time.

• True Single Pane of Glass: Highly rated for its comprehensive APM maps, out-of-the-box Kubernetes/cloud integrations, and AI-driven root cause analysis assistants.

• OpenTelemetry Native: Seamlessly adopts open standards, minimizing vendor lock-in for modern engineering stacks. Review collected by and hosted on G2.com.

Complex Configuration: Can have a steep learning curve; complex deployments—like managing standalone Elastic Agents, shards, and JVM configurations—often require manual tuning. Review collected by and hosted on G2.com.

What I like most about Elastic Observability is how it connects investigation across logs, metrics, and traces. For me, the strongest appeal is being able to follow an incident from a symptom to the underlying evidence in one place. Review collected by and hosted on G2.com.

The part I’d find least helpful is the setup and tuning effort. Connecting logs, metrics, and traces only pays off when the data is consistently labelled and the dashboards and alerts are well configured. Review collected by and hosted on G2.com.

Smart search feature that lets me search a huge set of data instantly, since indexing happens immediately upon ingestion. With other data lakes, indexing typically takes much longer to complete, so searches aren’t available as quickly. Review collected by and hosted on G2.com.

One thing I dislike about Elastic Observability is the learning curve. You need to get comfortable with tools like the Elastic Query DSL, Kibana Lens, and the QL language, and that takes time. Because of this, team adoption can be slower than expected. Review collected by and hosted on G2.com.

Log storage

Kibana

Anomaly detection

Like that I have both security and observability on one platform

Really like the professional services team who is engaging with us Review collected by and hosted on G2.com.

Dashboards need effort sometimes, while solid product, you need to build expertise on the product.

Certifications are important but they are paid, I have gone through the free learning but paid is helpful Review collected by and hosted on G2.com.

I appreciate the ability to quickly search through large volumes of logs and metrics and correlate information from different systems, which makes troubleshooting much easier. The flexibility of Kibana dashboards is another aspect I really like, as we can build customized views for different teams and use cases. The initial setup was relatively easy, particularly for the basic integrations. Elastic agent and the available integrations made it straightforward to start collecting logs and metrics. Review collected by and hosted on G2.com.

Cost management can be challenging, especially with the large volumes of logs and metrics that we collect. It would be helpful to have more built-in tools to identify unnecessary data ingestion and control retention and storage costs. Having clearer recommendations showing which data sources or log types are causing the most ingestion and storage costs would be beneficial for identifying low-value data before it reaches Elasticsearch. Review collected by and hosted on G2.com.

It offers broad compatibility with many programming languages. It’s easy to understand and user-friendly, especially for beginners. Overall, it feels versatile and well-suited to a wide range of use cases. Review collected by and hosted on G2.com.

Application-level changes are needed for log collection from APM and observability. In some cases, the application or certain entities do not allow the application team or the third-party vendor to make the required code changes. Review collected by and hosted on G2.com.