Sumo Logic Reviews & Product Details

There has been lots of improvements since I wrote this review,

UI changes - its still optional like you can have a experience with new UI, but I still prefer old UI though.

AI Query - Like there is a bit learning curve to learn about how to query, now we can use a query agent to translate natural-language questions into search query. Review collected by and hosted on G2.com.

There are bunch of ways you can save money like Frex Pricing or Assigning data to infrequent/frequent tires,. etc, based on your use cases. But its still bit pricey. Review collected by and hosted on G2.com.

Sumo is our first line of defense and insight. The best time is its deep error logging reporting mechanism with real time traces. It has proven to be a worthy alerting tool helping in detecting in issue before users escalate. The error logs gives meaningful insights in bug reporting. Review collected by and hosted on G2.com.

The UX feels clunky to me, also for a beginner can be difficult to get hold of things quickly. The queries differs from standard SQL hence requiring little extra efforts. Review collected by and hosted on G2.com.

I have started to enjoy the new UI. After many years of using the old and stacking the tabs, I have come around to the new way. A course that I did the other day also took my parse skills to the next level. Review collected by and hosted on G2.com.

Id like them to take their AI tool to the next level. Currently I ask it some questions and its less adaptable than other inbuilt AIs. Review collected by and hosted on G2.com.

What stands out to me is Sumo Logic’s real-time analytics and ease of deployment. The agent-based and API-driven ingestion makes onboarding fast, and the query language is powerful yet intuitive. The platform’s machine learning capabilities for anomaly detection are also valuable for proactive threat detection and operational visibility. Review collected by and hosted on G2.com.

While the query language is powerful, there can be a learning curve for teams coming from tools like Splunk or Elastic. Advanced queries and dashboard optimization sometimes require deeper platform familiarity. Review collected by and hosted on G2.com.

- Runtime calculated fields are incredible. Unlike Datadog (where calculated fields must be defined at ingestion time), Sumo Logic lets you define them on the fly. This is a massive productivity boost when you’re iterating on queries or exploring new log patterns.

- Outstanding value. Hosting my entire company’s logs cost roughly $100/month, which is shockingly affordable compared to Datadog or similar platforms.

- Easy integration with Heroku. The setup was quick and straightforward—no complex pipelines or custom agents required.

- Powerful search and flexibility. Once you get comfortable with its syntax, the query language is expressive and great for digging deep into logs. Review collected by and hosted on G2.com.

- Clunky UI. The interface feels dated and can be unintuitive to navigate, especially compared to modern tools like Datadog or Grafana Cloud.

- Alerting delays. Alerts tend to fire a bit slower than other platforms. Datadog, for example, seems to detect and trigger incidents faster in my experience.

- Limited ecosystem integration. For larger organizations, the lack of tight integration with APM and error-tracking tools can create friction—you end up context-switching across multiple dashboards to investigate an issue. Review collected by and hosted on G2.com.

I like the integration that Sumo Logic has with various tools. I also really like the way it is possible to manage data and create dashboards. The data collection part is something I really appreciate, as well as the possibility of using agents for data collection. The integration with tools like Jira, Atlas, and Google Workspace makes the work much easier, especially because it already comes with pre-made dashboards. I also appreciate the extensive documentation it has, which helps a lot in daily tasks. Review collected by and hosted on G2.com.

I think the query language of Sumo Logic is a bit complex to handle. Additionally, in some dashboard elements, the way elements are organized on the screen is not very flexible, which could be a bit more adaptable, especially since the sizes are quite fixed. This hinders a bit. Another point is the new contract model that charges per query, which ends up being quite costly for companies, especially those from countries that do not have the dollar as their main currency. Review collected by and hosted on G2.com.

I love how Sumo Logic seamlessly brings together powerful analytics with an incredibly user-friendly experience. The platform’s real-time search and visualization capabilities stand out for their ability to update dashboards instantly and alert tickets with minimal delays, even when dealing with massive volumes. I appreciate the optimized query language, which offers the flexibility of advanced analytics at a field level while still being approachable enough for new team members to pick up quickly. Another standout feature is the platform’s reliability and scalability; its performance remains consistent whether we’re ingesting a few gigabytes or terabytes of data. Additionally, the built-in integration with cloud services like AWS, Kubernetes, and security tools saves a huge amount of setup time. Overall, Sumo Logic feels like a twofold multiplier for both operational and security teams, enhancing efficiency and reducing the manual burden significantly. Review collected by and hosted on G2.com.

While Sumo Logic is a robust platform, there are a few areas needing improvement. During peak ingestion periods, the dashboard and search functions can slow down, especially when handling very large datasets or complex queries. Although the query language is powerful, it can initially seem challenging, and the learning curve for deep dive analysis is steeper than expected for new users. Additionally, managing ingestion volume and associated costs require careful tuning to prevent unexpected log spikes. More proactive recommendations or automatic optimization features could help maintain predictability. Furthermore, while integrations are generally effective, some newer cloud services demand more manual configuration than preferred. Review collected by and hosted on G2.com.

The platform remains incredibly powerful yet accessible. The ease of use in terms of getting data in and the speed of the query language are top-tier. I appreciate how quickly you can go from a raw log to a meaningful visualization. The pre-built dashboards and the App Catalog make it easy to get immediate value without having to build everything from scratch. It feels like a platform built for engineers who need answers fast, not just a storage bin for data Review collected by and hosted on G2.com.

The new UI is a significant pain point. Specifically, the removal of the internal tabbing system has disrupted my workflow. In the old UI, I could manage multiple searches and dashboards within one browser window effortlessly. The new "browser-native" tab approach feels cluttered and makes it much harder to pivot between concurrent investigations without losing my place. Additionally, the navigation in the new UI feels more "click-heavy" and less intuitive for those of us who grew used to the classic layout. Review collected by and hosted on G2.com.

I really like how flexible it is for analyzing records. The visual dashboards are not only clean, but also very easy to share, which makes collaboration a lot smoother. Review collected by and hosted on G2.com.

You have to stay vigilant, because if you leave a console.log file behind or forget about it, it can generate gigabytes of garbage. Then your bill becomes an unpleasant surprise. Review collected by and hosted on G2.com.

What I appreciate most is the powerful real-time data evaluation. I rely on the machine learning features for anomaly detection, which I find invaluable. Rather than manually searching for error patterns or unusual traffic spikes, these tools enable us to validate CI/CD deployments in production with confidence, knowing that any regression will be detected immediately. Review collected by and hosted on G2.com.

One of the downsides is that managing collectors in dynamic environments such as Kubernetes demands ongoing maintenance. Additionally, although the dashboards serve their monitoring purpose, they lack the flexibility and visual sophistication found in dedicated visualization tools. Review collected by and hosted on G2.com.